Functional Neurology, Rehabilitation, and Ergonomics

Functional Neurology, Rehabilitation, and Ergonomics Volume 3, Number 2/3, 2013 Table of Contents

Editorial - Refinding Gerry Leisman

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Editorial Note

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Metabolic Diseases Driven by Immunoinflammation Aristo Vojdani

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Brain-Reactive Antibodies in Traumatic Brain Injury Aristo Vojdani

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The Role of Environmental Triggers in Neuroautoimmunity Aristo Vojdani and Jama Lambert

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Toxicant Loss of Immune Tolerance, Neurologic Disease, and Nutritional Strategies Datis Kharrazian The Potential Impact of Various Physiological Mechanisms on Outcomes in TBI, mTBI, Concussion and PPCS Joel Brandon Brock, Samuel Yanuck, Michael Pierce, Michael Powell, Steven Geanopulos, Steven Noseworthy, Datis Kharrazian, Chris Turnpaugh, Albert Comey, and Glen Zielinski DIME (Diplomatic, Information, Military and Economic Power) Effects Modeling System: Applications for the Modeling of the Brain Newton Howard and Gerry Leisman

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Anatomically Accurate Head Models and Their Derivatives for Dense Array EEG Source Localization Jasmine Song, Kyle Morgan, Sergei Turovets, Kai Li, Colin Davey, Pavel Govyadinov, Phan Luu, Kirk Smith, Fred Prior, Linda Larson-Prior, and Don M. Tucker A Novel ERP Pattern Analysis Method for Revealing Invariant Reference Brain Network Models Amit Reches, Dan Kerem, Noga Gal, Ilan Laufer, Revital Shani-Hershkovitch, Dalia Dickman, and Amir B. Geva Disrupted Axonal Fiber Connectivity As a Marker of Impaired Consciousness States Rafael Rodriguez-Rojas, Karla Batista, Yasser Iturria, Calixto Machado, Gerry Leisman, Robert Melillo, Mauricio Chinchilla, Philip DeFina, Maylen Carballo, and Juan M. Morales If It Is Localization then There Is No Development, Education, and Rehabilitation: Neuroeducation Needs to Be about Building Networks Gerry Leisman The Effect of Off Vertical Axis and Multiplanar Vestibular Rotational Stimulation on Balance Stability and Limits of Stability Frederick R. Carrick,Guido Pagnacco, Elena Oggero, Susan E. Esposito, James L. Duffy, Derek Barton, Matthew Antonucci, Jacob Shores, and Diana M. Stephens

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Poster Abstracts - 4th Annual Conference of the International Association of Functional Neurology and Rehabilitation

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IAFNR News and Events

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Literature Calling

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New York

Journal of

Functional Neurology, Rehabilitation, and Ergonomics The Official Journal of the International Association of Functional Neurology and Rehabilitation The aim of this interdisciplinary journal is to provide a forum for the fields of Biomedical and Rehabilitation Engineering, Neuropsychology, Clinical Neurology, Human Factors and Ergonomics, and vocational assessment and training to present critical ideas, theories, proof-of-concept for technology solutions, and data-based evaluative research to facilitate return to work or more effective functional development in children and adults. Functional Neurology, Rehabilitation, and Ergonomics is published quarterly by Nova Science Publishers, Inc. 400 Oser Avenue, Suite 1600 Hauppauge, New York 11788, USA Phone: (631) 231-7269 Fax: (631) 231-8175 E-mail: [email protected] Web: www.novapublishers.com ISSN: 2156-941X Institutional Subscription Rates per Volume (2013) Print: $295

Electronic: $295

Combined Print and Electronic: $442

Additional color graphics might be available in the e-version of this journal. Copyright © 2013 by Nova Science Publishers, Inc. All rights reserved. Printed in the United States of America. No part of this Journal may be reproduced, stored in a retrieval system, or transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical, photocopying, recording, or otherwise without permission from the Publisher. The Publisher assumes no responsibility for any statements of fact or opinion expressed in the published papers.

Editor-In-Chief Gerry Leisman Garden City, NY USA Nazareth, Israel Co-Editor-In-Chief Robert Melillo Garden City, NY USA Assistant Editor Production Janet Groschel Gilbert, AZ USA

Assistant Editor Production Alicia M. Zelsdorf Charlotte, NC USA

Assistant Editor News and Events Tricia Merlin Cape Canaveral, FL USA

Editorial Board Members Sergio Azzolino San Francisco, CA USA

Barbara Hicks Kingsford, MI USA

Jackie Oldham Manchester, UK

Randy Beck Perth, Australia

Newton Howard Cambridge, MA USA

Chandler Phillips Dayton, OH USA

Paul Berger-Gross Bayside, NY USA

Megan L. Hudson West Springfield, MA USA

Anthony L. Rosner Boston, MA USA

Eti Ben-Simon Tel-Aviv, Israel

Efraim Jaul Jerusalem, Israel

Peter Scire Peachtree City, GA USA

John A. Brabyn San Francisco, CA USA

Datis Kharrazian Carlspoor, CA USA

Fredric Schiffer Boston, MA USA

Orit Braun-Benjamin Karmiel, Israel

Samuel Landsberger Los Angeles, CA USA

Suryakumar Shah Pomona, NJ USA

Lynn M. Carlson West Springfield, MA USA

Calixto Machado Havana, Cuba

Maria E. Stalias Manhasset, NY USA Athens, Greece

Ted Carrick Cape Canaveral, FL USA

Joy MacDermid Hamilton, Ontario Canada

Emmanuel Donchin Tampa, FL USA

Joav Merrick Jerusalem, Israel

Andrew L. Egel College Park, MD USA

Raed Mualem Nazareth, Israel

Khosrow Eghtesadi West Palm Beach, FL USA

Paul Noone Hampton E. Victoria, Australia

Joseph Weisberg Great Neck, NY USA Leslie Weiser Boston, MA USA Seung Won Lee Seoul, S. Korea

EDITORIAL

Funct Neurol Rehabil Ergon 2013;3(2-3):143-146

ISSN: 2156-941X © Nova Science Publishers, Inc.

REFINDING

Gerry Leisman Editor-in-Chief FNRE Scientific Director F. R. Carrick Institute for Clinical Ergonomics, Rehabilitation, and Applied Neuroscience-USA The National Institute for Brain and Rehabilitation Sciences Biomedical Engineering ORT-Braude College of Engineering Karmiel, Israel University of the Medical Sciences, Havana, Cuba Re-mind (from 17th c. rememorate or think again), re-view (from Fr., revue to see again), re-place (to find a substitute), re-work (to make changes to something), re-play (to repeat), re-turn (from Latin re, back + tornare, turn). We can go on finding a myriad of examples of how “re” can be part of a compound word with many meanings all relating to the same concept. Something exists and one returns to it. When one contemplates numerous discoveries ranging from the atom, DNA, the earth and other planets in our solar system revolving around the sun and not the other way around, gravity, HiggsBosson, and so many other findings one usually does not wonder whether these were actually innovations. The so-called discoveries, certainly existed before they were “discovered.” Similarly, inventions such as the transistor, television, the motor car, airplanes, telephones, record players, CDs, computers, are inventions based on what was already known but never assembled in a fashion that could create a novel function. Discovery then allows us to obtain sight or knowledge for the first time such as finding out that your car was out of gas, a trivial but practical example of the concept. Alternatively the atom existed before Rutherford and the Physics Department at the University of Manchester, but science has allowed us to put what exists together for novel uses, such as positron emission tomography. Columbus, it is claimed, discovered the Americas. In this instance, "discovered" is probably not the correct word. Certainly Columbus put America on the proverbial map. It was his journey that spurred many to follow him and eventually led to the settling of this "new world" in the early 17th century by Europeans. However, when Columbus landed, there were already natives inhabiting the land, named Indians (later Native Americans) as Columbus initially thought he had reached India. These people would certainly take exception to their land being "discovered" as they were obviously aware of it prior to Columbus' arrival. While it is clear Columbus was not the first to inhabit the Americas, he certainly opened the door for the mass settlements that were to come. For small schoolchildren it is easy to explain that "Christopher Columbus discovered America" as this is the type of simplistic idea they can grasp, but for those capable of understanding the bigger picture, the actual truth is much more gray than black and white. The issue of discovery then is, therefore, rendered less important than the doors that it can open to the generation of ideas and understanding of fundamental principles and processes. In 1861, the

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French surgeon, Pierre Paul Broca, described two patients who had lost the ability to speak after injury to the posterior inferior frontal gyrus of the brain [1]. Numerous studies since Broca have examined the nature of the localization of speech and language based on Broca’s findings in his two patients. Clinical studies of Broca's aphasia often assume that the deficits in these patients are due entirely to dysfunction in Broca's area, thereby attributing all aspects of the disorder to this one brain region. In addition, functional imaging studies often rely on activation in Broca's area as verification that tasks have successfully involved language and speech centers. Despite these strong assumptions, the range of locations ascribed to Broca's area varies broadly across studies [2,3]. We can say the same about Wernicke and his localized region that contains motor neurons involved in the comprehension of language which he “discovered” in 1874, approximately ten years after Broca’s “discovery.” The region is located in the posterior third of the upper temporal convolution of the left hemisphere of the brain. It is reportedly uniquely important for the comprehension of speech sounds and is considered to be the receptive language center. Recent findings with language-impaired patients, however, have suggested that other regions also play a role in speech and language production, some of which are medial to the area originally described by Broca on the lateral surface of the brain. Given the historical significance of Broca's original patients and the increasing reliance on Broca's area as a major speech center, we thought it important to re-inspect these brains to determine the precise location of their lesions as well as other possible areas of damage. Here we describe the results of high-resolution magnetic resonance imaging of the preserved brains of Broca's two historic patients. It had been noted that both patients’ had lesions that extended significantly into medial regions of the brain, in addition to the surface lesions observed by Broca. Results also indicate inconsistencies between the area originally identified by Broca and what is now called Broca's area, a finding with significant ramifications for both lesion and functional neuroimaging studies of this well-known brain area [1,4]. Figure 1 indicates the conception of brain language organization held by most since the time of Broca and Wernicke.

Figure 1. Brain Organization for Language.

We have begun to “re-think” the nature of brain organization due to fMRI, PET, connectography and other new technologies. Broca was so important because like the easily grasped simplistic idea of Columbus “discovering America," and having swept 150 years of thinking from his proposition, rethinking and re-discovery amongst those capable of understanding the bigger picture, may actually also have the actual truth being more gray than black and white as represented in Fig. 2 where multiple stream models may be more likely [4].

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(A)

(B) Figure 2. (A) Multiple stream language model in which receptive language functions are organized into multiple self-organizing simultaneously active networks. (B) Grounded meaning indicates that the meaning of words and sentences are both "embodied" and neurologically distributed rather than localized.

Discoveries are not discoveries but “re-findings.” Consensus is developed through painstaking testing, re-testing, dissemination, teaching, learning, communication, and practice, which allows us to re-examine long held “truths” with results that may be quite different from those to which we hold fast. There is no orthodoxy. There are no teachings only findings and open minds continually “refind.”

REFERENCES [1]

Dronk NF, Plasisant O, Iba-Zissen, MT, Cabanis EA. Paul Broca's historic cases: high resolution MR imaging of the brains of Leborgne and Lelong. Brain. 2007;130(5):1432-1441.

146 [2] [3] [4]

Gerry Leisman Dronkers NF, Wilkins DP, Van Valin Jr. RD, Redfern BB, Jaegerc JJ. Lesion analysis of the brain areas involved in language comprehension. Cognition. 2004;92(1-2):145-177. Grodzinsky Y, Santi A. The battle for Broca’s region. Trends Cogn Sci. 2008;12(12):474-480. Leisman G. Children’s Language Production: How Cognitive Neuroscience & Industrial Engineering Can Inform Public Education Policy and Practice Forum on Public Policy. A Journal of the Oxford Roundtable. 2012;2012;(1):1-14. (http://forumonpublicpolicy.com/ vol2012.no1/archive/leisman.pdf)(http://forumonpublicpolicy.com/vol2012.no1/earlychild2012. html)

Funct Neurol Rehabil Ergon 2013;3(2-3):147

ISSN: 2156-941X © 2013 Nova Science Publishers, Inc.

EDITORIAL NOTE The following papers did not reach the editorial office for review prior to the publication deadline and resultantly are not included in the IAFNR Conference Issue. They will be included in FNRE Volume 3 Issue 4. Calixto Machado. Functional and Anatomic Connectivity in Disorders of Consciousness. Robert Melillo. qEEG Spectral and Coherence Assessment of Autistic Children in Three Different Experimental Conditions Madeline Cunningham. Unlocking Neuropsychiatric and Movement Disorders in Children Lilian Calderón-Garcidueñas. Brain-reactive autoantibodies and air pollution



METABOLIC DISEASES DRIVEN BY IMMUNOINFLAMMATION Aristo Vojdani Immunosciences Laboratories, Los Angeles, CA, USA

ABSTRACT Inflammation is normally a protective response that is part of the immune system’s reaction to infection. Chronic inflammation, on the other hand, is a sign that there is a breakdown in the immune response system, and leads to chronic inflammatory diseases. More and more researchers are finding evidence that associates low-grade chronic inflammation with metabolic dysfunction. Many metabolic disorders such as diabetes, atherosclerosis, ischemic heart disease, a variety of autoimmune diseases and other metabolic dysfunctions are linked to obesity, which is fast becoming a world-wide epidemic. These findings have been engendered by the increasing recognition and understanding of what has come to be called immunometabolism, the interplay between the two distinct disciplines of immunology and metabolism. Type 1 and type 2 diabetes are examples of disorders in which immunometabolism plays a role. The concept that autoreactive lymphocytes are involved in the destruction of beta-islet cells in chronic autoimmune type 1 diabetes has been known for many years. More recently, the release of proinflammatory cytokines and the promotion of infiltrating macrophages into islet cells has emerged as a mechanism for the loss of beta-islet cells in type 2 diabetes. Therefore, the detection of low-grade chronic inflammation and abnormal immunometabolism may assist in the identification of obese individuals who will be at risk for developing diabetes, cardiovascular disease, autoimmunity and other associated disorders. In this review we will discuss: 1. The role of M1 and M2 macrophages, and their switch in the inflammatory environment induced by inflammatory cytokines and adipokines. This includes TH1 cytokines such as interferon-alpha, proinflammatory cytokines such as TNF-alpha, and IL-6, IL-18, IL-22, NFkappaB, which are induced by factors such as bacterial endotoxins and leads to the generation of M1 pathogenic macrophages. 2. The contribution of T-cell subsets, in particular the involvement and upregulation of CD8 cytotoxic lymphocytes plus TH17 cells, and downregulation of TH3 regulatory T cells in adipose tissue. 3. Altered gut microbiota, the change of good to bad bacteria, and the induction of low-grade chronic inflammation, which could be responsible for the induction of obesity. 4. The effect of diet on the composition of gut microbiota and its regulation of immune and inflammatory diseases. Recommended protocols for regulation of gut microbiota and inflammatory responses by repairing the breach in the intestinal barriers.

Keywords: Inflammation, obesity, autoreactive lymphocytes, diabetes, diet, gut microbiota 

Correspondence: Dr. Aristo Vojdani Immunosciences Lab., Inc. 822 S. Robertson Blvd., Ste. 312 Los Angeles, CA 90035 e-mail: [email protected]

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INTRODUCTION In recent years special attention has been given to the interplay between the distinct disciplines of immunology and metabolism, and the formation of a new field of investigation called immunometabolism [1]. In the field of immunology it is recognized that effector cells of the immune system, such as natural killer cells, and cytotoxic cells are required to guard the body against tumors and infectious agents [2]. Likewise, it is well known that TH3 or FoxP3+ regulatory T cells guard the body against TH1/TH2 immune dysregulation, which occurs in autoimmunity and allergy. Furthermore, understanding this powerful homeostatic system has resulted in the realization that immune cells also affect non-immune functions such as metabolism, cardiovascular function and even neuroinflammation and neuodegeneration [3-5]. This cross-talk between the immune system and metabolism is based on the fact that behaviors of lymphocytes and other white blood cells are controlled by internal metabolic properties, and metabolic abnormalities, including obesity, results in the mobilization of the innate and adaptive immune systems, followed by low-grade, chronic inflammation, culminating in increased susceptibility to type 1 and type 2 diabetes [6,7]. This concept is not new as a chronic autoimmune disease, type 1 diabetes, involves the destruction of beta-islet cells by pathogenic CD8+ and CD4+ T cells, and at the same time, regulatory T (Treg) cells are reduced [8]. However, more recently, the immune system has emerged as playing a role in the pathogenesis of type 2 diabetes. This pathway includes the release of interleukin (IL) -1, a pro-inflammatory cytokine, thus promoting the infiltration of macrophages into islets [7,8]. Cyclic inflammation results in beta-islet cell loss. This chronic, low-grade inflammation also leads to another type 2 diabetes characteristic, that of obesity-induced insulin resistance [9]. Inflammation of obesity is seen in white adipose tissue (fat), while in lean individuals, adipose tissue contains normal-sized adipocytes (fat cells). Lean state adipocytes are activated by M2 macrophages and Treg cells, thus creating an anti-inflammatory milieu by releasing IL-10. Conversely, pro-inflammatory M1 macrophages and hypertrophic adipocytes are predominant in adipose tissue of the obese. Endoplasmic reticulum stress activates intra-cellular pro-inflammatory pathways, resulting in the secretion of IL-6 [10]. These inflammatory cascades dysregulate the insulin signaling process, which is the molecular feature of insulin resistance. The effect of metabolic stress on the immune system contributes to both the onset of diabetes and the development of late-stage diabetic complications, with the activation of not only the adaptive, but also the innate immune responses, promoting the proapoptotic or profibrotic processes of diabetic nephropathy [11,12]. Destructive pathways may also lead to additional diseases. Cardiovascular disease, also associated with low-grade, chronic inflammation, can be a comorbidity for diabetes. Therefore, understanding the role of immune system responses in obesity may assist in the identification of obese individuals who are at risk for developing type 2 diabetes and/or cardiovascular disease. To elucidate the epigenetic and environmental mechanisms playing a role in the pathogenesis of metabolic diseases, cross-discipline research is necessary. The complexity of the immune system and metabolism interface has brought multiple scientific worlds together. Research immunologists are now going beyond the classical autoimmune mediated diseases in order to study the emerging biological themes involving the cross-communications between body systems. The following is one such researcher’s personal story.

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YOU ARE WHAT YOU FEED YOUR MICROBIOTA In the classic boy-meets-girl fashion, the hero of this story [13], while in graduate school, met and married the girl of his dreams. Within two years he added a beautiful, healthy daughter to his family, “PhD” to his name and excess weight to his body. He had grown from 132.28 – 176.37 pounds (60 – 80 kilograms). During our hero’s post-doctoral fellowship conducted at Cornell University, he added 10 more kilograms; tipping the scale at just below 200 pounds. By the time he returned to his homeland, China, our hero’s waist measured 43.31 inches (110 centimeters). Of greater concern, his health, like that of his father (who had endured two strokes and whose cholesterol levels had spiked) and obese brothers, was poor. Prompted by the work of Jeffrey I. Gordon and colleagues at Washington University School of Medicine, St. Louis, Missouri, which showed a link between obesity and gut microbiota in mice, our hero adopted a diet regimen containing traditional Chinese food. Bitter melon and Chinese yam are fermented, pre-biotic foods that are believed to alter digestive bacterial growth. As a microbiologist, our hero not only monitored his weight loss during this simple therapy, he assessed his microbiome. Within two years, our hero lost 44.09 pounds (20 kilograms). Additionally, his health condition improved as his blood pressure, heart rate and cholesterol level came down. Changes were also happening in his gastrointestinal tract. An anti-inflammatory bacterium, Faecalibacterium prausnitzii, increased from undetectable to 14.5% of his total gut bacteria. What began as a personal experiment quickly developed into serious study. Our hero, Zhao Liping, Associate Director of Shanghai Jiao Tong University’s Shanghai Center for Systems Biomedicine, started with mice and now conducts clinical research on humans. He hopes to uncover the roles played by the microbiome in obesity, diabetes and liver function.

THE ROLE OF ADIPOCYTES AND ADIPOKINES IN INFLAMMATION AND METABOLIC DISEASES Once seen predominantly in industrialized, consumer-driven countries, today obesity is a worldwide epidemic and has spawned global research to better understand the biology of adipocytes in obese states [6]. Obesity is linked to a number of economically and societal burdensome diseases such as diabetes, atherosclerosis and ischemic heart disease. Researchers are finding evidence that links chronic, low-grade inflammation to obesity [14, 15], which plays a role in the development of obesity-linked disorders, most notably metabolic dysfunction.

Pro- and Anti-Inflammatory Adipokines in Obesity Adipose tissue is widely known to store energy. Lesser known is its capacity for secreting bioactive substances [16, 17] like an endocrine organ. These substances are collectively referred to as adipokines. The dysregulated expression of these factors, which may be caused by excess adiposity and adipocyte dysfunction, has been associated with the pathogenesis of different diseases processes via altered immune responses. Thus, researchers are investigating the immunoregulatory functions of adipose tissue. Identification of factors secreted by adipose tissue that promote inflammatory pathways and metabolic dysfunction or play a role in the suppression of inflammation and thus have positive effects on obesity-linked metabolic disorders are elucidating immunometabolism. Such findings support a concept that adipokines secreted by adipose tissue can contribute to metabolic dysfunction.

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Once an individual becomes obese, the secretory status of an adipose tissue depot can be altered by changes in the cellular composition of the tissue; these modifications may include alterations in the number, phenotype and localization of immune, vascular and structural cells, as well as the expression of adipokines, depending on the site of the depot [18, 19]. Adipocyte depots are found throughout the body including bone and major blood vessels, and organs such as the heart, kidneys and lungs [20]. A high-calorie diet can promote the development of a pro-inflammatory state in these adipocyte depots [20]. Although the functional importance of many of these individual adipose depots has yet been elucidated, recent findings suggest that diet-induced changes in their adipokine secretion can influence the function of the associated tissue [21]. Noted discoveries of adipose tissue components and their roles in inflammation include the following: complement factor D, or adipsin, was identified in 1987 as an adipokine [22]; tumor necrosis factor-alpha (TNF-alpha), a pro-inflammatory cytokine, was discovered in 1993 as a product of adipose tissue that is induced in animal models of diabetes and obesity and thus provides a functional link between inflammation and obesity [23]; then in 1994, leptin was identified as an adipose tissue-specific secreted protein that regulates food intake and energy expenditure in an endocrine manner [24]. The 1994 report identified the gene encoding leptin and shows the role of leptin in the regulation of feeding behavior. Similar to this, the identification of plasminogen activator inhibitor 1 (PAI1), a fibrinolysis inhibitor, as an adipokine that is strongly upregulated in visceral adipose depots in obesity [25] suggested a mechanistic link between obesity and thrombotic disorders. Around the same time, adiponectin, which is now known to act as an insulin sensitizer and antiinflammatory, was identified as an adipocyte-specific adipokine [26-28]. Interestingly, adiponectin expression was found to be decreased in the obese stage, while experimental animal studies have shown that adiponectin protects against several metabolic and cardiovascular disorders that are associated with obesity. Similar to pro- and anti-inflammatory cytokines, these component findings have led to the notion that metabolic dysfunction, due to excess adipose tissue mass, may partly be the result of an imbalance in the expression of pro- and antiinflammatory adipokines. This contributes to the development of obesity-linked complications.

Infiltration and Interaction of Immune Cells into Adipose Tissue Although adipocytes make up the bulk of adipose tissue, it is not alone. Also contributing to the growth and function of adipose tissue are pre-adipocytes, lymphocytes, macrophages, fibroblasts and vascular cells. The cellular composition of, and cell phenotypes in adipose tissue are changed in the obese state, as shown in human and experimental animal models of obesity [29,30], in which a large number of macrophages is seen. The recruitment of macrophages, more abundantly in visceral than subcutaneous adipose tissue [31], is linked to systemic inflammation and insulin resistance. However, as shown in both human and mice [29,30], a sustained weight loss results in the reduction of macrophages in adipose tissue, which is accompanied by a decrease in the pro-inflammatory profiles of these individuals. It has been recently reported that macrophages accumulate in adipose tissues in the early stage of weight loss, presumably as a result of adipose tissue lipolysis [32]. Fibroblasts, which produce extracellular matrix components, are also found in adipose tissue. Researchers have been able to show that metabolically dysfunctional adipose tissue produces excess matrix components [33]. This production may interfere with adipose mass expansion and also contribute to metabolic dysregulation. There seems to be mounting evidence that intercellular communication within adipose tissue is required for normal metabolic function (Figures 1, 2).


Figure 1. Lean with normal metabolic function.

Figure 2. Obese with full metabolic dysfunction.

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Production of Pro-inflammatory Adipokines In this paper, adipose tissue is described by two structural and functional classifications: lean, with normal metabolic function, and obese, with full metabolic dysfunction. Lean tissue’s major immune cells are M2 macrophages, CD4+ cells and the adipocyte-produced anti-inflammatory adipokines. In obese individuals, with full metabolic dysfunction, not only is the volume of adipocytes increased significantly; instead of M2 macrophages, the ‘alternatively activated’ macrophage phenotype, obesity leads to the recruitment and accumulation of M1 macrophages, the ‘classically activated’ macrophage phenotype [34]. These M1 macrophages become activated upon contact with toll-like receptor ligands, such as lipopolysaccharides (LPS) and produce a significant amount of proinflammatory cytokines. Furthermore, cytotoxic lymphocytes are also accumulated in adipose tissue of obese individuals. Together with M1 macrophages, these cytotoxic lymphocytes form a crown-link structure around the adipocytes, causing adipose tissue dysfunction and chronic inflammation [35-37]. A key immune function of macrophages is to remove apoptotic cells from circulation, thereby preventing the release of noxious substances. Researchers speculate that the crown-like structures in adipose tissue signifies a pro-inflammatory state that may be due to the impairment of macrophagemediated processes [38]. An inflammatory cascade begins with the stimulation of TH1 cytokines, such as interferon-γ (IFNγ), or with bacterial products like LPS, which leads to the generation of M1 macrophages, which in turn produces pro-inflammatory cytokines such as TNF-alpha and IL-6, expresses inducible nitric oxide synthase (iNOS) and produces reactive oxygen species (ROS) and nitrogen intermediates [39]. On the other hand, macrophages are polarized to the M2 phenotype by TH2 cytokines, including IL-4 and IL-13. It is important to note that M2 macrophages upregulate the production of IL-10, an antiinflammatory cytokine, and downregulate pro-inflammatory cytokine secretion, thus giving M2 macrophages an important role in the repair of injured tissues and the resolution of inflammatory states. The transcription of several genes, such as those encoding IL-1 receptor antagonist, macrophage mannose receptor 1, and arginase 1 is also upregulated in M2 macrophages [40]. With their distinct roles, M1 macrophages have been suggested as promoting insulin resistance while M2 macrophages protect against obesity-induced insulin resistance [41]. T cell subsets reside in adipose tissue and play a role in the regulation of macrophage phenotype. Lean mice have more CD4+ regulatory T cells in their adipose tissues and thus have a protection against pro-inflammatory macrophages, thereby a suppression of insulin resistance [42]. Insulin resistance can be linked to CD8+ effector T cells and Th1 cell-associated factors that initiate the recruitment and activation of macrophages in adipose tissues and promote a pro-inflammatory effect [43,44]. Obesity-induced imbalance between TH1 and TH2 type signals may thus influence the recruitment and activation of macrophages in adipose tissues. Macrophage activation can promote either a pathogenic and inflammatory state, or a non-inflammatory and protective environment. The full function of and communications between adipose tissue components is not fully understood; however, it is important to keep in mind that cellular composition has an influence on inflammation. The macroenvironment in obese adipose tissue can dysregulate T cell responses. Adipose tissue of obese mice, compared to lean mice, had more activated CD8+ effector T cells but fewer CD4+ T cells; furthermore, CD8+ T cell infiltration preceded the accumulation of macrophages [43]. The authors, Nishimura et al., of this study propose, “that obese adipose tissue activates CD8+ T cells, which drive recruitment of macrophages and their differentiation into an inflammatory rather than anti-inflammatory phenotype” [43]. Working on characterizing the populations of Treg cells in obese and lean adipose tissue, Feuerer and colleagues found that fat-associated Treg cells were shown to have a different gene expression profile from Treg cells found at any other site, a unique TCR


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repertoire and evidence of antigen-driven selection [42]. Another study found that TH1 cells in adipose tissue of obese mice is antigen driven [44].

Pro-inflammatory Cytokines in Adipose Tissue Cytokines, the immune system’s messengers, can be classified as anti-inflammatory or proinflammatory based on their individual effect on other cells. The pro-inflammatory cytokines that have been shown to play a significant role in adipose tissue include TNF, IL-6, and IL-18. Each is described below. TUMOR NECROSIS FACTOR (TNF) – TNF is well known to autoimmunity. This proinflammatory cytokine is mainly produced by monocytes and macrophages and plays a leading role in inflammatory cascades and multiple autoimmune diseases. In experimental animals, TNF expression has been shown to be increased in models of obesity and type 2 diabetes [23]. Conversely, insulin sensitivity improves in obese animals in which TNF-induced signaling is lacking [45]. Where it is present, a fully active TNF function attenuates insulin-stimulated tyrosine phosphorylation of the insulin receptor and IRS1 in muscle and adipose tissues, promoting insulin resistance [46]. As with other pro-inflammatory cytokines described here, TNF levels are increased in obesity and decline with reduction in weight. Likewise, TNF levels in blood have been found to positively correlate with markers of insulin resistance [47-49]. More work, however, needs to be conducted for a better understanding of TNF’s role in insulin resistance. To give a few examples, short-term administration of TNF-blocking reagents led to a reduction in systemic inflammation, but did not ameliorate insulin resistance in type 2 diabetic obese patients [50]; while blocking TNF secretion in patients with metabolic syndrome led to an increase in muscle adiposity [51]; and prolonged TNF neutralization improved fasting glucose levels in patients with metabolic syndrome [52]. INTERLEUKIN-6 (IL-6): IL-6 is suspected of contributing to obesity-related insulin resistance. Elevated plasma levels of IL-6 positively correlate with obesity in humans, while levels are decreased after weight loss [19]. Additionally, elevated levels of IL-6 are seen in patients with type 2 diabetes and thus, can be used as a predictive biomarker for the development of type 2 diabetes [19]. An estimated one third of circulating IL-6 is believed to be produced in adipose tissue; therefore, in an obese state, the secretion of IL-6 is thought to play a role in metabolic dysfunction. The mechanistic role played by IL-6 in insulin resistance is not yet agreed upon. IL-6 is known to suppress insulinstimulated metabolic actions in hepatocytes, a result of the induction of SOCS3 expression, and it has been shown that infusion of IL-6 into mice prevents insulin from suppressing glucose production in the liver [53]. Additionally, IL-6 deficiency may exacerbate hepatic insulin resistance and inflammatory conditions, while on the other hand, a reduction of IL-6 in adipose tissue can protect against the development of insulin resistance. Thus, IL-6 actions may be dependent upon the tissue (liver or fat) and the source (muscle or fat) [52-54]. INTERLEUKIN-18 (IL-18): IL-18 is also known to be produced by adipose tissues. Like IL-6, serum levels of IL-18 are increased during the obese state, and decline after weight loss. In mice, elevated secretion of IL-18 resulted in an increase of endothelial cell adhesion molecules, macrophage infiltration of the blood vessel wall and vascular abnormalities; in humans, increased levels of IL-18 were detected in atherosclerotic lesions, which are thought to be an indication of plaque instability [55,56]. Mice deficient in IL-18 have shown hyperphagia and have insulin resistance, hyperglycemia and/or obesity, all characteristics of metabolic syndrome [57]. IL-18 appears to have a complex role in coordinating inflammation and metabolism, which needs further research to elucidate.

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Macrophage Interactions Influence Metabolic Homeostasis in Adipose Tissue In a healthy state or metabolic homeostasis, adipose tissue macrophages (ATMs) and adipocytes interact in a way that favors the inhibition of inflammatory pathways in the adipocytes and the classical activation of the ATMs; this healthy interaction also maintains insulin sensitivity in the former and alternative macrophage (M2) activation in the latter [40-42]. Unsaturated free fatty acids (FAs), such as omega3 FAs, signal, via G-protein coupled receptor 120 (GPR120), to dampen NFkappaB activation in ATMs. NF-kappaB inhibition is also mediated by factors secreted by adipocytes. The decrease in NF-kappaB activity decreases transcription of IL-1beta, whereas decreased production of ceramides, an inflammasome activator, prevents activation of caspase-1. Lipolysis in adipocytes via CD5-like antigen (CD5l) and ingestion of saturated fatty acids is restrained in the lean state; this attenuates signaling via Toll-like receptors 2/4 (TLR2/4) in macrophages and adipocytes. These changes in the ATMs combine to maintain insulin sensitivity in adipocytes, decrease the production of chemotactic factors (leptin, S100A8/9, serum amyloid A [SAA]), reduce chemotaxis and recruitment of Ly-6C+CCR2+ inflammatory monocytes into adipose tissue, and decrease the production of complement protein C3, thus preventing activation of NF-kappaB in ATMs. Since activation of NF-kappaB is essential to the production of inflammatory cytokines, inhibition of NFkappaB signaling in adipocytes and ATMs by statins, glucocorticoids and resveratrol, as well as induction of alternatively activated ATMs by thiazolidinediones, holds some therapeutic promise in combating obesity-induced insulin resistance and metabolic dysfunction [58-59]. In an obese state brought about by excessive food consumption, macrophages are recruited into adipose tissue, promoting local inflammation and insulin resistance. Dietary saturated fatty acids activate TLR2/4 on ATMs. Activation of TLR2/4 on ATMs leads to activation of NF-kappaB inflammatory signaling cascades. This activation of NF-kappaB results in the production of inflammatory cytokines such as IL-1beta and TNF-alpha, which inhibits insulin action in neighboring adipocytes. In obesity, ceramides induce activation of NLRP3, which contributes to the formation of inflammasomes, further augmenting IL-1beta production [60]. The increased IL-1beta and TNF-alpha plus various chemokines and chemotactic factors (such as MCP-1 and leptin) further contribute to the inflammatory cascade and perpetuate crosstalk between the inflamed adipocytes and adipose tissue, macrophages T cells and beta-islet cells. The MCP-1 and other chemokines secreted by adipocytes and macrophages lead to recruitment of inflammatory monocytes which differentiate into classically activated macrophages to promote adipose tissue inflammation. The classically activated macrophages and adipocytes secrete abundant amounts of several chemo-attractants such as S100A8/9, MCP-1 and serum amyloid A (SAA) during obesity, which further recruits monocytes to the inflammatory environment [34,61]. ATMs release CD5l, which promotes lipolysis after being incorporated into adipocytes via CD36-mediated endocytosis. In a feed-forward loop, the released fatty acids resulting from the increased lipolysis induce expression of chemokines in a TLR4-dependent manner, leading to recruitment of Ly-6C+CCR2+ inflammatory monocytes and ATMs. Reciprocally, saturated FAs, C3 complement, and inflammatory cytokines (TNF-alpha, IL-1beta) sustain inflammatory cascades in classically activated ATMs. Reduction in circulating levels of adipokines potentiate leads to inflammatory (M1) activation of ATMs, resulting in inflammation. The wave of inflammation spreads from adipocytes to the other organs, e.g. liver and skeletal muscle, bringing about systemic insulin resistance [62] (Figures 3, 4).


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Figure 3. (1) Dietary saturated fatty acids activate toll like receptors 2/4 (TLR2/4) on adipose tissue macrophages (ATMs). (2) Activation of TLR2/4 on ATMs leads to activation of NF-kappaB inflammatory signaling cascades. (3) This activation of NF-kappaB results in the production of inflammatory cytokines such as IL-1beta and TNFalpha, which inhibits insulin action in neighboring adipocytes. (4) In obesity, ceramides induce activation of NLRP3, which contributes to the formation of inflammasomes, further augmenting IL-1beta production. (5) The increased IL-1beta and TNF-alpha plus various chemokines and chemotactic factors (such as MCP-1 and leptin) further contribute to the inflammatory cascade and perpetuate crosstalk between the inflamed adipocytes and adipose tissue, macrophages T cells and beta-islet cells. Modified from Nat Med: August 2011 Vol 17 (8) suppl, Metabolic Syndrome.

Low-Grade Inflammatory Responses and Metabolic Diseases Inflammation is a beneficial immune response designed by nature to protect the body from infection, and to restore damaged tissues after acute trauma. Chronic inflammation, defined as persisting for weeks, months or years, leads to chronic inflammatory diseases. Chronic inflammation is a sign that there is a breakdown in the resolution of the immune response. Following is a summary of a recent Nature Conference, held at Keble College, Oxford, UK, and themed “Resolving Inflammation: Mechanisms and Drug Discovery” [63]. Increasingly evidence is accumulating to show that obesity causes chronic low-grade inflammation, and that this continuous low-grade inflammatory condition contributes to systemic metabolic dysfunction, which is associated with obesity-linked disorders [6]. Clinical and epidemiological studies have been published that link the development of low-grade inflammatory immune response to metabolic diseases such as obesity and type 2 diabetes. C-reactive protein (CRP), a pro-inflammatory marker in the blood, is found in individuals with excess adipose mass or obesity. Increased levels of CRP and IL-6, its inducer, are predictive for the development of type 2 diabetes [14,15]. Lifestyle changes aimed at weight loss for these individuals have resulted in reductions in the levels of pro-inflammatory markers including CRP and IL-6 [64].

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Since microbiome disharmony, in general, and microbiota imbalance or gut dysbiosis is responsible for the induction of low-grade inflammation, and hence, obesity, the following section will describe the role of infection, in particular altered gut microbiota, in obesity.

Figure 4. (6) The MCP-1 and other chemokines secreted by adipocytes and macrophages lead to recruitment of inflammatory monocytes which differentiate into classically activated macrophages to promote adipose tissue inflammation. (7) The classically activated macrophages and adipocytes secrete abundant amounts of several chemo-attractants such as S100A8/9, MCP-1 and serum amyloid A (SAA) during obesity, which further recruits monocytes to the inflammatory environment. (8) ATMs release CD5-like antigen (CD5l), which promotes lipolysis after being incorporated into adipocytes via CD36-mediated endocytosis. (9) In a feed-forward loop, the released fatty acids resulting from the increased lipolysis induce expression of chemokines in a TLR4-dependent manner, leading to recruitment of Ly6C+CCR2+ inflammatory monocytes and ATMs. (10) Reciprocally, saturated FAs, C3 complement, and inflammatory cytokines (TNF-alpha, IL-1beta) sustain inflammatory cascades in classically activated ATMs. Modified from Nat Med: August 2011 Vol 17 (8) suppl, Metabolic Syndrome.

Altered Gut Microbiota and Metabolic Syndrome Two landmark programs were launched for the study of gut microbiota and its effect on the host. In the US, the Human Microbiome Project (HMP), linked to the US National Institutes of Health, spent five years creating a reference database that will allow scientists to more rapidly sequence and assemble microbial genomes taken from humans and other animal subjects. Across the pond, Metagenomics of the Human Intestinal Tract (MetaHIT), a European program, worked for four years on a sequencing study of 124 subjects from Denmark and Spain. MetaHIT counted 3.3 million genes in the gut alone. Using 300 volunteers, HMP decoded microbial genomes found in the gut, mouth, nose, skin and reproductive tract. Sadly, both programs are ending this year. However, publications from these two groups are filling the pages of many scientific journals and providing scientists,


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researchers and clinicians with important information that may help in the prevention or management of many inflammatory autoimmune conditions. The increasing incidence of metabolic diseases is thought to be the result of excessive food consumption, leptin deficiency and reduced levels of physical activities. The hallmarks of this disorder include high cholesterol, high triglycerides, hyperglycemia, insulin resistance and increased fat mass throughout the body [65]. Recent work suggests a possible role for gut microbiota and its induction of low-grade chronic inflammation in obesity [66]. In both lean and obese human volunteers, as well as genetically obese mice and their lean counterparts, comparisons of gut microbiota were made using shotgun sequencing of microbiomes [66]. Shifts in the relative abundance of two bacterial phyla, Bacteroidetes and the Firmicutes, in both humans and mice, correlated with the development of obesity. Bacteroidetes and the Firmicutes are two major members of the more than 50 known divisions of bacteria making up more than 90% of all phylogenetic types in mice and in humans [67], and the Bacteroidetes to Firmicutes ratio in humans and in mice is about 3:1. Interestingly, this ratio changes significantly in the obese state. The relative abundance of Bacteroidetes in obese mice is reduced by 50%, while the Firmicutes are increased by a similar percentage [68]. In other words, the ratio of Bateroidetes to Firmicutes in obese individuals is more in favor of Firmicutes. These differences cannot be attributed to differences in relative food consumption since the obese mice had reduced chow consumption, but still exhibited marked increases in percent body fat. Furthermore, the percent body fat correlated with an increase in the ratio of Firmicutes to Bacteroidetes [68] (Figure 5).

Figure 5. Correlation of body weight to ratio of Firmicutes to Bacteroidetes.

When an obese human is put on either a low-fat, or carbohydrate-restricted, diet, they lose weight and the weight loss correlates with relative abundance of Bacteroidetes [66] (Figure 5). Moreover, the increase in Bacteroidetes was correlated with weight loss but not total caloric intake [69]. It appears the obese microbiome has an increased capacity to harvest energy from the diet; this trait of increased energy harvest from the diet is transmissible. It has been shown that transfer of gut microbiota from obese to wild-type germ-free mice caused an increase in fat mass in the recipient mice. This data leads to speculation that gut microbiota promote obesityp Using mice that are prone to develop type 1 diabetes mellitus, scientists found that if altered gut microbiota is transplanted into germ-free recipients, the functional characteristics of the donor microbiota are transferred as well [70]. The obesity trait was transmissible by transplanting microbiota of leptin-deficient, ‘obese’ mice into germ-free mice [66], or by transplanting a Western-dietassociated microbiome to germ-free mice, even if the donor recipient mice consumed a standard, lowfat, high-carbohydrate diet after transplantation [71].

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We are Never Alone: Our Co-developing Microbiota The number of microorganisms living on the outer surfaces of the human body, mouth, nose, lungs, skin, gastrointestinal tract, eyes, and reproductive tract outnumber the total cells of the human body. These friends of ours protect us, and thus are vital to our health. When the delicate balance within the microbiota environment is dysregulated, the host experiences inflammation. An inflammatory cascade can result in autoimmunity. Beginning at birth, the composition and activity of gut microbiota co-develop. The impact of the host genome, nutrition and lifestyle on gut microbiota is body-wide. Gut microbiota are involved through metabolic signaling and immune inflammatory pathways in not only the gut, but also the liver, muscle and brain. By understanding the roles that gut microbiota play in mechanisms of inflammation, one can better optimize therapeutic protocols by manipulation of gut microbiota and thus prevent disease onset and improve the overall health of the host. Just as a person’s fingerprint is unique, so is his microbiome. Unlike the fingerprint, which remains constant throughout one’s life (with the exception of the addition of scar tissue or ridges worn down from a lifetime of manual labor), the microbiota composition changes based on host nutrition, lifestyle stressors and antibiotic use. This composition is subject to the host’s phase of life and environment. Within the host microbiota compositions can change from one niche of the body to another, such as skin versus reproductive tract or upper gastrointestinal tract versus colon. The microbiota of an infant (Figure 6) are sown at birth. Delivery method and whether or not the infant is breastfed have influence on infant microbiota. Vaginally-delivered babies have microbiota compositions dominated by Lactobacillus, Prevotella and Atopobium, while Cesarean section babies have microbiota that resemble maternal skin composition, with staphylococci dominance [72]. If the baby is born with a lower number of Bifidobacteria, he has a greater chance of being overweight in later childhood [73]. Furthermore, a neonate is prone to ‘obesogenic microbiota’ if his mother is obese, suggesting a decreased number of Bifidobacteria at birth is a heritable trait [74]. During periand postnatal development, the predominance of aerobic bacteria is altered over the first few weeks of life to form a complex anaerobic-dominated microbial community [75]. It is during this stage of development that the activation of the hypothalamic-pituitary-adrenal (HPA) axis occurs. The HPA axis has an important impact on the enteric nervous system and thus the gastrointestinal tract. Aside from adolescent years, when there is a higher abundance of bifidobacteria and clostridia [76], core gut microbiota remains constant. At the age when immune function declines (60 + years), microbiota composition shifts, resulting in a significant decrease in Bifidobacteria [77]. A symbiotic relationship exists between gut microbiota and host immune system. At birth the microbiota shapes the immune system, which in turn, shapes the composition of the microbiota. An array of signaling pathways keeps these two constantly connected. Their complex interactions comprise a series of host-microbe metabolic axes. Nicholson et al. define such an axis as “a multidirectional interactive chemical communication highway between specific host cellular pathways and a series of microbial species, sub-ecologies and activities” [78]. Small molecules, low-molecular weight metabolites, peptides and proteins are co-produced by the host and its gut microbiota in order to transmit information between cells and microbial symbionts. As part of this signaling, humans excrete between 50 and 100 mg of volatile phenals per day, predominantly in the form of 4-cresol and phenol [79].


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Figure 6. Influences on microbiota through life.

Altered levels of 4-cresol metabolites in urine have been associated with a variety of physiological and pathological conditions including weight loss (differences in ratio of Firmicutes to Bacteroidetes [69]) and inflammatory bowel disease (loss of Lactobacillus and Bacteroides species [80]). A notable change in gut microbiota species ratio occurs in bariatric surgery, particularly gastric bypass. Such gastrointestinal trauma induces a marked shift in gut microbitoa composition from predominant Firmicutes and Bacteroidetes toward a predominance of gamma proteobacteria [81,82]. Post-surgery, Faecalibacterium prauznitzii has been shown to correlate inversely with inflammatory markers such as C-reactive protein and IL-6 [83].

Nutrition and Gut Microbiota A high-fat diet increases the proportion of gram-negative to gram-positive microbes in the gut [84]. A dominance of gram-negative microbes produces an increase in the release of LPS, endotoxins on the membrane of gram-negative bacteria. LPS induces gut inflammation, which may contribute to increased intestinal permeability. Leaky intestinal barriers allow the transference of LPS through the barrier. Increased toxin exposures triggers inflammatory cascades, which result in a decrease in the host’s metabolism. When LPS enters the blood stream, it has been shown to play detrimental roles in major depression [85], chronic fatigue syndrome [86], seizure disorders [87], atherosclerosis [88] and type 2 diabetes [89]. Furthermore, oral cavity Veillonella and Streptococcus combined with atherosclerotic plaques that contain more Proteobacteria species and fewer Firmicutes, correlates with atherosclerotic plaque formation [90]. An interesting target for restoring host immune function is n-butyrate. A short-chain fatty acid (SCFA), n-butyrate has many beneficial effects. It regulates neutrophil function and migration, inhibits inflammatory cytokine-induced expression of vascular cell adhesion molecule-1, increases expression of tight junction proteins, and reduces cytokine and chemokine release from human immune cells, which shows its anti-inflammatory effect [78].

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If diet affects the composition of gut microbiota, and it has been shown that microbiota regulates the immune and inflammatory responses [91] throughout the body, then quantifiable results on immune responses based on diet should easily follow. Indeed, small independent studies have been performed, but larger numbers in research have thus far been indirect [92]. Some study results are summarized in Table 1. Table 1. Effects of Diet on Inflammatory Diseases DIET

OUTCOME

Dietary Fiber in adequate or large amounts [92]

 Decrease in incidence of colitis  Decrease in incidence of type 2 diabetes  Decrease in incidence of cancer

Vegan diet [93]

 Diminishes severity of rheumatoid arthritis

Short Chain Fatty Acids [94]

 Improve inflammatory bowel conditions

Omega-3 Fish Oil [95]

 Decrease in inflammatory disease activity  Reduced need for use of anti-inflammatory drugs

Berberine [(rat study) 96]

 Protected against obesity, even with high-fat diet  Protected against the development of insulin resistance  Decrease in pathogenic populations of gut bacteria  Increase in beneficial gut bacteria

Dietary Fructans [97,98]

 Energy source for Bifidobacteria  Increased satiety  Decreased caloric intake  Decreased post-prandial glycaemia

Lipopolysaccharide Released by Gut Microbiota is Associated with Diet-Induced Obesity In the microbiology lab, students learn that each type of bacteria requires a specific medium for growth. Although the base of these media is agar-agar, it is not enough for many bacteria. In addition to agar-agar, bacteria desire specific carbohydrates, sugars, fatty acid proteins, such as rice, corn, soy, egg, whole blood, heart or brain, in order to grow. Similar to the growth of bacteria in test tubes and laboratory flasks, the human gastrointestinal tract and the composition of the gut microbiota is influenced by the diet and its components [99]. For example, it has been shown that low-intake of fiber, or complex plant polysaccharides, adversely affects the makeup of intestinal bacteria. This can lead to decreased production of immunomodulatory products, such as SCFAs, which are important for the overall regulation of immune function [100]. Accordingly, certain types of diets induce selective bacterial growth and release of endotoxins, or LPS. Immune responses against these bacterial toxins are likely the explanation for greater inflammatory diseases in developed countries [101]. Increased incidence of gut dysbiosis for the past six decades is associated with gastric ulcers caused by Helicobacter pylori infection, and life-stylerelated disorders such as obesity and diabetes. This proposed change in diet and microbiota, and their association with increasing incidence of inflammatory diseases such as asthma, obesity or type 1 and type 2 diabetes, is shown in Figure 7.


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Figure 7. Changes in diet and microbial composition may result in symbiosis or dysbiosis in the gut.

Diet and other environmental factors have a major effect on gut microbial composition. This suggests that balanced microbial composition results in symbiosis. If harmonious, there is regulation of immune and inflammatory responses through anti-inflammatory and/or immunomodulatory products, all of which help maintain homeostasis. Dysbiosis, therefore, would lead to dysregulation of the immune system via a lack of beneficial microbial products and an increase in bacterial endotoxic factors. This scenario leads to inflammation. Clearly, certain gut microbiota are required for the regulation of immune responses and any modification of this milieu may result in immune dysregulation, the overgrowth of pathogenic bacteria, the release of endotoxins, LPS, and the promotion of inflammation. People who are genetically susceptible to metabolic diseases are particularly prone to this inflammatory cascade [102]. It was recently reported that moderate increase of plasma concentration of LPS increased during a fat-enriched diet and defined metabolic endotoxemia [84]. It was demonstrated that LPS was responsible for the onset of metabolic disease due to a chronic low-rate infusion of LPS into circulation induced many of metabolic disease characteristics. Moreover, when LPS receptors were knocked out in animal models, the animals did not develop the disease. Change in the intestinal microbiota, due to antibiotic treatment to reduce the elevated concentration of plasma LPS, also reduced metabolic endotoxemia and the cecal LPS contents in high fat-fed and obese mice [103]. Therefore, it is clear that gut bacteria are involved in high-fat diet-induced metabolic endotoxemia.

Microbiota and the Immune System: Crossing Barriers Gut bacteria are usually confined to the luminal side of the gastrointestinal barrier. However, the sheer number of intestinal bacteria makes an occasional breach inevitable. Microorganisms that

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breach the intestinal barrier are typically phagocytosed and eliminated by lamina propria macrophages [104]. A sampling of the invader is taken by the immune system which induces the production of antibodies specific to that bacterial antigen. The next penetration of that antigen is met by a barrage of dendritic cells. Microbiota should not be seen only as inflammatory to the intestinal barrier, as described earlier. Indeed, microbiota can induce repair of damaged epithelial cells through an MyD88-dependent process; the innate signals, conveyed largely through myeloid cells, are required for the enhancement of epithelial cell proliferation [104]. Gastrointestinal tract tissue is rich in myeloid and lymphoid cells and it has long been established that the gut microbiota have a critical role in the development of organized lymphoid structures and the function of immune system cells. Bacteria have been shown to enhance the anti-inflammatory branches of the adaptive immune system by influencing the differentiation of Tregs or by inducing IL-10 expression. Within the intestinal tract, the balance of effector lymphoid cells and Treg cells can have a marked influence on how the mucosa responds to stresses that trigger inflammatory damage [104]. The influencing reach of gut bacteria on the balance of T cell subsets is now known to extend beyond the intestinal barrier.

Adipose Tissue Inflammation and Metabolic Disorders The effect of gut bacteria may be mediated by a mechanism that could increase, not only the release of LPS, but also gut permeability, and enhance LPS absorption and subsequent antibody production against it. Finally, it has been concluded that gut microbiota could control intestinal permeability, which determines the threshold at which metabolic disorders occur through endotoxemia [103]. A high-fat diet initiates the cascade that leads ultimately to metabolic disorders. With each stage (high-fat feeding, change in glut flora, increased gut permeability, increased LPS absorption, increased endotoxemia, low-grade inflammation, metabolic disorders) the fat cell grows and the inflammation increases. These findings are summarized in Figure 8. Poor diet, lack of exercise, daily stress and microbiome composition all play a role in metabolic disorders. Addressing all of these triggers in combination may help in a therapeutic approach to inflammatory, autoimmune, or metabolic conditions. Still, more work needs to be conducted to fully understand the role microbiota play in human immune responses. Nicholson and colleagues [78], pose challenges for future research into understanding the microbial impact on health. They state that we need: 1. Better understanding of maternal to fetus transfer of microbiota and influence of nutrition on infant development of microbiota. 2. To map the impact of early anti-biotic use in the developmental ecology, function and resilience of microbiota in childhood. 3. More knowledge on how gut microbiota influence drug metabolism, bioavailability, and toxicity. 4. To develop strategies for the in vitro culturing of complete microbiota in order to study bacterial species and their interactions within ecological constructs and ecosystems. 5. Comprehensive, cross-discipline studies to elucidate the changing interactions between the immune system and gut microbiota that affect gut, liver and brain function.


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Figure 8. Cascade leading to metabolic disorders.

Despite the ending of two great programs, HMP and MetaHIT, scientists will continue the work that was catalyzed by US and European researchers. Responses to the above may still be forthcoming. Until then, the recommended protocol is to regulate inflammatory responses, support the mucosal immune system and repair the breached intestinal tight junctions (Table 2). Table 2. How to Regulate Inflammatory and Immune Responses, and Repair Breach of Intestinal Barriers      

Include a regimen of pre- and probiotics whenever using antibiotics Include probiotics in daily supplement routine Consume complex plant polysaccharides Include mercury-free omega-3 fish oil in daily supplement routine Use vitamin A to support the mucosal immune system Get a daily dose of sun for the production of vitamin D, which helps to regulate the immune system and supports the mucosal immune system

REFERENCES [1] [2]

[3]

Mathis D, Shoelson SE. Immunometabolism: an emerging frontier. Nat. Rev. Immunol. 2011;11:81-3. Vojdani A, Mumper E, Granpeesheh D, Mielke L, Traver D, Bock K, Hirani K, Neubrander J, Woeller KN, O'Hara N, Usman A, Schneider C, Hebroni F, Berookhim J, McCandless J. Low natural killer cell cytotoxic activity in autism: the role of glutathione, IL-2 and IL-15. J. Neuroimmunol. 2008;205:148-54. Vojdani A, Erde J. Regulatory T cells, a potent immunoregulatory target for CAM researchers: the ultimate antagonist (I). eCAM. 2006;3(1):25-30.

166 [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19]

[20]

[21]

[22]

[23] [24] [25]

[26]

Aristo Vojdani Vojdani A, Lambert J. Functional neurology and immunology part III. Cell-mediated immunity. Funct Neurol Rehabil Ergon. 2011;1:443-60. Vojdani A, Lambert J. Function neurology and immunology part IV. Natural killer, T-cell and B-cell function in health and disease. Funct Neurol Rehabil Ergon. 2011;1:461-83. Ouchi N, Parker J, Lugus JJ, Walsh K. Adipokines in inflammation and metabolic disease. Nature Rev. Immunol. 2011;11:85-97. Donath MY, Shoelson SE. Type 2 diabetes as an inflammatory disease. Nature Rev Immunol. 2011;11:98-107. Todd JA. Etiology of type 1 diabetes. Immunity. 2010;32:457-67. Mandrup-Poulsen T. IAPP boosts islet macrophage IL-1 in type 2 diabetes. Nat Immunol. 2010;11:881-3. Olefsky JM, Glass CD. Macrophages, inflammation, and insulin resistance. Annu. Rev. Physiol. 1010;72:219-46. Gotamisligil GS. Endoplasmic reticulum stress and the inflammatory basis of metabolic disease. Cell. 2010;140(6):900-17. Navarro-Gonzáles JF, Mora-Fernández J. The role of inflammatory cytokines in diabetic nephropathy. Am. Soc. Nephrol. 2008;19:433-42. Hvistendahl M. My microbiome and me. Sci. 2012;336:1248-50. Hotamisligil GS. Inflammation and metabolic disorders. Nature. 2006;444:860-7. Shoelson SE, Lee J, Goldfine AB. Inflammation and insulin resistance. J. Clin. Invest. 2006;116:1793-1801. Ouchi N, Kihara S, Funahashi T, Matsuzawa Y, Walsh K. Obesity, adiponectin and vascular inflammatory disease. Curr. Opin Lipidol. 2003;14:561-566. Berg AH, Schere PE. Adipose tissue, inflammation, and cardiovascular disease. Circ. Res. 2005;96:939-49. Samaras K, Botelho NK, Chisholm DJ Lord RV. Subcutaneous and visceral adipose tissue gene expression of serum adipokines that predict type 2 diabetes. Obesity. 2010;18:884-9. Fried SK, Bunkin DA, Greenberg AS. Omental and subcutaneous adipose tissues of obese subjects release interleukin-6: depot difference and regulation by glucocorticoid. J. Clin. Endocrinol Metab. 1998;83:847-50. Chatterjee TK, Stoll LL, Denning GM, Harrelson A, Blomkalns AL, Idelman G, Rothenberg FG, Neltner B, Romig-Martin SA, Dickson EW, Rudich S, Weintraub NL. Proinflammatory phenotype of perivascular adipocytes: influence of high-fat feeding. Cir. Res. 2009;104:541-9. Takaoka M, Nagata D, Kihara S, Shimomura I, Kimura Y, Tabata Y, Saito Y, Nagai R, Sata M. Periadventitial adipose tissue plays a critical role in vascular remodeling. Circ. Res. 2009;105:906-11. Cook KS, Min HY, Johnson D, Chaplinsky RJ, Flier JS, Hunt CR, Spiegelman BM. Adipsin: a circulating serine protease homolog secreted by adipose tissue and sciatic nerve. Science. 1987;237:402-5. Hotamisligil GS, Shargill NS, Spielgelman BM. Adipose expression of tumor necrosis factor- : direct role in obesity-linked insulin resistance. Science. 1993;259:87-91. Zhang Y, Proenca R, Maffei M, Barone M, Leopold L, Friedman JM. Positional cloning of the mouse obese gene and its human homologue. Nature. 1994;372:425-32. Shimomura I, Funahasm T, Takahashi M, Maeda K, Kotani K, Nakamura T, Yamashita S, Miura M, Fukuda Y, Takemura K, Tokunaga K, Matsuzawa Y. Enhanced expression of PAI-1 in visceral fat: possible contributor to vascular disease in obesity. Nature Med. 1996;2:800-3. Hu E, Liang P, Spiegelman BM. AdipoQ is a novel adipose-specific gene dysregulated in obesity. J. Biol Chem. 1996;271:10697-10703.


167

[27] Maeda K, Okuboa K, Shimomuraa I, Funahashib T, Matsuzawab Y, Matsubaraa K. cDNA cloning and expression of a novel adipose specific collagen-linked factor, apM1 (AdiPose Most abundant Gene transcript 1). Biochem. Biophys. Res. Commun. 1996;221:286-9. [28] Scherer PE, Williams S, Fogliano M, Baldini G, Lodish HF. A novel serum protein similar to C1q, produced exclusively in adipocytes. J. Biol. Chem. 1995;270:26746-9. [29] Xu H, Barnes GT, Yang Q, Tan G, Yang D, Chou CJ, Sole J, Nichols A, Ross JS, Tartaglia LA, Chen H. Chronic inflammation in fat plays a crucial role in the development of obesity-related insulin resistance. J. Clin Invest. 2003;112:1821-30. [30] Weisberg SP, McCann D, Desai M, Rosenbaum M, Leibel RL, Ferrante, Jr AW. Obesity is associated with macrophage accumulation in adipose tissue. J. Clin. Invest. 2003;112:17961808. [31] Bruun JM, Lihn AS, Pedersen SB, Richelsen B. Monocyte chemoattractant protein-1 release is higher in visceral than subcutaneous human adipose tissue (AT): implication of macrophages resident in the AT. J. Clin. Endocrinol Metab. 2005;90:2282-9. [32] Kosteli A, Sugaru E, Haemmerle G, Martin JF, Lei J, Zechner R, Ferrante, Jr AW. Weight loss and lipolysis promote a dynamic immune resonse in murine adipose tissue. J. Clin. Invest. 2010;120:3466-79. [33] Khan T, Muise ES, Iyengar P, Wang ZV, Chandalia M, Abate N, Zhang BB, Bonaldo P, Chua S, Scherer PE. Metabolic dysregulation and adipose tissue fibrosis: role of collagen VI. Mol. Cell Biol. 2009;29:1575-91. [34] Lumeng CN, Bodzin JL, Saltiel AR. Obesity induces a phenotypic switch in adipose tissue macrophage polarization. J. Clin. Invest. 2007;117:175-84. [35] Apovian CM, Bigornia S, Mott M, Meyers MR, Ulloor J, Gagua M, McDonnell M, Hess D, Joseph L, Gokce N. Adipose macrophage infiltration is associated with insulin resistance and vascular endothelial dysfunction in obese subjects. Arterioscler Thromb Vasc. Biol. 2008;28:1654-9. [36] Cinti S, Mitchell G, Barbatelli G, Murano I, Ceresi E, Faloia E, Wang S, Fortier M, Greenberg AS, Obin MS. Adipocyte death defines macrophage localization and function in adipose tissue of obese mice and humans. J. Lipid Res. 2005;46:2347-55. [37] Murano I, Barbatelli G, Parisani V, Latini C, Muzzonigro G, Castellucci M, Cinti S. Dead adipocytes, detected as crown-like structures, are prevalent in visceral fat depots of genetically obese mice. J. Lipid Res. 2008;49:1562-8. [38] Pajvani UB, Trujillo ME, Combs TP, Iyengar P, Jelicks L, Roth KA, Kitsis RN, Scherer PE. Fat apoptosis through targeted activation of caspase 8: a new mouse model of inducible and reversible lipoatrophy. Nature Med. 2005;797-803. [39] Gordon S. Alternative activation of macrophages. Nature Rev. Immunol. 2003;3:23-35. [40] Odegaard JI, Ricardo-Gonzalez RR, Red Eagle A, Vats D, Morel CR, Goforth MH, Subramanian V, Mukundan L, Ferrante AW, Chawla A. Alternative M2 activation of Kupffer cells by PPAR ameliorates obesity-induced insulin resistance. Cell Metab. 2008;7:496-507. [41] Odegaard JI, Chawla A. Alternative macrophage activation and metabolism. Annu. Rev. Pathol. 2011; 6:275-97. [42] Feuerer M, Herrero L, Cipolletta D, Naaz A, Wong J, Nayer A, Lee J, Goldfine AB, Benoist C, Shoelson S, Mathis D. Fat Treg cells: a liaison between the immune and metabolic systems. Nature Med. 2009;15:930-9. [43] Nishimura S, Manabe I, Nagasaki M, Eto K, Yamashita H, Ohsugi M, Otsu M, Hara K, Ueki K, Sugiura S, Yoshimura K, Kadowaki T, Nagai R. CD8+ effector T cells contribute to macrophage recruitment and adipose tissue inflammation in obesity. Nature Med. 2009;15:91420.

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[44] Winer S, Chan Y, Paltser G, Truong D, Tsui H, Bahrami J, Dorfman R, Wang Y, Zielenski J, Mastronardi F, Maezawa Y, Drucker DJ, Engleman E, Winer D, Dosch HM. Normalization of obesity-associated insulin resistance through immunotherapy. Nature Med. 2009;15:921-9. [45] Hotamisligil GS, Budavari A, Murray D, Spiegellman BM. Reduced tyrosine kinase activity of the insulin receptor in obesity-diabetes. Central role of tumor necrosis factor- . J. Clin Envest. 1994;94:1543-9. [46] Uysal KT, Wiesbrock SM, Marino MW, Hotamisligil GS. Protection from obesity-induced insulin resistance in mice lacking TNF-alpha function. Nature. 1997;389:610-4. [47] Kern PA, Saghizadeh M, Ong JM, Bosch RJ, Deem R, Simsolo RB. The expression of tumor necrosis factor in human adipose tissue. Regulation by obesity, weight loss, and relationship to lipoprotein lipase. J. Clin Invest. 1995;95:2111-9. [48] Ziccardi P, Nappo F, Giugliano G, Esposito K, Marfella R, Cioffi M, D'Andrea F, Molinari AM, Giugliano D. Reduction of inflammatory cytokine concentrations and improvement of endothelial functions in obese women after weight loss over one year. Circulation. 2002;105:804-9. [49] Hivert MF, Sullivan LM, Fox CS, Nathan DM, D'Agostino RB Sr, Wilson PW, Meigs JB. Associations of adiponectin, resistin, and tumor necrosis factor-a with insulin resistance. J. Clin. Endocrinol Metab. 2008;93:3165-72. [50] Dominguez H, Storgaard H, Rask-Madsen C, Steffen Hermann T, Ihlemann N, Baunbjerg Nielsen D, Spohr C, Kober L, Vaag A, Torp-Pedersen C. Metabolic and vascular effects of tumor necrosis factor- blockade with etanercept in obese patients with type 2 diabetes. J. Vasc. Res. 2005;42:517-25. [51] Ofei F, Hurel S, Newkirk J, Sopwith M, Taylor R. Effects of an engineered human anti-TNFalpha antibody (CDP571) on insulin sensitivity and glycemic control in patients with NIDDM. Diabetes. 1996;45:881-5. [52] Stanley TL, Zanni MV, Johnsen S, Rasheed S, Makimura H, Lee H, Khor VK, Ahima RS, Grinspoon SK.. TNF-alpha antagonism with etanercept decreases glucose and increases the proportion of high molecular weight adiponectin in obese subjects with features of the metabolic syndrome. J. Clin. Endocrinol Metab. 2011;96:E146-E150. [53] Kim HJ, Bachmann RA, Chen J. Differential effects of interleukin-6 and -10 on skeletal muscle and liver insulin action in vivo. Diabetes. 2004;53:1060-7. [54] Matthews VB, Allen TL, Risis S, Chan MH, Henstridge DC, Watson N, Zaffino LA, Babb JR, Boon J, Meikle PJ, Jowett JB, Watt MJ, Jansson JO, Bruce CR, Febbraio MA. Interleukin-6deficient mice develop hepatic inflammation and systemic insulin resistance. Diabetologia. 2010;53:2431-41. [55] Wood IS, Wang B, Jenkins JR, Trayhurn P. The pro-inflammatory cytokine IL-18 is expressed in human adipose tissue and stongly upregulated by TNF-alpha in human adipocytes. Biochem. Res Commun. 2005;337:422-9. [56] Esposito K, Pontillo A, Ciotola M, Di Palo C, Grella E, Nicoletti G, Giugliano D. Weight loss reduces interleukin-18 levels in obese women. J. Clin. Endocrinol Metab. 2002;87:3864-6. [57] Elhage R, Jawien J, Rudling M, Ljunggren HG, Takeda K, Akira S, Bayard F, Hansson GK. Reduced atherosclerosis in interleukin-18 deficient apolipoprotein E-knockout mice. Cardiovasc. Res. 2003;59:234-40. [58] Oh DY, Talukdar S, Bae EJ, Imamura T, Moringa H, Fan W, Li P, Lu WJ, Watkins SM, Olefsky JM. GPR120 is an omega-3 fatty acid receptor mediating potent anti-inflammatory and insulin-sensitizing effects. Cell. 2010;142:687-98.


169

[59] Vandanmagsar B, Youm YH, Ravussin A, Galgani JE, Stadier K, Mynatt RL, Ravussin E, Stephens JM, Dexit VD. The NLRP3 inflammasome instigates obesity-induced inflammation and insulin resistance. Nat. Med. 2011;17:179-88. [60] Gregor MF, Hotamisligil GS. Inflammatory mechanisms in obesity. Annu. Rev. Immunol. 2011; 29:415-45. [61] Lumeng CN, Deyoung SM, Saltiel AR. Macrophages block insulin action in adipocytes by altering expression of signaling and glucose transport proteins. Am. J. Physiol. Endocrinol. Metab. 2007;292(1):E166-74. [62] Osborn O, Olefsky JM. The cellular and signaling networks linking the immune system and metabolism in disease. Nat. Med. 2012;18:363-74. [63] Resolving Inflammation: Mechanisms and Drug Discovery. Conference presented by Nat. Rev. Immunol. Keble College, Oxford, UK. April 1-3, 2012. [64] Esposito K, Pontillo A, Di Palo C, Giugliano G, Masella M, Marfella R, Giugliano D. Effect of weight loss and lifestyle changes on vascular inflammatory markers in obese women: a randomized trial. JAMA. 2003;289:1799-1804. [65] Vijay-Kumar M, Aitken JD, Carvalho FA, Cullender TC, Mwangi S, Srinivasan S, Sitaraman SV, Knight R, Ley RE, Gewirtz AT. Metabolic syndrome and altered gut microbiota in mice lacking toll-like receptor 5. Science. 2010;328:228-31. [66] Turnbaugh PF, Levy RE, Mahowald MA, Magrini V, Mardis ER, Gordon JI. An obesity associated gut microbiome with increased capacity for energy harvest. Nature. 2006;444:102731. [67] Eckburg PB, Bik EM, Bernstein CN, Purdom E, Dethlefsen L, Sargent M, Gill SR, Nelson KE, Relman DA. Diversity of the human intestinal microbial flora. Science. 2005;308:1635-8. [68] Ley RE, Bäckhed F, Turnbaugh P, Lozupone CA, Knight RD, Gordon JI. Obesity alters gut microbial ecology. Proc. Natl. Acad. Sci. USA. 2005;102:11070-5. [69] Ley RE, Turnbaugh PJ, Klein S, Gordon JI. Microbial ecology: human gut microbes associated with obesity. Nature. 2006;444:1022-3. [70] Delzenne NM, Neyrinck AM, Bäckhed F, Cani PD. Targeting gut microbiota in obesity: effects of prebiotics and probiotics. Nat. Rev. Endocrinol. 2011;7:639-46. [71] Turnbaugh PJ, Bäckhed F, Fulton L, Gordon JI. Diet-induced obesity is linked to marked but reversible alterations in the mouse distal gut microbiome. Cell Host Microbe. 2008;3:213-23. [72] Ravel J, Gajera P, Abdo Z, Schneider GM, Koenig SSK, McCulle SL, Karlebach S, Gorle R, Russell J, Tacket CO, Brotmana RM, Davis CC, Ault K, Peralta L, Forney LJ. Vaginal microbiome of reproductive-age women. Proc Natl Acad Sci USA. 2011;108(Suppl 1):4680-7. [73] Kalliomaki M, Collado MC, Salminen S, Isolauri E. Early differences in fecal microbiota composition in children may predict overweight. Am. J. Clin. Nutr. 2008;87:534-8. [74] Collado MC, Isolauri E, Laitinen K Salminen S. Effect of mother’s weight on infant’s microbiota acquisition, composition and activity during early infancy: a prospective follow-up study initiated in early pregnancy. Am. J. Clin. Nutr. 2010;92:1023-30. [75] Mitsou EK, Kirtzalidou E, Oikonomou I, Liosis G, Kyriacou A. Fecal microflora of Greek healthy neonates. Anarobe. 2008;14(2):94-101. [76] Agans R, Rigsbee L, Kenche H, Michail S, Khamis HJ, Paliy O. Distal gut microbiota of adolescent children is different from that of adults. FEMS Microbial Ecol. 2001;77(2):404-12. [77] Mariat D, Firmesse O, Levenez F, Guimarăes VD, Sokol H, Doré J, Corthier G, Furet J-P. The Firmicutes/Bacteroidetes ratio of the human microbiota changes with age. BMC Microbiol. 2009;9:123 doi:10.1186/1471-2180-9-123. [78] Nicholson JK, Holmes E, Kinross J, Burcelin R, Gibson G, Jia W, Pettersson S. Host-gut microbiota metabolic interactions. Science. 2012;336:1262-7.

170

Aristo Vojdani

[79] Bone E, Tamm A, Hill M. The production of urinary phenols by gut bacteria and their possible role in the causation of large bowel cancer. J. Clin. Nutr. 1976;29:1448-54. [80] Ott SJ, Musfeldt M, Wenderoth DF, Hampe J, Brant O, Fölsch UR, Timmis KN, Schreiber S. Reduction in diversity of the colonic mucosa associated bacterial microflora in patients with active inflammatory bowel disease. Gut. 2004;53:685–93. [81] Holmes E, Li JV, Athanasiou T, Ashrafian H, Nicholson JK. Understanding the role of gut microbiome-host metabolic signal disruption in health and diease. Trands Microbiol. 2011;19(7):348-59. [82] Zhang H, DiBaise JK, Zuccolo A, Kudrna D, Braidotti M, Yuc Y, Parameswarana P, Crowell MD, Wing R, Rittmanna BE, Krajmalnik-Brown R. Human gut microbiota in obesity and after gastric bypass. Proc. Natl. Acad. Sci. 2009;106(7):2365-70. [83] Furet J-P, Kong L-C, Tap J, Poitou C, Basdevant A, Bouillot J-L, Mariat D, Corthier G, Doré J, Henegar C, Rizkalla S, Clément K. Differential adaptation of human gut microbiota to bariatric surgery–induced weight loss links with metabolic and low-grade inflammation markers. Diabetes. 2012;59:3049–57. [84] Cani PD, Amar J, Iglesias MA, Poggi M, Knauf C, Bastelica D, Neyrinck AM, Fava F, Tuohy KM, Chabo C, Waget A, Delmée E, Cousin B, Sulpice T, Chamontin B, Ferrières J, Tanti JF, Gibson GR, Casteilla L, Delzenne NM, Alessi MC, Burcelin R. Metabolic endotoxemia initiates obesity and insulin resistance. Diabetes. 2007;56:1761-72. [85] Maes M, Kubera M, Leunis J-C. The gut-brain barrier in major depression: Intestinal mucosal dysfunction with an increased translocation of LPS from gram negative enterobacteria (leaky gut) plays a role in the inflammatory pathophysiology of depression. Neuroendocrinol Lett. 2008;29(1):117–24. [86] Maes M, Coucke F, Ategis J-C. Normalization of the increased translocation of endotoxin from gram negative enterobacteria (leaky gut) is accompanied by a remission of chronic fatigue syndrome. Neuroendocrinol Lett. 2007;28(6):101-6. [87] Arican N, Kaya M, Kalayci R, Uzun H, Ahishali B, Bilgic B, Elmas I, Kucuk M, Gurses C, Uzun M. Effects of lipopolysaccharide on blood–brain barrier permeability during pentylenetetrazole-induced epileptic seizures in rats. Life Sci. 2006;79:1-7. [88] Szeto C-C, Ching-Ha Kwan B, Chow K-M, Lai K-B, Chung K-Y, Leung C-B, Kam-Tao Li P. Endotoxemia is related to systemic inflammation and atherosclerosis in peritoneal dialysis patients. Clin. J. Am. Soc. Nephrol. 2008;3:431-6. [89] Creely SJ, McTernan PG, Kusminski CM, Fisher ffM, Da Silva NF, Khanolkar M, Evans M, Harte AL, Kumar S. Lipopolysaccharide activates an innate immune system response in human adipose tissue in obesity and type 2 diabetes. Am. J. Physiol Endocrinol Metab. 2007;292:E7407. [90] Koren O, Spor A, Felin J, Fåk F, Stombaugh J, Tremaroli V, Behre CJ, Knight R, Fagerberg B, Leya RE, Bäckhed F. Human oral, gut, and plaque microbiota in patients with atherosclerosis. Proc. Natl. Acad. Sci. 2011;108(Suppl 1):4592-8. [91] Maslowski KM, Mackay CR. Diet, gut microbiota and immune responses. Nat. Immunol. 2011;12:5-9. [92] Slavin J, Jacobs D, Maquart L. Whole grain consumption and chronic disease: protective mechanisms. Nutr. Cancer. 1997;27(1):14-21. [93] Müller H, de Toledo FW, Resch KL. Fasting followed by vegetarian diet in patients with rheumatoid arthritis: a systematic review. Scand. J. Rhematol. 2001;30(1):1-10. [94] Galvez J, Rodríguez-Cabezas ME, Zarzuelo A. Effects of dietary fiber on inflammatory bowel disease. Mol. Nutr. Food Res. 2005;49(6):601-8.


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[95] Simopoulos AP. Omega-3 fatty acids in inflammation and autoimmune diseases. J. Am. Col Nutr. 2002;21(6):495–505. [96] Zhang X, Zhao Y, Zhang M, Pang X, Xu J, Kang C, Li M, Zhang C, Zhang Z, Zhang Y, Li X, Ning G, Zhao L. Structural Changes of Gut Microbiota during Berberine-Mediated Prevention of Obesity and Insulin Resistance in High-Fat Diet-Fed Rats. PLoS One. 2012;7(8):e42529. [97] Cani PD, Lecourt E, Dewulf EM, Sohet FM, Pachikian BD, Naslain D, De Backer F, Neyrinck AM, Delzenne NM. Gut microbiota fermentation of prebiotics increases satietogenic and incretin gut peptide production with consequences for appetite sensation and glucose response after a meal. Am. J. Clin. Nutr. 2009;90(5):1236-43. [98] Cani PD, Joly E, Horsmans Y, Delzenne NM. Oligofructose promotes satiety in healthy human: a pilot study. Eur. J. Clin. Nutr. 2006;60(5):567-72. [99] Clarke TB, Davis KM, Lysenko ES, Zhou AY, Yu Y, Weiser JN. Recognition of peptidoglycan from the microbiota by Nod1 enhances systemic innate immunity. Nat. Med. 2010;16:228-31. [100] Sin DD, Sutherland ER. Obesity and the lung: 4. Obesityand asthma. Thorax. 2008;63:1018-23. [101] Patterson CC, Dahiquist GG, Gyurus E, Green A, Soltesz G. Incidence trends for childhood type 1 diabetes in Europe during 1989-2003 and predicted new cases 2005-20: a multicentre prospective registration study. Lancet. 2009;373:2027-33. [102] Frank DN, St Amand AL, Feldman RA, Boedeker EC, Harpaz N, Pace NR. Molecularphylogenetic characterization of microbial community imbalances in human inflammatory bowel diseases. Proc. Natl. Acad. Sci. USA. 2007;104:13780-5. [103] Cani PD, Bibiloni R, Knauf C, Waget A, Neyrinck AM, Delzenne NM, Burcelin R. Changes in gut microbiota control metabolic endotoxemia-induced inflammation in high-fat diet-induced obesity and diabetes in mice. Diabetes. 2008;57:1470-81. [104] Hooper VL, Littman DR, Macpherson AJ. Interactions between the microbiota and the immune system. Science. 2012;336:1268-73.

Received: November 9, 2012 Revised: January 12, 2013 Accepted: January 15 2013.



BRAIN-REACTIVE ANTIBODIES IN TRAUMATIC BRAIN INJURY Aristo Vojdani Immunosciences Lab., Inc., Los Angeles, CA USA

ABSTRACT Neuroautoimmune diseases are disorders that involve the body’s immune system attacking its own brain or neural tissues. Normally the brain is protected from the outside world by the bloodbrain barrier (BBB), which is composed of highly specialized brain endothelial cells. However, repetitive traumatic brain injury (TBI), such as occurs in football and other sports, can lead to repeated disruptions to the BBB. This opening of the door to the brain can lead to a dysfunctional exchange of molecules between the blood and the brain. A dysfunctional immune system can mistakenly identify neural antigens as invasive agents and produce autoreactive antibodies against BBB proteins such as S100-B and various neural tissue antigens. S100-B has been used in conjunction with CT scanning to successfully confirm concussions or brain injuries. The detection of S100-B antibodies actually goes further to indicate that the BBB has been damaged and autoimmunity has been activated against the brain cells, and can even be used to indicate degree of recovery and when to return to normal activity. These findings support the importance of measuring antibodies against S100-B and other neural autoantigens in the diagnosis and therapy of patients with TBI.

Keywords: Autoimmune, traumatic brain injury, autoantigens, S100-B antibodies

INTRODUCTION Autoimmune diseases affect about 7% of the world’s population. In these disorders, pathogenic TH1 cells, autoreactive TH17 cells, antibodies and associated molecules attack antigens of various tissues, including brain tissue. Brain-reactive antibodies are detected in about 3% of the general population but do not contribute to brain pathology unless they cross the blood-brain barrier (BBB) [1]. The BBB is composed of highly specialized brain endothelial cells which are fully differentiated to the neurovascular system. It is estimated that the human brain contains more than ten billion capillaries, which translates into one vessel for each neuron. The total length of the capillaries in the human brain is about 400 miles. In conjunction with microglia, astrocytic foot processes and pericytes, the BBB separates the neurons from various components of the circulating blood [2]. The endothelial tight junctions, together with astrocytic foot processes, prevent the passage of all soluble 

Correspondence: Dr. Aristo Vojdani, Immunosciences Lab., Inc. Los Angeles, CA USA, 822 S. Robertson Blvd., Ste. 312, Los Angeles, CA 90035 E-mail: [email protected]

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molecules greater than 400 Da into the nervous system; consequently, during immune maturation B cells are not exposed to a variety of unique brain antigens expressed on neurons, oligodendrocytes, microglia and astrocytes. As a result, the immune system has no mechanism for regulatory T-cell development to establish tolerance for brain antigens [3]. However, various conditions such as stress, infection (in particular, bacterial endotoxins), toxic chemicals, drugs, some medication, and, more importantly, traumatic brain injury (TBI), directly or indirectly, through the activation of inflammatory signals, can disrupt the integrity of the BBB [4-12]. The breakdown of the BBB due to the disruption of tight junctions by various triggers results in the altered transport of molecules as well as pathogenic TH1 and TH17 cells between the blood and the brain, and to some degree from brain to blood. This molecular and cellular exchange between blood and brain can result in aberrant angiogenesis, vessel regression, brain hyperfusion, neuroinflammatory responses, neural cell damage, and the release of neural antigens into the blood [2]. Due to defects in immune tolerance or response against various neural antigens, these antigens will be transmitted by antigen-presenting cells, first to T cells and then to B cells, resulting in brain-specific antibodies, and autoreactive TH1 and TH17 cells. The entry of these pathogenic cells and antibodies into the brain tissue may result in progressive synaptic and neuronal dysfunction and loss in neuroautimmune and neurodegenerative disorders such as multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS), Alzheimer’s and Parkinson’s disease [1,13]. In some cases, it might be expected that brain antibodies that arise in diseases with clear antigenic triggers such as bacterial endotoxins or lipopolysaccharides (LPS), dietary antigens (gluten, milk proteins, excessive salt), and environmental toxins (heavy metals, polychlorinated biphenyls), disappear once the inciting triggers are no longer present [4-12,14,15]. Thus, eradication of the exogenous triggers may result in BBB repair, followed by termination of autoantibody production. However, in the case of brain concussion or repeated TBI, this may not be the case.

TRAUMATIC BRAIN INJURY, BLOOD-BRAIN BARRIER DISRUPTION, AND BRAIN ANTIBODIES TBI is a multifaceted pathology involving excitotoxicity, free radical formation, brain swelling, and the entry of locally produced molecules such as cytokines, chemokines, and other molecules that can disrupt the metabolism and contribute to neuroinflammation [16-18]. Understanding the diverse mechanisms involved in TBI is becoming increasingly important; it is estimated that 4 million people experience sports and recreation-related concussion annually in the United States [12,19,20]. Following TBI, in addition to a leaky BBB, a cascade of biochemical, immunological and excitotoxic events which are mediated by the innate and adaptive immune systems occurs in the central nervous system (CNS). These excitotoxic events begin with acute microglial activation followed by the release of massive amounts of glutamate and aspartate which over-stimulate the glutamate receptors. This results in the opening of calcium channels, the influx of calcium, neuronal toxicity and cell death [13,21]. Depending on the degree of injury, this excitotoxic reaction may improve within hours or days. But with repeated injuries and multiple concussions, the excitotoxic reaction could be followed by immunoexcitotoxicity and neuro-destructive process (Figure 1). Microglial cells or resident macrophages constitute about 15% of the total glial cell population within the brain. These cells are the major components of active immune defense in the CNS. Normally microglia are in a resting state, but upon exposure to environmental triggers, trauma or injury, disruption of the BBB, or disruption of brain homeostasis, the microglia can be activated and switch to a state of active immune defense.

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Figure 1. Proposed mechanism for excitotoxicity from leaky BBB. Repeated head trauma and multiple disruptions of the BBB leads to the release of free radicals and immunoinflammatory factors, causing acute microglia activation, which contributes to immunoexcitotoxicity.

To facilitate the healing process after an injury, the host body tries to remove the inciting agents and clear dead or dying cells by releasing immune factors, in particular chemokines and cytokines, reactive oxygen and nitrogen species, inflammatory prostaglandins, proteases, nitric oxide and trophic factors [21]. During this healing process, microglia secrete a number of neurotrophic factors and immunoregulatory or anti-inflammatory cytokines, such as nerve growth factors, brain-derived neurotrophic factors which contribute to the reduction of neurotoxic processes in the brain and the repair of the disrupted BBB. One of the major concerns after a first injury is the prevention of recurrent injuries before the brain is completely healed. This is because repetitive brain injury that occurs before the complete healing and repair of the neuroinflammatory response can accelerate and exacerbate chronic activation of the microglia, with serious consequences. Indeed, it has been shown that the primed microglia get fully activated and release significantly higher levels of pro-inflammatory cytokines/chemokines and excitotoxins than the initial injury. In most cases the activated microglia will switch to a reparative mode, but in some cases this normal protective microglial response to the injury does not have the time to “turn off’ the switching mechanism. When the switching mechanism becomes locked in the “on” position, it can lead to prolonged and severe brain immunoexcitotoxicity, neurodegeneration, and possibly neuroautoimmunities [12, 22]. The process of neuroautoimmunity depends largely on the integrity of the BBB. A disrupted BBB leads to exposure to many environmental triggers. Due to the antigenic similarity of these triggers with neuronal cell antigens, brain-reactive antibodies are detected in healthy subjects who do not exhibit neurological symptomatologies. These autoantibodies contribute to a host of neuroimmunological disorders. For example, neuron-binding autoantibodies have been detected in the

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sera of patients with obsessive-compulsive disorders, Sydenham’s chorea, pediatric autoimmune neuropsychiatric disorders associated with streptococcal infection, autism, multiple sclerosis, Guillain-Barré syndrome, Hashimoto’s encephalopathy, lupus, schizophrenia, chronic peripheral neuropathy, optic neuritis, vascular dementia, stiff person syndrome, celiac disease and Alzheimer’s disease [1].

Figure 2. Autoreactive antibodies and intact BBB. In an intact BBB, autoantibodies are restricted to the lumen of the blood vessels, so that the antibodies are prevented from causing damage to brain tissue, regardless of how high the antibody level is.

Figure 3. Autoreactive antibodies and disrupted BBB. With a disrupted BBB, autoantibodies gain access to the brain tissues. With only a few autoreactive antibodies, damage is minimal and the neurons and brain may recover. However, a high level of autoreactive antibodies can lead to extensive neuronal damage, neuronal cell death, and possibly neuroautoimmune disorders.


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It seems that in these conditions a defective BBB allows these autoantibodies access to various targets on the surfaces of brain cells. These antibodies may therefore contribute to the initiation and/or progression of many neuroinflammatory and neurodegenerative diseases that involve BBB compromise. A proposed model for the role of brain-reactive autoantibodies and BBB integrity disruption in the pathogenesis of neurological disease is shown in Figures 2 and 3.

CONSEQUENCES OF REPEATED BBB DISRUPTION IN TRAUMATIC BRAIN INJURY The annual incidence of traumatic brain injuries is about one in 250 persons or 5% of total ER patients [23]. In the National Football League, the number of sub-concussive head hits has been estimated to be in the range of hundreds per season. Clinically, concussions can produce symptoms that are of short or long duration lasting from several minutes to several months. Severe postconcussive symptoms have been reported to last several years in some athletes and have caused numerous athletes to retire from their sport. Although football-related concussions are becoming increasingly recognized, the mechanisms involved remain poorly understood. BBB disruption (BBBD) or increased permeability of the brain vasculature has been linked to a variety of neurological disorders including seizures, Alzheimer’s disease, stroke and TBI [11]. Circulating autoantibodies against CNS antigens become pathogenic to the brain when the BBB allows their access to the brain [24]. The consequences of BBBD could be deleterious when accompanied by autoimmune reactivity as in neuroautoimmune disorders. In these cases the loss of BBB integrity initiates humoral and cellular immune response in the CNS and unmasking of the CNS antigens, including BBB proteins and astrocytic antigens called S100-B, which triggers peripheral immune responses against these antigens. S100-B is a 21 kDa calcium-binding glial-specific protein mainly expressed by astrocytes on their endfeet. These endfeet, together with the tight junction proteins zonula occludens and ZO-1, form the BBB. The prevailing method of choice for detecting intracranial injury in patients with minor injury is computed tomography (CT) scan. Although the CT scan has high sensitivity in detecting intracranial injury in patients with brain injury, it is expensive, exposes patients to high doses of radiation, and reveals clinically relevant lesions in less than 10% of cases [23]. For this reason, the measurement of S100-B in blood was introduced as an indicator of minor as well as severe head injury [25,26]. This S100-B protein level in the blood was used as a screening tool for the early assessment of minor head injuries in more than 2,000 patients in Bordeaux, France, comparing CT scans with plasma S100-B levels [23]. With a cutoff of 0.12 microgram/L of S100-B, TBIs on CT scan were identified with a sensitivity of 99% and specificity of 20% [23]. It was concluded that plasma S100-B in patients with minor head injury is a promising screening tool that may be of help in the clinician’s decision not to perform CT imaging [23]. It is important to mention that the half-life of S100-B 21 kDa protein is about 4 hours, and therefore, in many players where S100-B was detected, antigen levels returned to pre-game values within 24 hours after the game [23]. This speedy elimination of 21 kDa from the blood may be related to immune response and the production of specific antibodies against S100-B. As opposed to the antigens, S100-B antibodies are much more stable in blood, with IgG having a half-life of 21 days. Therefore, the measurement of antibodies against S100-B is more useful than just measuring the levels of S100-B itself in TBI.

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CLINICAL SIGNIFICANCE OF AUTOANTIBODIES AGAINST S100-B AND OTHER NEURONAL ANTIGENS It is possible that repeated “opening” of the BBB can result in a delayed pathological response consisting of immune cell activation against a brain antigen. Activated immune cells mistakenly “recognize” self antigens as foreign invaders and mount an immune response against them. A very recent study examined both the levels of S100-B and specific antibodies against S100-B in football players with TBI [11], but other brain antigens, such as myelin basic protein (MBP), tau, and betatrace protein could also be attacked by the activated immune cells, resulting in neuroautoimmunity. Although antibodies are produced as a result of BBBD, the presence of neural autoantibodies in blood alone does not necessarily translate into an autoimmune or neurological disease. In fact, autoantibodies can be detected in individuals who do not present autoimmune symptoms [27]. However, autoantibodies may become pathogenic upon penetration into the CNS through either a BBBD or extravasation into cerebrospinal fluid from the sub-arachnoid space [24]. As has been stated earlier, the presence or detection of autoantibodies is associated with many neurological and/or autoimmune diseases. Elevated antibody titers for S100-B and other brain proteins have been described in a variety of human diseases including Alzheimer’s disease [28-30]. Immunoglobulins in the brain have also been detected in epilepsy [31]. Recent reports have shown that in patients with senile dementia, one of the early markers of cognitive decline is the presence of antibodies directed against S100-B [28,29]. The presence of an autoimmune response that persists for an extended period following repetitive BBBDs in adulthood may cause neuronal cell death and an early cognitive decline [32]. To borrow the parlance of sports, it has been proposed that a number of molecular “players” “switch teams” in the event of a BBBD [33]. These molecular players in serum (albumin, magnesium ions, potassium ions, immunoglobulins) may enter the brain after a BBBD and disrupt the homeostasis of the CNS. On the other hand, brain proteins may activate an autoimmune response by antigen unmasking. This decline in cognitive function and the risk of developing neurodegenerative diseases have been found in football players with head injuries [30]. If repeated head trauma is causing BBBDs and leading to the presence of autoantibodies in the CNS, it should be no surprise that autoantibodies to S100-B can be found in football players after playing even a single season, during which a typical player may experience 1,000 head hits or more [34]. In the latest study involving 67 football players, the number of head hits and brain injuries were assessed by conducting CT scans and tests that measured balance, motor control and memory [11]. They collected blood from 57 players before and after football games and measured the level of S100-B protein in their blood. Serum S100-B was detected in players who experienced the greatest number of sub-concussive hits. Since S100-B is a large molecule (21 kDa), even trace amounts handled by cells involved in the immune system resulted in specific antibodies against S100-B. The fact that this protein found its way into the blood means that the blood-brain barrier or the biological door to the brain had been damaged, and the antibodies produced against S100-B had made their way into the brain, producing autoimmune response against the brain tissue. Indeed, this autoimmune response was even found in a subgroup of players that did not suffer from brain concussion [11]. Considering the fact that it is sometimes difficult to diagnose concussion, which occurs in about 40% of football players, the detection of antibodies against S100-B indicates that not only is there an abnormal opening or a door to the brain, but that autoimmunity has been activated against the brain cells. Furthermore, elevated levels of autoantibodies against S100-B and other brain tissue antigens such as myelin basic protein, myelin oligodendrocyte glycoprotein, tubulin, cerebellar and synapsin indicate repeated sub-concussive events characterized by BBBD. The presence or absence of these antibodies against S100-B and other brain tissue antigens can determine whether or not TBI or


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concussion has occurred, and it can also indicate when it will be safe to return to normal activities. This process of neuroautoimmunity and neurodegeneration in repeated concussions or subconcussions is shown in Figure 4.

Figure 4. Repetitive sports brain injuries and neurologic disorders. Repeated trauma caused to the brain in a short period of time, such as often occurs in many sports, can overwhelm the brain’s healing capacity, potentially leading to neuroautoimmunity and neurodegeneration.

Serum levels of S100-B autoantibodies also predicted the persistence of white matter abnormalities detected by MRI, which in turn correlated with cognitive changes. The correlation of serum S100-B autoantibodies with white matter abnormalities support a link between repeated BBB disruption and future risk for cognitive changes. Even in the absence of concussion, the athletes may experience repeated BBB disruption and the surge of potential autoantigens in the blood. Additional autoantigens that were detected in the blood were microtubule-associated protein isoforms 5 and 7, neuromodulin 2, synapsin 1, beta-tubulin 3 and MBP. Finally, it should be noted that much attention is being paid to the big hits and concussions suffered by athletes, but there should be concern as well for sub-concussive hits that also appear to cause damage. These findings support the proposition that measurement of antibodies against S100-B and these other neural autoantigens is important for the diagnosis and therapy management of patients with TBI. The detection of these brain-reactive antibodies is part of the Neurological Autoimmune Reactivity Screen that is being offered by Cyrex Labs in Phoenix, AZ as its Array 7.

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REFERENCES [1] [2] [3] [4] [5]

[6] [7] [8] [9] [10] [11]

[12]

[13]

[14] [15]

[16] [17]

[18]

Diamond B, Honig G, Mader S, Brimberg L, Volpe BT. Brain-reactive antibodies and diseases. Annu. Rev Immunol. 2013;31:345-385. Zlokovic BV. The blood-brain barrier in health and chronic neurodegenerative disorders. Neuron. 2008;57:178-201. Diamond B, Huerta PT, Mina-Osorio P, Kowal C, Volpe BT. Losing your nerves? Maybe it’s the antibodies. Nat. Rev. Immunol 2009;9:449-456. Hanin I. The Gulf war, stress, and a leaky blood-brain barrier. Nat. Med. 1996;2(12):1307-1308. Friedman A, Kaufer D, Shemer J, Hendler I, Soreq H, Tur-Kaspa I. Pyridostigmine brain penetration under stress enhances neuronal excitability and induces early immediate transcriptional response. Nat. Med. 1996;2:1382-1385. Xaio H, Banks WA, Niehoff ML, Morley JE. Effect of LPS on the permeability of the bloodbrain barrier to insulin. Brain Res. 2001;896:36-42. Hazleton JE, Berman JW, Eugenin EA. Novel mechanism of central nervous system damage in HIV infection. HIV/AIDS Res Palliat Care. 2010;2:39-49. Zheng W, Aschner M, Ghersi-Egea JF. Brain barrier systems: a new frontier in metal neurotoxicological research. Tox. App. Pharmacol. 2003;192:1-11. Seelbach M. Polychlorinated bishpenyls disrupt blood-brain barrier integrity and promote brain metastases formation. Env. Health Persp. 2010;118:479-484. Dietrich JB. Alteration of blood-brain barrier function by methamphetamine and cocaine. Cell Tissue Res. 2009;336:385-392. Marchi N, Bazarian JJ, Puvenna V, Janigro M, Ghosh C, Zhong J, Zhu t, Blackam E, Stewart D, Ellis J, Butler R, Janigro D. Consequences of repeated blood-brain barrier disruption in football players. PLoS One. 2013;8(3):e56805. Maroon JC, Lepere DB, Blaylock RL, Bost JW. Postconcussion syndrome: a review of pathophysiology and potential nonpharmacological approaches to treatment. Phys. Sportsmed. 2012;40:73-87. Calderon-Garciduenas L, Franco0Lira M, Mora-Tiscareño A, Medina-Cortina H, Torres-Jardon R, Kavanaugh M. Early Alzheimer’s and Parkinson’s disease pathology in urban children: friends vs foes responses – it is time to face the evidence. BioMed Res Int. 2013;Article ID 161687. Vojdani A, O’Bryan T, Kellermann GH. The immunology of gluten sensitivity beyond the intestinal tract. Eur. J. Inflamm. 2008;6(2):49-57. Vojdani A, Campbell A, Anyanwu E, Kashanian A, Bock K, Vojdani E. Antibodies to neuronspecific antigens in children with autism: possible cross-reaction with encephalitogenic proteins from milk, Chlamydia pneumoniae and Streptococcus Group A. J. Neuroimmunol. 2002;129:168177. Pellman EJ, Lovell MR, Viano DC, Casson IR, Tucker AM. Concussion in professional football: neuropsychological testing – part 6. Neurosurgery. 2004;55:290–1303. Pellman EJ, Viano DC, Casson IR, Tucker AM, Waeckerle JF, Powell JW, Feuer H. Concussion in professional football: neuropsychological testing – part 4. Neurosurgery. 200455:290–1303. Neuwelt EA, Bauer B, Fahlke C, Fricker G, Iadecola C, Janigro D, Leybaert L, Molnár Z, O'Donnell ME, Povlishock JT, Saunders NR, Sharp F, Stanimirovic D, Watts RJ, Drewes LR. Engaging neuroscience to advance translational research in brain barrier biology. Nat. Rev. Neurosci. 2011;12:169–182.


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[19] Maroon JC, Field M, Lovell M, Colins M, Bost J. The evaluation of athletes with cerebral concussion. Clin. Neurosurg. 2002;49:319-332. [20] Hoge CW, Goldberg HM, Castro CA. Care of war veterans with mild traumatic brain injury. N. Engl. J. Med. 2009;360(16):1588-1591. [21] Arundine M, Tymianski M. Molecular mechanisms of glutamate-dependent neurodegeneration in ischemia and traumatic brain injury. Cell Mol Life Sci. 2004;61:657-668. [22] Blaylock RL, Maroon JC. Immunoexcitotoxicity as a central mechanism in chronic traumatic encephalopathy – a unifying hypothesis. Surg. Neurol. Int. 2011:2:107. doi: 10.4103/21527806.83391. [23] Zongo D, Ribéreau-Gayon R, Masson F, Laborey M, Contrand B, Salmi LR, Montaudon D, Beaudeux JL, Meurin A, Dousset V, Loiseau H, Lagarde E. S100-B as a screening tool for the early assessment of minor head injury. Ann. Emerg Med. 2012;59:209-218. [24] Vincent A, Bien CG, Irani SR, Waters P. Autoantibodies associated with diseases of the CNS: new developments and future challenges. Lancet Neurol. 2011;10:759–772. [25] Raabe A, Grohms C, Sorge O, Zimmerman M, Seifert V. S-100B protein in severe head in jury. Neurosurgery. 1999;45(3):477-483. [26] Poletaev AB, Morozov SG, Gnedenko BB, Zlunikin VM, Korzhenevskey DA. Serum antiS100b, anti-GFAP and anti-NGF autoantibodies of IgG class in healthy persons and patients with mental and neurological disorders. Autoimmun. 2000;32:33–38. [27] Biberthaler P, Linsenmeier U, Pfeiffer KJ, Kroetz M, Mussack T, Kanz KG, Hoecherl EF, Jonas F, Marzi I, Leucht P, Jochum M, Mutschler W. Serum S-100B concentration provides additional information for the indication of computed tomography in patients after minor head injury: a prospective multicenter study. Lancet. 1995;346: 221-223. [28] Maetzler W, Berg D, Synofzik M, Brockmann K, Godau J, Melms A, Gasser T, Hörnig S, Langkamp M. Autoantibodies against amyloid and glial-derived antigens are increased in serum and cerebrospinal fluid of Lewy body-associated dementias. J. Alzheimers Dis. 2011;26:171– 179. [29] Gruden MA, Davidova TB, Malisauskas M, Sewell RD, Voskresenskaya NI, Wilhelm K, Elistratova EI, Sherstnev VV, Morozova-Roche LA. Differential neuroimmune markers to the onset of Alzheimer’s disease neurodegeneration and dementia: autoantibodies to Abeta((25– 35)) oligomers, S100b and neurotransmitters. J. Neuroimmunol. 2007;186:181-192. [30] Storace D, Cammarata S, Borghi R, Sanguineti R, Giliberto L, Piccini A, Pollero V, Novello C, Caltagirone C, Smith MA, Bossù P, Perry G, Odetti P, Tabaton M. Elevation of {beta}-amyloid 1-42 autoantibodies in the blood of amnestic patients with mild cognitive impairment. Arch. Neurol. 2010;67:867–872. [31] Lehman EJ, Hein MJ, Baron SL, Gersic CM. Neurodegenerative causes of death among retired National Football League players. Neurol. 2010;79:1970-1974. [32] Vincent A, Lang B, Kleopa KA. Autoimmune channelopathies and related neurological disorders. Neuron. 2006;52:123-138. [33] Janigro D. Are you in or out? Leukocyte, ion, and neurotransmitter permeability across the epileptic blood-brain barrier. Epilepsia. 2012;53(Suppl 1):26-34, 2012. [34] Ocwieja KE, Mihalik JP, Marshall SW, Schmidt JD, Trulock SC, Guskiewicz KM. The effect of play type and collision closing distance on head impact biomechanics. Ann. Biomed. Eng. 2012;40:90-96.

Received: June 12 2013 Revised: June 18 2013 Accepted: June 28 2013.



THE ROLE OF ENVIRONMENTAL TRIGGERS IN NEUROAUTOIMMUNITY Aristo Vojdani1 and Jama Lambert2 1

Immunosciences Lab, Inc., Los Angeles, CA USA 2 Cyrex Laboratories, LLC., Phoenix, AZ USA

ABSTRACT Lipophilic chemicals have been identified as playing a role in neurological dysfunctions. Researchers are working to define the mechanisms by which environmental chemicals disrupt normal body immune and neuronal functions. Chemical exposures can occur in both the occupational and home environments, and can be acute (high-level) or chronic (low-level). Any of these scenarios can result in neuroautoimmunity. In this article we review seven incidents of environmental chemical exposure and discuss their effects on the human immune and nervous systems.

Keywords: Lipophillic, immunity, neuroimmune, environmental toxin

INTRODUCTION Researchers, public health officials and the medical community are continuously defining environmental risk factors that can lead to neuroautoimmunity. The list grows each year. Currently, we know that infectious agents, chemicals, hormones and genetics each play a role in the pathogenesis of some neuroautoimmunities. Our focus is on specific environmental chemicals and their effect on the human immune and nervous systems. Contemporary industrialized environments are becoming overly toxic to many of Earth’s habitants. Paradoxically, the human immune system has not had time enough to evolve into a mechanism of absolute protection against this multitude of human-made and organic chemicals seeping into all parts of the world. Under normal working conditions, the human immune system is able to identify friend from foe, or self from invader, and respond appropriately to the exposure. However, the taxing of our immune systems by a daily multitude of environmental toxins has, for many individuals, affected the immune system’s ability to recognize the good versus the bad. Toxic chemicals, both acute and chronic, low-level and high-level, can affect the human body. The interaction of the immune system with a single chemical or combination of toxins may result in three principal, undesirable effects:

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Correspondence: Dr. Aristo Vojdani, Immunosciences Lab., Inc., 822 S. Robertson Blvd., Ste. 312, Los Angeles, CA 90035, E-mail: [email protected].

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Aristo Vojdani and Jama Lambert 1. immediate or delayed hypersensitivity responses, 2. immune suppression, and/or 3. immune activation leading to neuroautoimmunity.

Rising rates of autoimmunity and possible outcomes of toxic exposure lead to the problem of finding reliable health risk assessments. Discovery of reliable biomarkers could assist affected individuals in the prevention of cancer or autoimmunity by identifying which carcinogens or chemicals to avoid. Exposures to chemicals may also elicit immune cascades that can lead to neuroinflammation and neuroautoimmune reactivity (see Figure 1).

Figure 1. Potential molecular mechanisms in chemical-induced autoimmune reactivity.

Some xenobiotics are labeled “neurotoxic” due to the pathogenic role they play in the neuroautoimmune process. Chemical infiltration of the body can occur by contact through the skin, inhalation via the lungs, and ingestion breaching the gastrointestinal tract. Once through the barrier, the chemical will elicit a systemic reaction leading to the production of antibodies. Circulating antibodies can ignite the autoimmune process. For a detailed mapping of xenobiotic-induced autoimmunity, see “Allergic and autoimmune reactions to xenobiotics: how do they arise?” by Peter Griem1 and colleagues. Below is an abbreviated version of how the body produces autoantibodies following xenobiotic exposure.

Environmental Triggers of Neuroautoimmunity

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During humoral immune responses of the adaptive immune system (see Figure 2), an invading antigen is recognized by an antigen presenting cell (APC). The APC picks up and transports the antigen to a T cell, which introduces the antigen to a B cell in the lymph node. Clonal expansion of the B cell follows and triggers antibody production. Immunoglobulin M (IgM) is produced as a primary response in the first days of defense. If previous exposures have occurred, a secondary immune response results in immunoglobulin G (IgG) production. High levels of these antibodies indicate an immune reaction to an antigen that threatens the homeostasis of the body and may result in autoimmune reactivity. The adaptive immune system consists of lymphocytes that recognize a wide range of foreign antigens from dietary peptides to xenobiotics without reacting to self- antigens. However, in cases of autoimmunity, some autoreactive lymphocytes, those that react to self-antigens, escape clonal deletion in the thymus (T lymphocytes) or bone marrow (B lymphocytes), lie dormant, and later become activated. Once activated, these autoreactive lymphocytes may initiate autoimmune diseases such as multiple sclerosis (MS), systemic lupus erythematosus (SLE), or Parkinson’s disease. In most cases, scientists can only speculate about the triggering mechanism by which autoreactive lymphocytes become activated; in some scenarios viruses, chemicals or physical/emotional trauma is thought to be the cause. In the case of mercury exposure, the chemical will bind to nucleoproteins such as fibrillarin and chromatin resulting in aberrant migration of the autoantigen [1-3]. Under stressful stimuli, autoantigens yield intracellular relocalization [2]. For example, the auto-antigen fibrillarin is a substrate of granzyme B, a protease, and undergoes alteration by mercury via oxidative fragmentation [2]. Thus modified during apoptosis, chromatin and fibrillarin may circulate, either in native form, or packaged in apoptotic bodies in the serum of patients with systemic autoimmune disorders [2, 4, 5]. Apoptosis is programmed cell death. It plays a significant role in the deletion of autoreactive lymphocytes, the removal of virally infected cells and the elimination of cancerous cells [6]

Figure 2. Putative mechanisms for mercury-induced autoimmunity. Modified from Schiraldi M, Monestier M. Trends in immunology. 2009;30:502-509.

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In most tissues, apoptosis, including clearance of cell corpses by neighboring parenchymal cells, transpires quickly, usually in less than one hour. However, in the absence of the first component of complement, the clearance of apoptotic corpses is delayed. Delayed clearance increases immunogenicity, which may result in antibody production. Based on this mechanism of induction of cell death by mercury, researchers have shown that the release of auto-antigens bound to mercury may be important in the genesis of autoimmune disorders, most notably, scleroderma [6]. Antibody test results of environmental chemicals can be useful tools in assessing a person’s health risk whether the exposure was short-lived but in high doses, or was presented in low doses over a long period of time. 

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Detection of antibodies against metals in blood indicates metal bound to human tissue, formation of neo-antigens and immunological intolerance of self after exposure to metals [2, 3, 6, 7]. Detection of anti-nucleolar autoantibodies and/or heavy metal binding proteins fibrillarin and chromatin, along with antibodies to metals, indicates autoimmune reaction induced by heavy metals [4, 5]. Detection of antibodies against metals, as well as different brain antigens (neurofilament, tubulin) and receptors, will measure the neurotoxic effect and neuroautoimmune reactivity of metals [1-3, 6, 8].

Specific antibody testing thus provides reliable health risk evaluations that can be used in conjunction with additional laboratory analysis and other pertinent clinical data to identify potential autoimmune or neuroimmune disorders. In an ever-growing chemically-laden world, it is vital for the medical community to provide the most useful, cost-effective analysis of health risk involved in such exposures. Although the presence of circulating autoantibodies does not always indicate immediate or future pathological consequences, they are often associated with disease processes [9]. The measurement of specific autoantibodies in serum assists health care professionals in determining an individual’s immune function, neuronal function and potentiality for progressive dysfunction resulting in a neuroautoimmune disorder. In the following pages we will review seven scenarios of chemical exposures that have been shown to affect the human nervous system. These include Silicone Implants, the Cantara Metam Sodium Spill, Gasoline Chemicals Exposure, the Effect of Industrial Solvents, Mold and Mycotoxin Exposure, Gulf War Syndrome and heavy air pollution. These examples illustrate the various types of exposures from purposefully-injected to accidental, from acute to chronic low-dose and the combination of xenobiotics that can elicit neurologic complaints from mild to severe.

SILICONE IMPLANTS Silicone implants are not just for female breast augmentation; they are also common in calf enhancements and other muscle cosmetic treatments for body builders [10, 11], as well as in rhinoplasty [12]. Silicone implants have been shown to contribute to the autoimmune process [13, 14] and to suppress the immune system [15]. In a study on 40 women with silicone breast implants and 40 age-matched controls without implants [13], it was demonstrated that the silicone implant patients had much higher levels of rheumatoid factor, immune complexes, anti-nuclear antibodies, thyroid antibodies and myelin basic protein (MBP) antibodies. Furthermore, there was correlation between silicone implant patients with significantly elevated anti-MBP IgM antibodies and degree of symptomatology (see Table 1). The marked increase in anti-MBP antibodies in patients with implants indicates that body burden due to

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silicone exposure contributes to autoimmunity that may involve the central and peripheral nervous systems. As described by Vojdani et al. [14], silicone exposure can occur as the implant oozes or bleeds silicone particles into circulation; these particles are absorbed or bound to macromolecules surrounding the silicone bag; combined tissue antigen with silicone spheres is presented to macrophages via T helper cells to B cells interaction; antibodies are produced against silicone and human tissues. Table 1. Clinical complaints: 40 silicone breast implant patients versus 40 controls CLINICAL COMPLAINTS REPORTED Fatigue Fibromyalgia Attention Deficit

PATIENTS 90% 81.8% 75%

CONTROLS 4% 5% 3%

Three years after results of the above study were published a larger group of women with silicone breast implants were tested for 20 autoantibodies against age-matched controls. Bar-Meir and colleagues assessed 116 female patients, whose chief complaints included polyarthralgias, fatigue, myalgias, morning stiffness, and decreased memory, and 134 controls [15]. The results showed a statistically significant greater frequency of autoantibodies in women with implants for 15 of the 20 autoantigens; the most striking were anti-histones, ribosomal phosphate, SS-A, SS-B, Scl-70, cardiolipin, phosphatidylserine, gangliosides, and glomerular basement membrane [15]. Many patients produced multiple autoantibodies; 20% had four autoantibodies, 8% had six autoantibodies [15]. The presence of these autoantibodies in patients with silicone implants may possibly indicate future development of an autoimmune disease [15]. At the time of publication 10 out of 116 silicone implant patients had a diagnosed autoimmune disease [15]; given more time, the number may have been higher. The propensity toward autoimmunity in silicone breast implant patients is not the only medical concern. Immune suppression has also been shown. Specifically, natural killer cell activity is lowered in patients with implants [16]. When silicone breast implants were removed, 50% of the study patients had significant improvement in natural killer cell activity [16]. Researchers have not identified the mechanisms involved in natural killer cell activity suppression due to silicone implants and are speculating whether the effect is direct or indirect. The end result of immune suppression leaves the patient vulnerable to infectious agents. Epstein-Barr virus (EBV) has been implicated in MS [17,18]; Chlamydia pneumoniae infection of the central nervous system is suspected in encephalitis [19,20], and group A streptococcus is seen in PANDAS, ANDAS, neuropsychiatric disorders and Sydenham’s chorea [21,22]. In either case, whether autoimmunity targeting myelin sheaths or immune suppression, the clinical manifestation of toxic body burden to silicone implants may result in neurological disorder.

THE CANTARA METAM SODIUM SPILL Early December 1984 the world watched the horror of the Union Carbide pesticide plant disaster. In the wee hours of a single night 27 tons of methyl isocyanate leaked into the air over the 900,000 sleeping residents of Bhopal, India. This travesty caused thousands of premature deaths in the 20-year aftermath. On the other side of the world, July 14, 1991 at 9:50 pm, a Southern Pacific 97-car train derailed on the Cantara loop above the Upper Sacramento River. An estimated 19,000 gallons of metam sodium spilled into the river. By early morning, while volunteer firefighters went house to house in nearby Dunsmuir, California, and the California Highway Patrol closed a 50 mile stretch of

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Interstate 5, many residents had already become ill with symptoms including headaches, shortness of breath, chest pains, rashes, dizziness and vomiting, and were filling local medical offices and emergency rooms [23]. Metam sodium [C2H4NNaS2] is the active ingredient in many pesticide products. Agriculturally it is used as a soil fumigant to kill weeds, soil diseases and insects. Metam sodium was not designated by the EPA as “hazardous” while the US Coast Guard considered it “extremely hazardous” because it becomes poisonous when mixed with water [23]. The breakdown products of metam sodium include methyl isothiocyanate, hydrogen sulfide, carbon disulfide and methylamine. In the Cantara Spill, the train car fell from the bridge, landed on a rock below the water line and seeped metam sodium into the river. A toxic methyl isothiocyante plume 18 feet thick, 100 yards wide and ¾ of a mile long eventually made its way into Lake Shasta [23-25]. The environmental toll on the 100-mile stretch of river was staggering. Over a million fish perished, hundreds of thousands of willows, alders and cottonwoods along the river died, wildlife either starved or left the area [26], more than 700 people, including emergency responders and Dunsmuir residents, sought medical help (7 were hospitalized) [25], many reported lingering effects even 9 months after the incident [25,27], and in total 1500 personal injury claims were made [24]. Many of these patients exhibited neurological abnormalities and some developed peripheral neuropathy [unpublished data]. Abbott points out that environmental accidents, like the Cantara Spill, not only pose injury to humans from toxic insults, but disasterassociated morbidity includes emotional stress and other psychological effects on the community and emergency responders and thus plays a potential role for increased risk of communicable disease [24]. Although less toxic than the methyl isocyante gas released in Bhopal, metam sodium and its breakdown product, methyl isothiocyanate (MITC) [CH3N=C=S], are known to cause dizziness and headaches [28]. Furthermore, in vitro experiments showed that MITC is inactivated by body fluids (saliva, gastric juice), and the low-concentration-DNA-damaging properties of MITC are attenuated by non-enzymatic protein binding [29]. In laboratory experiments, exposure of human hepatoma cells to MITC led to formation of thiobarbituric acid reactive substances; therefore, it is likely that its DNA-damaging effects involve lipid peroxidation processes [29]. Industrial disasters, accidents or incidents expose humans not only to toxic chemicals but also to great physical and emotional stress. Individually, or in combination, these events can trigger neurological discomforts.

CHEMICALS IN GASOLINE AND SOLVENTS Classified as a hydrocarbon, benzene [C6H6] is an organic chemical compound composed of six carbon atoms arranged in a hexagonal ring. Benzene is naturally found in crude oil and because it has a high octane number, it is utilized in gasoline. Benzene is also used as a precursor to chemicals (ethylbenzene, cumene). Benzene has been an important solvent especially in the rubber and surface coating industries. Methyl tert-butyl ether (MTBE), is an organic compound [(CH3)3COCH3]. MTBE is a gasoline additive, used as an oxygenate to raise the octane number of gasoline and prevent engine knocking. Benzene ring containing materials such as phenol, toluene and MTBE can bind to human tissue proteins and form neo-antigens. These new antigen proteins are comprised of the haptenic chemical plus the tissue antigen. The formation of neo-antigens initiates immune responses which may result in antibody production against the chemical bound to human tissue. Continued exposure to the chemical and the subsequent continual production of antibodies against various tissue antigens may result in autoimmune reactivity. Acute inhalation exposure to high concentrations of chemicals in gasoline and solvents can cause drowsiness, fatigue, nausea, vertigo, narcosis, and other symptoms of central nervous system depression; however, the most damaging health outcomes associated with benzene exposure are the chronic effects due to repeated exposure of low concentrations over a period of many years [29].


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Due to their ability to dissolve in fats, most organic solvents, like benzene ring compounds, tend to accumulate in lipid-rich organs, such as nerve tissues of both the peripheral and the central nervous systems [30]. Benzene is also known to cross the placenta and has been found in cord blood at levels equal to or higher than maternal blood [31]. Indeed, an association between maternal airborne benzene exposure and birth defects has been noted [32]. With the oil industry centered in the state, it is no surprise that Texas ranks number one in the United States for benzene levels in ambient air and accounts for 48% of all benzene emissions in the nation [33]. In a study conducted in the oil state of Texas [33], it was shown that the risk of delivering a spina bifida-affected infant more than doubled for mothers living in census tracts with estimated benzene levels of ≥ 3 μg/m3. Benzene can lead to genetic toxicity by covalently binding to DNA and forming DNA adducts, which, if not repaired quickly, disrupts the microenvironment of the cell, leading to inhibition of important enzymes, cell death, and alteration of other cells. [31]. When this occurs during the critical window of fetal development, the complex cellular processes involved in neurulation (e.g., folate metabolism, cell proliferation, cellular adhesion, and vascular development) may be disturbed [33]. The final result could be a baby born with neural tube defects. Studies with adult populations exposed to occupational benzene ring compounds [30,34] support the finding that changes in the visual function can serve as an early marker of neurotoxic damage, especially that resulting from chronic low-level industrial exposure. Comparing the MTBE blood levels of gas station workers to car repair shop employees and commuters, there was a significant difference, 8 – 30 microgram/L, 0.1-32 microgram/L and 0.07 – 2.3 microgram/L respectively, between industry workers and commuters [29]. Gas station workers were more apt to complain of ailments than the other two groups [29]. Exposures to MTBE may result in eye irritation, burning of nose and throat, headaches, memory effects or skin rashes [35]. These chemicals may also contaminate drinking water and cause symptomatology described in persons exposed to benzene and MTBE via inhalation [35]. Utilizing the World Health Organization’s Neurobehavioral Core Test Battery (NCTB) researchers concluded that diesel pollutant-exposed workers in the locomotive industry had reduced neurobehavioral performance scores in hand-eye coordination, cognitive function, speed stimulation of motor nerve, visual assessments and memory skills [34]. Locomotive workers are exposed to not only benzene, but also toluene, n-hexane and cyclohexane.

INDUSTRIAL SOLVENTS A solvent is any liquid that can dissolve a substance. The name organic solvent is used for a large group of these chemicals that come from petroleum-based products. They are often used as degreasing agents and paint thinners. They are also used to manufacture a wide range of other products, such as adhesives, fuels, pharmaceuticals and cosmetics. Organic solvents came into the environment out of the Industrial Revolution in the latter half of the 19th Century from the coal-tar industry [36]. Solvents can be classified as chlorinated, petroleum, benzene or non-benzene aromatic. Studies on solvent exposures have shown solvents can affect central nervous system functioning in attention, processing speed and motor performance [37]. These chemicals are used in a number of common areas (see Table 2). The human effects of these solvents are varied. For example, trichloroethylene exposure can result in lymphoproliferative reaction, anti-nuclear and cardiolipin antibodies, protein modification, formation of adducts, stimulation of active TH17, production of ROS and NO, activation of T cells, cellular infiltration, increase in CD4+ and CD8+ T cells and inhibition of cellular apoptosis of naïve CD4+ and CD8+ T cells [reviewed in 36]. In a study conducted on 289 subjects exposed to chemicals in computer manufacturing plants, immunological abnormalities and markers of neural autoimmunity were found [38].

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Aristo Vojdani and Jama Lambert Table 2. Short list of common uses for organic solvents USE Dry Cleaning Paint Thinner Nail Polish Removers and Glue Solvents Spot Removers Detergents Perfumes Octane Booster Lighter Fluid Air Conditioning Coolant

CHEMICAL Tetrachloroethylene Toluene, Turpentine Acetone, Methyl Acetate, Ethyl Acetate Hexane, Petrol Ether Citrus Turpenes Ethanol Methyl tert-butyl ether Butane Chlorofluorocarbon

The patients in the study had been exposed to phthalic anhydride, formaldehyde, isocyanate trimellitic anhydride and aliphatic and aromatic hydrocarbons for ten years or more. Significant levels of IgM followed by IgG and IgA antibodies against MBP were detected in the exposed subjects [38]. Individuals with abnormal T4/T8 ratios exhibited simultaneous elevation of IgM and IgG rheumatoid factor and immune complexes [38]. This cocktail of chemicals contributed to a range of dysfunctions in the exposed subjects including [38]:        

Decreased cell-mediated immunity Abnormal lymphokine and cytokine production Natural killer cell function decline Mitogen-induced lymphocyte blastogenesis Impaired suppressor or helper cell generation Changes in helper/cytotoxic cell ratios Increase in antigen reactive TA1 positive cells Elevation in autoimmune biomarkers o Rheumatoid factor o Anti-nuclear antibodies o Immune complexes o Myelin basic protein antibodies

The authors concluded that the majority of exposed subjects demonstrated elevated MBP antibodies, an indication of demyelination, which should lead neurologists to look for autoimmune reactivity in their patients with a history of toxic exposures [38]. The excellent organic solvent review by Barragán-Martínez and colleagues includes a number of studies conducted on the prevalence of MS in a variety of work environments where organic solvents are used. These publications showed a rise in MS for nurse anesthetists; leather and shoe industry workers; auto repair workers; mechanical, oil textile, wood-working, paint, printing, plastic and rubber industries; and painters [36]. Organic solvents that have been shown to specifically affect the cerebellum are toluene, benzene and carbon disulfide [39]. Cerebellar disorders can manifest as depression, developmental delay, cerebellar cognitive affective syndrome, impaired multitasking ability, limited cognitive flexibility and other psychological distress [39]. Those studying the neurological effects of solvent exposures state: o

Sustained motor or attention difficulties and intellectual impairment have been seen among French gas utility workers [37].

Environmental Triggers of Neuroautoimmunity o

o

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The immune system and the immune defense mechanisms may be affected as a result of prolonged occupational chemical exposure, which mediates some of the symptomatology associated with such exposures [38]. Individuals with family history of autoimmunity, or carrying genetic factors, should avoid exposure to organic solvents in order to deter increasing their risk for autoimmune diseases [36].

Due to the varying immunologic effects of organic solvents that may lead to neuroinflammatory responses and neuroautoimmunity, susceptible individuals should endeavor to avoid exposures to solvents both in the work place and home environments.

MOLDS AND MYCOTOXINS Molds are multicellular fungi that are ubiquitous in outdoor and indoor environments. Mycotoxins are the metabolites produced by molds (see Table 3). Exposure to molds and mycotoxins can occur through inhalation, ingestion, and touching moldy surfaces. Adverse health effects may occur through allergic, infectious, irritant, or toxic processes. Table 3. Mycotoxins and their source molds MYCOTOXIN

PRODUCED BY

Aflatoxin

Aspergillus flavus

Alternariol

Alternaria

Aspergillus

Aspergillus fumigatus

Chaetoglobosins

Chaetomium

Cladosporin

Cladosporium herbarum

Cladosporium HSP-70

Cladosporium herbarum

Mycophenolic acid

Penicillium

Ochratoxin

Penicillium

Penicillium major antigen

Penicillium

Stachyhemolysin

Stachybotrys

Stachytoxins

Stachybotrys

T-2 Toxin

Fusarium

Trichothecenes (satratoxin, verrucarin, roridin)

Stachybotrys

Versitoxins

Aspergillus versicolor

Vomitoxin

Fusarium

Dietary Sources of Mycotoxins Aflatoxin B1 is the most potent natural carcinogen known and is usually the major aflatoxin produced by toxigenic strains. It is a well-studied mycotoxin found on grains and nuts, thus it is often consumed. However, in other cases it can be inhaled. The Curse of the Mummy stories have entertained us in literature, films and folklore for generations. Although an engaging thought, Egyptian pharaoh Tutankhamen, the Boy King, did not reach from the great beyond to strike down the

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men who audaciously entered his tomb. Instead, the mysterious and painful deaths of the archeologists, including Americans Arthur Mace and George Jay Gould, who died within 24 hours of opening the famous tomb, and British adventurer and financier Lord Carnarvon, who passed weeks later, were more likely caused by aflatoxicosis [40]. Tutankhamen and many other royals on a number of continents were entombed with baskets of rice. Aspergillus flavus grows on rice. This mold and its mycotoxin, aflatoxin, can thrive in a tomb environment [41]. When Carnarvon entered King Tut’s tomb, he crawled on his hands and knees, close to the wall, where he overturned containers. By disturbing the contents of the containers, now suspected of holding rice, Carnarvon inhaled copious amounts of aflatoxins. Carnarvon died after suffering from a high fever, severe pain, pneumonia in both lungs, and eventually heart and respiratory failure; exposure to mycotoxins can cause a form of pneumonia to which immune-compromised individuals, like Carnarvon had been, are susceptible [40]. Aflatoxin exposure can occur via airborne spores entering through the lung barrier, ingested food products entering through the intestinal barrier, or contacted spores entering through the skin barrier. The symptoms of aflatoxicosis depend on the amount and duration of the exposure; the age, health, and sex of the exposed individual; and many poorly understood synergistic effects involving genetics, dietary status, and interactions with other toxic insults [40,41]. Thus, the severity of aflatoxin harmfulness can be compounded by factors such as vitamin deficiency, caloric deprivation, alcohol abuse, and infectious disease status [42]. Aflatoxosis can suppress immune function, including lowering secretory IgA (SIgA) levels [44]. Due to the vital role SIgA plays in host defense, insufficient SIgA levels may cause a heightened vulnerability to microbial diseases, worsen the effects of malnutrition, and interact synergistically with other toxins [42,44]. Animal studies show that aflatoxin interferes with vitamins A and D, iron, selenium, and zinc nutrition [43]. In a review of animal studies [45], authors have mapped the effects aflatoxin exposure cause on:      

Respiratory System Gastrointestinal System Immune System Nervous System Renal System Reproductive System

Birth defects have also been reported. Tortillas made with contaminated corn may have caused a rash of newborns with missing or rudimentary brains in the Rio Grande Valley in the 1990s. Tortillas are an inexpensive dietary staple along the Texas-Mexico border. One study [46] found that pregnant women who ate 300 to 400 tortillas per month during the first trimester had twice the risk of giving birth to babies with the defects as women who ate less than 100 tortillas. Blood samples taken from these women indicated that the higher the level of the mycotoxin, fumonisin, the greater the risk of neural tube defects [46]. Clearly, the risks of eating molding grains may have devastating consequences. Authors in Pakistan suggest storing and preparing rice commodities with garlic and/or lemon grass extracts due to their ability to inhibit Aspergillus flavus and its aflatoxin production [43].

Water-Damaged Building Source of Mycotoxins Mold and mycotoxin growth is rampant in water-damaged buildings. A family left their North American home to rent a house in Hawaii. What sounds like a dream come true turned into a nightmare. The family described by Thrasher and colleagues [47] consisted of mom, dad, daughter, son, in utero daughter and pet dog. Ochratoxin A was the predominant mycotoxin in samples of urine,


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nasal secretions, breast milk, placenta and umbilical cord [47]. Among the family members symptoms ranged from mild wheezing to long-term memory loss, and a series of neurological evaluations including Profile of Mood States, Beck’s depression inventory and Limbic System Check List Score revealed mom and dad each had 17 neurological deficits, the daughter had noticeable tremors and when the son began school, his teacher reported that he lacked concentration while in class [47]. Additional studies have shown neurological effects on humans after exposure to molds and mycotoxins in water-damaged buildings [48-51]. Patients with documented mold exposures along with elevated antibodies to molds and mycotoxins exhibited symptoms of peripheral neuropathy (tingling, numbness, tremors and muscle weakness in extremities) [48]. These 119 patients were evaluated for 9 neuronal autoantibodies (MBP, myelin associated glycoprotein, asialoganglioside GM1, sulfatide, myelin oligodendrocyte glycoprotein, crystalline, glutamate, tubulin, chondroitin sulfate and neurofilament antigen) and all patients had significant elevations in neuronal autoantibodies [48]. Additionally 99 of the patients had abnormalities in latencies, amplitudes, and velocities of selected peripheral nerves, and peripheral neuropathy [48]. A comparison study [49] to evaluate the neurobehavioral and pulmonary impairment of 105 adults exposed to molds (Stacybotrus chartarum, Aspergillus, Penicillium, Chaetomium, Alterenaria, Fusarium, Rhizopus) and 100 patients exposed to other chemicals (hydrogen sulfide, diesel exhaust, formaldehyde, indoor air, organophosphate insecticides, glutaraldehyde, cleaning chemicals, polycholorinated biphenyls, carbon monoxide, chlorine, chrordane) were compared to 202 community referents without mold or chemical exposures. Neurophysiological tests, Simple Reaction Time and Choice Reaction Time were performed on the participants. The mold-exposed group had a total of 6.1 abnormalities and those exposed to chemicals had 7.1 compared to 1.2 abnormalities in referents [49]. The exposed groups showed decreased balance, longer reaction times, lengthened blink reflex latencies, increased color discrimination errors, and reduced visual field performances and grip strengths [49]. Compared to referents, the exposed groups had decreased verbal recall, impaired perceptual motor functions for peg placement and trail making, and reduced problem solving in digit Symbol Substitution and Culture Fair [49]. Due to the irreversible impact water-damaged buildings can have on neurological and respiratory human health, susceptible individuals must avoid these areas completely [49]. After mold exposure susceptible patients will show signs and symptoms of central and peripheral nervous system effects [51]. Measuring antibodies to the molds and mycotoxins alone may not complete the clinical picture. The presentation of clinical manifestations did not always correlate with the levels of mold or mycotoxin antibodies in all patients [50]. The presence of antibodies therefore may be an indication of exposure, when antibody levels do not correlate with disorder severity. Treatment of patients with mold/mycotoxin exposure must not only address the clinical condition of the patient, but also must include in-tandem bio-balancing of the home and work environments for mold [51].

GULF WAR SYNDROME War ravages every living being on the planet. Although relatively short-lived, as wars go, the Gulf War (August 2, 1990 – February 28, 1991) and its codename Operation Desert Storm (January 17, 1991 – February 28, 1991) had a lasting physical effect on deployed men and women compared to non-deployed military personnel. The name for the effect has been known as “Gulf War Syndrome” (GWS), “Chronic Multi-Symptom Illness” (CMI), “Gulf War Illness” and “Multi-Symptom condition” [52]. Symptoms of GWS include: muscle fatigue, tiredness, malaise, myalgia, impaired cognition, ataxia, diarrhea, bladder dysfunction, sweating disturbances, headaches, fever, arthralgia, skin rashes, gastrointestinal disturbances sleep disturbances, chemical sensitivity and odor intolerance [52]. The

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symptoms are very similar to those of patients chronically ill with immunologic alterations after exposure to chlorinated pesticides, silicone implants and solvents [53]. Officially, the Research Advisory Committee on Gulf War Veterans’ Illnesses ruled out wartime stress or psychiatric illness as the cause of GWS; instead suspected factors for GWS are combinations of the low-level exposure to sarin, pesticides, benzene, other solvents, pyridostigmine bromide [53,54], Arabian sand dust, depleted uranium shells, combustion by-products of oil well fires, diesel exhaust and infectious agents [53]. Research has pointed to subtle damage to the parasympathetic nervous system as an underlying mechanism in the GWS pathogenesis [54]. In Gulf War veterans (GWV) with unexplained symptoms (not attributed to medical diagnosis) 87% had cognitive symptoms, 38% experienced musculoskeletal symptoms and 42% were fatigued [55]. The 1.92 risk of developing amyotrophic lateral sclerosis (ALS) was significantly increased in deployed versus non-deployed veterans with a mortality risk of 1.53 for deployed GWV [55]. An increased rate of ALS, increased incidences of neurological diseases and abnormalities of basal ganglia and brainstem are found in GWVs [53] and have been explained by genetic polymorphism of paraoxonase [56,57], butyrylcholinesterase [58], esterase [59], glutathione S-transferase and cytochrome P4501A1 [60]. Furthermore the risk of ALS was significantly higher in GWVs in the Air Force or Army [55]. Of the 700,000 deployed US GWVs about 25% developed GWS [61]. Chronic low-level exposure to organophosphates is the major suspect. Organophosphates are the basis for insecticides and nerve gases, both of which were used during the Gulf War. Insecticides were applied to the skin, clothing, tents, sleeping quarters and sprayed in the camps [61]. This can explain the increased risk for ALS in deployed Air Force and Army GWVs. GWS has been reported more in those with the highest exposures to organophosphates [61]. The insecticide chlorpyrifos (CP) was used extensively in camps. The metabolite of CP is chlorpyrifos oxon (CPO), which is several-fold more potent than CP as a neurotoxin due to its irreversible inhibition of acetylcholinesterase activity [61]. Oxidative conversion of CP to CPO occurs when CP comes into contact with oxidizing decontaminating cleaning and laundry products [61]. The human immune defense against organophosphates is the liver enzyme paraoxanase I (PONI). This antioxidant neutralizes nerve agents. GWVs who became chronically ill had lower levels of PONI and thus were unable to clear the toxins from the body, which may have negatively impacted the nervous system [61]. Pyridostigmine bromide (PB), another chemical used during the Gulf War, has also been studied. PB exposures contribute to many of the above mentioned GWS conditions. There are noticeable trends toward worse health with greater exposure to PB [52]. Central nervous system injury has been reported in animal studies of exposure to PB [63]. Studying GWVs, researchers have found an increase in autoantibodies to MBP [53] which is thought to have occurred from tissue injury after exposure to toxic chemicals [1,64]. The increase of IgM to MBP appears to indicate that an active process involving the release of neuronal antigens occurs up to 8 years after initial injury of the central nervous system [53]. GWS seems to be the result of a confluence of chemical exposures and both the physical and emotional stress of war. The bombardment of chemical exposures easily penetrates the over-stressed human body. If the soldier is genetically weak in enzyme activity, these chemicals are not cleared out of the body and instead are able to injure the central and peripheral nervous systems.

AIR POLLUTION Air pollution is a composite mixture of ozone and particulate matter. Composition depends on industrial pollutants, automobile exhaust and wind currents, and thus varies from region to region, city to city, continent to continent. Air pollution may include serious xenobiotics such as carbon


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monoxide, lead, nitrogen dioxide and sulfur dioxide, lipopolysaccharides, mercury, arsenic, benzene, formaldehyde and acid gases. Chronic exposure to air pollution is associated with respiratory and cardiovascular-related sickness and death [65]. Ozone has been shown to cause respiratory tract epithelial injury and inflammation [66], while particulate matter can evoke inflammatory responses [67-69]. Inflammatory processes beginning in the nose can result in brain inflammation (see Figure 3). The residents of two highly-polluted cities in Mexico were studied due to their chronic exposure to a complex mixture of air pollutants, including ozone and particulate matter [70].

Figure 3. The nose-brain connection to brain inflammation.

Studying autopsied brain samples from lifelong residents of Mexico City, Monterrey, and five small cities with low levels of air pollution (Abasolo, Iguala, El Mante, Tlaxcala, and Veracruz), researchers found Alzheimer’s-like pathology in residents exposed to high levels of air pollution [70]. Ozone and particulate matter are the major air pollutants for both Mexico City and Monterrey. The high-exposure group included 10 subjects, while 9 subjects made up the low-exposure group. Interesting to note, all subjects were non-smokers from middle socioeconomic status [70]. Inclusion criteria for the study were as follows :       

Researcher access to complete clinical information for at least 3 months prior to death No evidence of neurological disease or cognitive abnormalities by medical history and by complete neuropathological examination Body mass index between 19 and 25 Negative family history of dementia Negative history of drug addictions, occupational exposures to potential neurotoxicants, recent vaccinations, and intake of vitamins, dietary or herbal supplements Negative history of non-steroidal anti-inflammatory drugs (NSAID) and steroidal compounds A negative history of depression, memory complaints, and speech or learning disabilities was required.

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Additionally, the subjects had no clinical history or pathological evidence of short- or long-term inflammatory processes, administration of anti-inflammatory drugs or hormones, or events such as cerebral ischemia, head trauma, or epilepsy. This, and previous studies by the author, have provided evidence of brain inflammation in the form of an upregulation of the expression of prostaglandin-endoperoxide synthase 2, also known as cyclooxygenase-2 (COX2), an extremely potent biologically-active mediator of inflammation, in the brains of both human and dog residents of Mexico City [68,70]. COX-2 is rapidly expressed in several cell types in response to growth factors, cytokines, and pro-inflammatory molecules and is responsible for ‘‘pathological’’ prostaglandin (PG) H synthase. COX2 expression was predominantly observed in capillary endothelium [70]. Blood vessels of the brain exhibit inherent and induced expression of receptors for inflammatory cytokines (TNF-alpha, IL-1beta, and IL-6) [71,72]. Chronic respiratory tract inflammation may lead to chronic brain inflammation by altering levels of circulating cytokines [71] and that are known to be transported across the blood–brain barrier [71,72]. The brains of Mexico City dogs exhibit upregulation of COX2 expression, indicative of chronic brain inflammation, and accelerated accumulation of 42-amino acid form of β-amyloid (Aβ42), a neurotoxic fragment of the amyloid precursor protein (APP) that causes neuronal dysfunction [68,73]. The canine data suggested that chronic exposure of humans to severe urban air pollution may also have adverse effects in human brains [70]. Lipopolysaccharide (LPS) is a component of Mexico City particulate matter [69]. Systemic administration of LPS to rodents causes upregulation of COX2 in brain perivascular and endothelial cells [68,74] and alters the expression or processing of APP or both. LPS also accelerates the generation of Aβ42 in transgenic mice [75] and increases the abundance of APP751 [76]. This pairing of LPS and COX2 appears to have lasting neurological effects. An estimated 5.4 million Americans have Alzheimer’s disease (AD) [77]. The environmental role in the pathogenesis of AD is unknown. The identification and alleviation of environmental factors that influence AD pathogenesis is a fundamental approach to limiting the rising numbers of AD cases. About half of all Americans live in areas where levels of smog are unhealthy, while many individuals endure occupational and indoor exposures to air pollutants [70].

CLINICAL MECHANISMS Depending on the person’s genetic ability to handle toxins, amount and duration of exposure and body burden of accumulated insults, immunotoxicity may lead to:   

Neuroinflammation Neuroautoimmune reactivity Neurodegeneration

Autoimmune responses can be induced by environmental chemicals through a variety of effects including cellular, biochemical and molecular [78]. The chemical’s toxic effects can indirectly damage the structural integrity or function of organs or tissues (see Figure 4) [78]. As a chemical enters the body it is metabolized. The parent compound and the metabolite may attach to human tissue. The toxic effect of the chemical and its metabolite can cause tissue damage resulting in the release of tissue antigens into circulation. At this point the APC can pick up the parent compound bound to tissue, the metabolite bound to tissue or the tissue antigen. The APC hands the antigen(s) to the T-cell, which begins the process of antibody production.


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The potential immune responses are:   

Antibodies to the chemical bound to human tissue Antibodies to the chemical’s metabolite bound to human tissue Autoantibodies to human tissue.

Figure 4. Possible antibodies produced from chemical exposure.

Chemicals can directly influence cytokine production or inhibition of certain lymphocyte subsets [78]. Polycyclic aromatic hydrocarbons (PAHs) are known to influence TH17 cells [79] which produce IL-17A, an inflammatory cytokine implicated in autoimmunity. Although this article is focused on neuroautoimmunity, it is important to note the role some chemicals play in cancers. Aflatoxin is a potent carcinogen. The liver is the primary target organ for aflatoxins. Cytochrome P450 enzymes convert aflatoxins to the reactive 8,9-epoxide form, which can bind to both DNA and human proteins [42]. To clear aflatoxins, a reactive glutathione S-transferase system, found in the cytosol and microsomes, catalyzes the conjugation of activated aflatoxins with reduced glutathione, thus inducing the expulsion of aflatoxin [42]. Subjects exposed to aflatoxins were four times more likely to develop liver cancer than unexposed controls, while the subject group infected with hepatitis B virus and exposed to aflatoxins was sixty times more likely to develop liver cancer [78]. Silicone breast implants have been shown to increase the risk of multiple myeloma [81]. Although this study [82] was performed on occupational exposures to specific agricultural pesticides not discussed in this paper, it is important to state that pesticides have been shown to increase the risk of monoclonal gammopathy of undetermined significance (MGUS) in men.

CONCLUSION Exposures to environmental chemicals occur daily around the world. It is only when these exposures, which can be acute or chronic low-level, reach a threshold of body burden that clinical effects will manifest. If a person’s genetic ability to clear toxic substances from the body functions properly, the person will remain healthy. Unfortunately for many individuals, environmental exposures can trigger an autoimmune cascade that results in neuroinflammation and

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neuroautoimmunity, or these exposures can manifest in immune suppression leaving the patient susceptible to stealth organisms known to contribute to neuronal disorders. Today clinicians have tools to assess at-risk individuals. Autoantibodies to neuronal tissues can be detected in sera prior to the clinical onset of disease. Body burden of toxin exposure can be assessed using antibodies to the chemical bound to human tissue. These assessments, along with other pertinent clinical data, can improve the diagnosis and treatment of environmentally-triggered neuroautoimmune disorders. Screens for the detection of multiple autoimmune reactivity, neurological autoimmune reactivity, and chemical autoimmune reactivity are part of a very special menu offered by Cyrex Labs in Phoenix, AZ, as their Array 5, Array 7, and Array 11, respectively.

REFERENCES [1] [2]

[3]

[4]

[5] [6] [7]

[8]

[9] [10] [11] [12]

[13] [14] [15] [16]

Greim P, Wulferink M, Sachs B, González JB, Gleichmann E. Allergic and autoimmune reactions to xenobiotics: how do they arise? Immunol Today. 1998;19(3):133-141. Pollard KM, Lee DK, Casiano CA, Bluthner M, Johnston MM, Tan EM. The autoimmunityinducing xenobiotic mercury interacts with the autoantigen fibrillarin and modifies its molecular and antigenic properties. J. Immunol. 1997;158(7):3521-3528. Wulferink, M. Chemical-induced allergy and autoimmunity. Medical Institute for Environmental Hygeine at Heinrich Heine University Duesseldorf: Duesseldorf, Germany; 1971. Abedi-Valugerdi M, Hu H, Möller G. Mercury-induced anti-nucleolar autoantibodies can transgress the membrane of living cells in vivo and in vitro. Internatl Immunol. 1999;11(5):605615. Kono DH, Park MS, Szydlik A, et al. Resistance to xenobiotic-induced autoimmunity maps to chromosome 1. J. Immunol. 2001;167:2396-2403. Utz, PJ, Gensler TJ, Anderson P. Death, autoantigen modifications, and tolerance. Arthritis Res. 2000;101-114. Silva IA, Nyland JF, Gorman A, Perisse A, Ventura AM, Santos EC, Souza JM, Burek CL, Rose NR, Silbergeld EK. Mercury exposure, malaria, and serum antinuclear/antinucleolar antibodies in amazon populations in Brazil: a cross-sectional study. Environ. Health. 2004;3:11. Vojdani A, Pangborn JB, Vojdani E, Cooper EL. Infections, toxic chemicals and dietary peptides binding to lymphocyte receptors and tissue enzymes are major instigators of autoimmunity in autism. Internatl J. Immunopathol Pharmacol. 2003;16(3):189-199. Bigazzi PE. Autoimmunity caused by xenobiotics. Toxicology. 1997;119:1-21. Flores-Lima G and Eppley B. Body contouring with solid silicone implants. Aesthetic Plast Surg,.2009;33(2):140-146. Niechajev I. Calf augmentation and restoration. Plast Reconstr Surg. 2005;116(1):295-305. Jung DH, Kim BR, Choi JY, et al. Gross and pathologic analysis of long-term silicone implants inserted into the human body for augmentation rhinoplasty: 221 revision cases. Plast Reconstr Surg. 2007;120(7):1997-2003. Vojdani A, Campbell A, Brautbar N. Immune functional impairment in patients with clinical abnormalities and silicone breast implants. Toxicol Ind Health. 1992;8(6):415-429. Vojdani A, Brautbar N, Campbell A. Antibody to silicone and native macromolecules in women with silicone breast implants. Immunopharmacol Immunotoxicol. 1994;16(4):497-523. Bar-Meir E, Teuber SS, Lin HC, et al. Multiple autoantibodies in patients with silicone breast implants. J. Autoimmun. 1995;8(2):267-277. Campbell A, Brautbar N, Vojdani A. Suppressed natural killer cell activity in patients with silicone breast implants: reversal upon explantation. Toxicol Ind Health. 1994;10(3):149-154.


199

[17] Lünemann JD, Kamradt T, Martin R, Münz C. Epstein-barr virus: environmental trigger of multiple sclerosis? J. Virol. 2007;81(13):6777-6784. [18] Serafini B, Rosicarelli B, Franciotta D, Magliozzi R, Reynolds R, Cinque P, Andreoni L, Trivedi P, Salvetti M, Faggioni A, Aloisi F. Dysregulated Epstein-Barr virus infection in the multiple sclerosis brain. J. Exp. Med. 2007;204(12):2899-2912. [19] Du C, Yao SY, Ljunggren-Rose A, Sriram S. Chlamydia pneumoniae infection of the central nervous system worsens experimental allergic encephalitis. J. Exp. Med. 2002;196(12):16391644. [20] Xavier M, Correa B, Coromina M, et al. Sudden psychotic episode probably due to meningoencephalitis and Chlamydia pneumoniae acute infection. Clin. Pract Epidemiol Ment Health. 2005;1:15. [21] Tan J, Smith CH, Goldman RD. Pediatric autoimmune neuropsychiatric disorders associated with streptococcal infections. Can Fam. Physician. 2012;58(9):957-959. [22] Dale RC. Autoimmunity and the basal ganglia: new insights into old diseases. Q. J. Med. 2003;96(3):183-191. [23] Gherman E. A toxic nightmare: the Dunsmuir metam sodium spill revisited. In: Reactions of a kindly nature. Sonoma County Free Press; 1997 Jul. (cited 2013 Jan 31). Available from: http://www.sonomacountyfreepress.com/reaction/a_toxic_nightmare.html.]. [24] Darling D. 20th anniversary of Cantara Loop spill: measures taken to keep Sacramento River clean. Redding.com; 2011. (cited 2013 Jan 31). Available from: [http://www.redding.com/news/2011/jul/09/legacy-of-a-disaster/]. [25] Abbott D. Disaster public health considerations. Prehospital Disaster Med. 2000;15(4):158-166. [26] Cantara Trustee Council. Final Report on the recovery of the Upper Sacramento River: subsequent to the 1991 Cantara spill. 2007. [27] Kreutzer RA, Hewitt DJ, Draper WM. An epidemiological assessment of the Cantara metam sodium spill: acute health effects and methyl isothiocyanate exposure. In: Draper WM, editor. Environmental epidemiology: effects of environmental chemicals on human health. A symposium sponsored by the Division of Environmental chemistry, Inc. at the 203rd national meeting of the American Chemical Society. San Francisco, California. 1992 Apr 5 – 10,. Advances in Chemistry Series No. 241. 1994:209-230. [28] Pruett SB, Myers LP, Keil DE. Toxicology of metam sodium. In: Journal of toxicology and environmental health part B: critical reviews. (vol 4, no 2); Taylor and Francis Ltd. 2001:207222. [29] NIOSH. Health Hazard Evaluation Report No. 93-802-2338, 1993. [30] Lee E-H, Eum KD, Cho SI, Cheong HK, Paek do M. Acquired dyschromatopsia among petrochemical industry workers exposed to benzene. Neuro Toxicology. 2007;28:356–363. [31] ATSDR (Agency for Toxic Substances and Disease Registry). Toxicological Profile of Benzene. 2007. Available from: http://www.atsdr.cdc.gov/toxprofiles/tp3.pdf [32] Lupo PJ, Symanski E, Waller DK, Chan W, Langlois PH, Canfield MA, Mitchell LE. Maternal exposure to ambient levels of benzene and neural tube defects among offspring: Texas, 1999– 2004. Environ. Health Perspect. 2001;119:397–402. [33] U.S. EPA (U.S. Environmental Protection Agency). Access the air quality system data mart. 2007. Available from: http://www.epa.gov/ttn/airs/aqsdatamart/access.htm [34] Ithnin A, Shaari RAH, Sahani M, Mokhtar AM, Halim AA, Awang N. Effects of pollutant diesel fuels on neurobehavioral performance among workers in locomotive depot. Am. J. Environ. Sci. 2011;7(3):248-253. [35] Vojdani A ad Brautbar N. Containated drinking water with TBE and gasoline: immunological and cellular effects. Eur. J. Oncol. 1998;3(3):191-199.

200


[36] Barragán-Martínez C, Speck-Hernández CA, Montoya-Ortiz G, Mantilla RD, Anaya JM, RojasVillarraga A. Organic solvents as risk factor for autoimmune diseases: a systemic review and meta-analysis. PLoS ONE. 2012;7(12):e51506. doi:10.137/journal.pone.0051506. [37] Sabbath EL, Glymour MM, Berr C, Singh-Manoux A, Zins M, Goldberg M, Berkman LF. Occupational solvent exposure and cognition: does the association vary by level of education? Neurology. 2012;78(22):1754-1760. [38] Vojdani A, Ghoneum M, Brautbar N. Immune alteration associated with exposure to toxic chemicals. Toxicol Indust Health. 1992;8(5):239-254. [39] Schmahmann JD. Disorders of the cerebellum: ataxia, dysmetria or thought, and the cerebellar cognitive affective syndrome. J. Neuropsych Clin. Neurosci, 2004; 16:367-378. [40] Cox AM. The death of Lord Carnarvon. Lancet. 2003;361:1995. [41] Gandon S. The curse of the pharaoh hypothesis. Proc R Soc Lond B. 1998;265:1545-1552. [42] Bennett JW, Klich M. Mycotoxins. Clin. Microbiol Rev. 2003;16(3):497-516. [43] Qazi JI and Fayyaz Z. Aflatoxin contaminated foods and health risk perspective for Pakistani population. Mycopath. 2006;4(2):27-34. [44] Turner PC, Moore SE, Hall AJ, Prentice AM, Wild CP. Modification of immune function through exposure to dietary aflatoxin in Gambian children. Environ Health Perspect. 2003;111:217–220. [45] Coulombe RA. Nonhepatic disposition and effects of aflatoxin B1. In: The toxicology of aflatoxins: human health, veterinary and agricultural significance. Eaton DL, Groopman JD, editors. Academic Press; 1993. p. 89-101. [46] Missmer SA, Suarez L, Felkner M, Wang E, Merrill AH Jr, Rothman KJ, Hendricks KA. Exposure to fumonisins and the occurrence of neural tube defects along the Texas-Mexico border. Environ. Health Perspect. 2006;114(2):237-241. [47] Thrasher JD, Gray MR, Kilburn KH, Kilburn KH, Dennis DP, Yu A. A water-damaged home and health of occupants: a case study. J. Environ. Public Health. 2012;2012:312836. doi: 10.1155/2012/312836. [48] Campbell AW, Thrasher JD, Madison RA, Vojdani A, Gray MR, Johnson A. Neural autoantibodies and neurophysiologic abnormalities in patients exposed to molds in waterdamaged buildings. In: Molds and mycotoxins: papers from an international symposium. Kilburn KH, editor. Washington, DC: Heldref Publications, 2004. p. 46-54. [49] Kilburn KH. Neurobehavioral and pulmonary impairment in 105 adults with indoor exposure to molds compared to 100 exposed to chemicals. Toxicol Industr Health. 2009;25(9-10):681-692. [50] Vojdani A, Campbell AW, Kahanian A, Vojdani E. Antibodies against molds and mycotoxins following exposure to toxigenic fungi in a water-damaged building. Arch Environ Health. 2003;58(6):324-336. [51] Empting LD. Neurologic and neuropsychiatric syndrome features of mold and mycotoxin exposure. Toxicol Industr Health. 2009;25(9-10):577-581. [52] Israeli E. Gulf War Syndrome as a part of the autoimmune (autoinflammatory) syndrome induced by adjuvant (ASIA). Lupus. 2012;21:190–194. [53] Vojdani A and Thrasher JD. Cellular and humoral immune abnormalities in Gulf War veterans. Environ. Health Perspect. 2004;112(8):840-846. [54] Vastag B. Gulf War syndrome not due to wartime stress or psychiatric illness. Lancet Neurol. 2004;3(12):702. [55] Rose MR, Brix KA. Neurological disorders in Gulf War veterans. Phil Trans R Soc B. 2006;361:605-618.


201

[56] Haley RW, Billecke S, La Du BN. Association of low PON1 type Q (type A) arylesterase activity with neurologic symptom complexes in Gulf War veterans. Toxicol Appl Pharmacol. 1999;157:227–233. [57] La Du BN, Billecke C, Hsu R, et al. Serum paraoxonase (PON1) isozymes: the quantitative analysis of isozymes affecting individual sensitivity to environmental chemicals. Drug Metab Disp. 2001;29:566–569. [58] Shen ZX. Pyridostigmine bromide and Gulf War syndrome. Med. Hypotheses. 1998;51:235– 237. [59] Winrow CJ, Hemming ML, Allen DM, et al. Loss of neuropathy target esterase in mice links organophosphate exposure to hyperactivity. Nat. Genet. 2003;33:477–485. [60] Whatt RM, Perera FP, Jedrchowski W, Santella RM, Garte S, Bell DA. Association between polycyclic aromatic hydrocarbon-DNA adduct levels in maternal and newborn white blood cells and glutathione S-transferase and CYP1A1 polymorphism. Cancer Epidem Biomark Prev. 2000;9:207–212. [61] Cao J-l, Varnell AL, Cooper DC. Gulf War Syndrome: a role for organophosphate induced plasticity of locus coeruleus neurons. Nature Proceedings, 2011. Available from: http://hdl.handle.net/10101/npre.2011.6057.1 [62] Abou-Donia MB, Goldstein LB, Jones KH, Abdel-Rahman AA, Damodaran TV, Dechkovskaia AM, Bullman SL, Amir BE, Khan WA. Locomotor and sensorimotor performance deficit in rats following exposure to pyridostigmine bromide, DEET, and permethrin, alone and in combination. Toxicol Sci. 2001;60:305–314. [63] Cooper GS, Miller FW, Germolec DR. Occupational exposures and autoimmune diseases. Int. Immunopharmacol. 2002;2:303–313. [64] Brunekreef B and Holgate ST. Air pollution and health. Lancet. 2002;360:1233–1242. [65] American Thoracic Society. Health effects of outdoor air pollution. Committee of the Environmental and Occupational Health Assembly of the American Thoracic Society. Am. J. Respir Crit Care Med. 1996;153:3–50. [66] Elmquist JK, Breder CD, Sherin JE, Scammell TE, Hickey WF, Dewitt D, Saper CB. Intravenous lipopolysaccharide induces cyclooxygenase 2-like immunoreactivity in rat brain perivascular microglia and meningeal macrophages. J. Comp. Neurol. 1997;381:119–129. [67] Calderón-Garcidueñas L, Maronpot RR, Torres-Jardon R, Henríquez-Roldán C, Schoonhoven R, Acuña-Ayala H, Villarreal-Calderón A, Nakamura J, Fernando R, Reed W, Azzarelli B, Swenberg JA. DNA damage in nasal and brain tissues of canines exposed to air pollutants is associated with evidence of chronic brain inflammation and neurodegeneration. Toxicol Pathol. 2003;31:524–538. [68] Osornio-Vargas AR, Bonner JC, Alfaro-Moreno E, Martínez L, García-Cuellar C, Ponce-deLeón Rosales S, Miranda J, Rosas I. Proinflammatory and cytotoxic effects of Mexico City air pollution particulate matter in vitro are dependent on particle size and composition. Environ Health Perspect. 2003;111:1289–1293. [69] Calderón-Garcidueñas L, Reed W, Maronpot RR, Henríquez-Roldán C, Delgado-Chavez R, Calderón-Garcidueñas A, Dragustinovis I, Franco-Lira M, Aragón-Flores M, Solt AC, Altenburg M, Torres-Jardón R, Swenberg JA. Brain inflammation and Alzheimer's-like pathology in individuals exposed to severe air pollution. Toxicol Pathol. 2004;32(6):650-658. [70] Rivest S. How circulating cytokines trigger the neural circuits that control the hypothalamicpituitary-adrenal axis. Psychoneuroendocrinology. 2001;26:761–788. [71] Nguyen MD, Julien JP, Rivest S. Innate immunity: the missing link in neuroprotection and neurodegeneration? Nat. Rev. Neurosci. 2002;3:216–227. [72] Selkoe DJ. Alzheimer’s disease: genes, proteins, and therapy. Physiol. Rev. 2001;81:741–766.

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[73] Yermakova AV and O’Banion MK. Downregulation of neuronal cyclooxygenase-2 expression in end stage Alzheimer’s disease. Neurobiol Aging. 2001;22:823–836. [74] Sheng JG, Bora SH, Xu G, Borchelt DR, Price DL, Koliatsos VE. Lipopolysaccharide-inducedneuroinflammation increases intracellular accumulation of amyloid precursor protein and amyloid β peptide in APPswe transgenic mice. Neurobiol Dis. 2003;14:133–145. [75] Brugg B, Dubreuil YL, Huber G, Wollman EE, Delhaye-Bouchaud N, Mariani J. Inflammatory processes induce β-amyloid precursor protein changes in mouse brain. Proc. Natl. Sci. USA. 1995;92:3032–3035. [76] Alzheimer's Association. 2012 Alzheimer's disease facts and figures. Alzheimers Dement. 2012;8(2):131-168. doi: 10.1016/j.jalz.2012.02.001. [77] Perera FP. Uncovering new clues to cancer risk. Sci Am. 1996;274(5):54-55,58-62. [78] Bigazzi PE. Autoimmunity caused by xenobiotics. Toxicology. 1997;119:1-21. [79] Monteleone I, Pallone F, Monteleone G. Th17-related cytokines: new players in the control of chronic intestinal inflammation. BMC Med. 2011;9:122. doi: 10.1186/1741-7015-9-122. [80] Rabkin CS, Silverman S, Tricot G, Garland LL, Ballester O, Potter M. The national cancer institute silicone implant/multiple myeloma registry. Curr Topics Microbiol Immunol. 1996;210:385-387. [81] Landgren O, Kyle RA, Hoppin JA, Beane Freeman LE, Cerhan JR, Katzmann JA, Rajkumar SV, Alavanja MC. Pesticide exposure and risk of monoclonal gammopathy of undetermined significance in the Agricultural Health Study. Blood. 2009;113(25):6386-6391.

Received: June 14 2013, Revised: June 21 2013, Accepted: June: 23 2013.



TOXICANT LOSS OF IMMUNE TOLERANCE, NEUROLOGIC DISEASE, AND NUTRITIONAL STRATEGIES Datis Kharrazian Bastyr University, San Diego, CA USA

ABSTRACT This paper reviews immunology models of chemical tolerance and the role they may play with the pathogenesis of neurological autoimmune and neurodegenerative disease and how we may be able to reduce the impacts of these adverse reactions with various nutritional applications. The immune model of chemical tolerance describes how trace amounts of exposures to various chemicals commonly found within our environment lead to exaggerated immune responses turning on the cascade of immune dysregulation and systemic inflammation leading to neurological disease. Immune chemical tolerance is maintained by healthy integration of various immune cells that can be disrupted from toxicant exposure, chronic stress physiology, blood-brain barrier compromise, intestinal barrier compromise, hormone imbalances, antigenic models, oxidative stress models, and various mechanisms that induce loss of healthy immune integration. These mechanisms themselves have been shown to have the ability to be manipulated and modulated with various nutritional applications. With an increasing epidemic of toxicant load and virtually no conventional or pharmaceutical strategies to decrease their impacts on human systems evidence-based consideration leads us to the potential role of various natural compounds that exhibit activity that can decrease the expression NF-kappaB, optimize glutathione redox systems, improve barrier system impermeability, and support regulatory T-cell activity all which is essential to improve chemical immune tolerance environmental toxicants.

Keywords: Autoimmune, neurodegenerative disease, environment, chemical tolerance, oxidative stress, blood-brain barrier, nutrition

INTRODUCTION There is no question that environmental pollution and toxins have potential for severe adverse impacts on both developmental brain health and inflammatory and autoimmune mechanisms of neurodegeneration [1]. We are living in a world that has changed dramatically within our lifetimes. We are now exposed to countless chemicals, hybridized foods, and genetically modified foods, all of which are very immune activating. Additionally, the increased use of pharmaceutical drugs is increasing rapidly. This polypharmacy model of various drugs potentially has diverse impacts on human physiology beyond known adverse reactions and iatrogenic causes of death and disability. The U.S. consumption of foods known as the Standard American Diet (SAD) is not only very 

Correspondence: Dr. Datis Kharazian, 1001 Canvasback Court Carlsbad, CA 92011 Email [email protected]

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inflammatory but also very immune activating. The combination of chronic exposure to triggering pollutants, toxins, and inflammatory foods has potentially contributed to inflammatory ailments that we as clinicians face today. Many have theorized that the development of autoimmunity, autism, and neurodegenerative diseases and other inflammatory conditions may be result of our newly immune reactive environment [2-5].

immune various growing chronic

Chemical Tolerance Chemical tolerance is our immune system’s ability to react proportionately to compounds such as toxins, pollutants, and environmental proteins. The loss of chemical tolerance is a phenomenon both researchers and clinicians have identified as a mechanism leading to disease and inflammatory promoting reactions to commonly exposed pollutants within the environment that then lead to pathophysiological expression leading to chronic illness [6]. Immune chemical tolerance is dependent upon many overlapping physiological factors that include regulatory T-Cell integrity, antioxidant reserves, barrier system integrity, and integrity of hepatic biotransformation pathways. All of these systems can be compromised with various toxins; however these systems can also be compromised unrelated to toxin exposure from various etiologies and also lead to loss of chemical tolerance. Our immune system has some degree of tolerance to our environment however and loss of immune tolerance may lead to neurological autoimmunity involving known autoimmune diseases such as multiple sclerosis, autoimmune neuropathy, etc., but it may also be an underlying autoimmune factor for diseases such as Alzheimer’s, Parkinson’s, and autism [7-9]. The unprecedented levels of chemicals and heavy metals today, as well as hybridized, genetically modified, and industrially processed foods, all activate the immune system towards a proinflammatory expression. Only a minority of the synthetic compounds introduced to our environment have been researched individually, much less in conjunction with one another. The Environmental Protection Agency (EPA) doesn’t require testing on chemicals introduced to market unless evidence of potential harm exists, which means testing seldom happens. The EPA approves about 90 percent of new chemicals and only a quarter of more than 80,000 have been tested for toxicity [10]. Americans are born with increasingly high levels of chemical and toxin burdens. For example, a 2005 study of cord blood from newborns found almost 300 environmental compounds, including mercury and DDT. Another study showed first-time mothers in the United States had levels of flame retardants in their breast milk 75 times higher than in similar European studies. Environmental toxins have been linked with neurodegenerative conditions such as Alzheimer’s and Parkinson’s disease [13-15].

NF-κB and Chemical Immune Reactivity Environmental toxicant activations of NF-kappaB is a powerful force capable of igniting relentless inflammatory cascades that play a role in neurological degeneration, autoimmunity, cancer, and loss of chemical tolerance. [16]. NF-κB is a protein inside of cells that acts as a switch to turn inflammation on and off in the body. It responds to whatever may be conceived as a threat to the cell, including environmental toxins, toxic metabolites, pollutants, and xenobiotics [17]. Systemic toxic load increase NF-κB activation promotion inflammation degradation of the barriers of the gut, brain and lungs, further increasing inflammation and loss of chemical tolerance [18]. Chronic activation of NF-κB also impairs cytochrome p45O hepatic biotransformation phase 1 oxidation/reduction reactions yielding compounds that are more immunoreactive and further perpetuating loss of chemical tolerance and perpetuation of inflammatory cascades that have potential to activate environmental hapten-induced neurodegeneration or autoimmunity [19-23].

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It has been shown recently that NF-κB is required for activation of autoreactive T-cells, and its hyperactivity in monocytes and dendritic cells results in altered cytokine secretion and antigen presentation, which ultimately contribute to the initiation of autoimmunity [24]. An increasing number of studies indicate that NF-κB plays an important role in controlling the expression of genes relevant to the pathogenesis of autoimmunity. NF-κB is a protein complex that controls the transcription of DNA. It is found in all cell types and is involved in cellular responses to stimuli, such as stress, cytokines, free radicals, and antigens. NF-κB controls the expression of genes encoding the proinflammatory cytokines, chemokines, adhesion molecules, inducible enzymes (COX-2 and iNOS), and growth factors [25]. Once the NF-κB amplifying loop is activated, it may persist as an expression of chronic inflammation and autoimmunity, unless an active NF-κB inhibitor is provided. The two most naturally powerful supporters of a healthy NF-κB suppression are resveratrol and curcumin [26]. In recent studies, both curcumin and resveratrol have supported healthy numbers of T-cell cytokines [27, 28]. These results suggest the potential use of these select phytochemicals for supporting healthy immune responses. Research indicates that curcumin has the potential to support cardiovascular health through the minimization of IL-1beta, TNF-alpha, GATA-4 and NF-κB expression [29]. Curcumin has been shown to support healthy anti-inflammatory response. Studies show both compounds are effective in protecting the body from damage due to environmental toxins and for dampening NF-κB activation and inflammation [30-32].

Glutathione and Chemical Tolerance Glutathione serves as key antioxidant to protect cells from environmental toxicants and pollutants by converting from reduced glutathione (GSH) to oxidized glutathione (GSSG), but even before the oxidation of glutathione occurs at the cellular level, glutathione is also involved with quenching oxidative stress occurring at our immune barrier to limit external chemical haptens exposure to our internal physiology [33]. Glutathione also supports both Phase I and Phase II hepatic biotransformation systems necessary for hepatic metabolic clearance of toxic metabolites [34]. Each of these mechanisms of glutathione protect us from toxicant induced neurological disease and neurological autoimmune disease to some degree and research has found that loss of chemical tolerance or autoimmunity may be kept in check at various levels by the pleiotropic impacts of glutathione [35,36]. GSH depletion is associated with environmental-induced inflammatory reactions. Researchers are now finding that environmental pollutants do not trigger an immune response until glutathione levels are depleted [37-39]. Continued oxidative stress from chemicals, immune-reactive proteins, and infections all deplete the glutathione protective system at our barriers. However, when glutathione becomes depleted there is no protection for the barrier system and free radicals can readily destroy them leading to exposure of chemicals and large particles to the underlying immune cells of the barrier system. This can lead to exaggerated inflammatory responses and be participating in a vicious cycle in those that suffer from chronic loss of immune tolerance integrity [40-45]. Glutathione doesn’t just protect cells from chemical oxidants is also possess natural chelation properties that allow the tripeptide to bind to environmental compounds and help remove them from the body without displacing them into other tissues, such as the brain that occurs with chelator [4650]. Numerous botanicals have been found to support glutathione levels in our body from various mechanisms. N-acetyl-cysteine is a key compound to glutathione activity. It is rapidly metabolized into intracellular glutathione [51-52]. Alpha-lipoic acid directly recycles and extends the metabolic life spans of vitamin C, glutathione, and coenzyme Q10, and it indirectly renews vitamin E, all of

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which support glutathione recycling [53-54]. L-glutamine is important for the generation of glutathione and oral ingestion is transported into the cell, converted to glutamate, and readily available to intracellular glutathione synthesis [55-57]. Selenium is a trace element nutrient that serves as the essential cofactor for the enzyme glutathione peroxidase, which converts GSH to GSSG so glutathione can quench free radicals in order to spare cells [58-60]. Cordyceps has been shown to activate both glutathione and peroxidase synthesis in the body and protect cells by engaging the glutathione enzyme cycle. Cordyceps increases glutathione levels in the cells by 300 percent within minutes [61-62]. Oral ingestion of Centella asiatica rapidly and dramatically increases the activity and amount of glutathione peroxidase and the quantity of glutathione [63]. Milk thistle has been shown to significantly increase glutathione, increase superoxide dismutase activity, and positively influence the ratios of reduced and oxidized glutathione [64,65]. In addition to the Pro-GSH compounds listed above that are useful in supporting glutathione recycling. Glutathione can also be taken directly, but only if it is the S-Acetyl-Glutathione. This form of glutathione has been shown to be efficiently absorbed unlike other versions [66-70].

Toxicants, Chemical Tolerance and Immune Barrier Systems Many of the top ten Unites States list of hazardous substances, established by the Agency for Toxic Substances and Disease Registry, are found in such high levels that the chemicals themselves are leading to continued oxidative stress and breakdown of the barriers. Polychlorinated biphenyls (PCB), listed #4 on the top 10 list of hazardous substances, has been shown to disrupt the blood-brain barrier [71, 72]. Chronic exposure of arsenic in human water has been shown to alter the lung epithelial barrier and restrict wound repair [73]. Pesticides have also been found in food and drinking water and therefore are now considered a major route of exposure to the general population. The organo-photothionates in pesticides have been found to directly cause intestinal tight junction breakdown [74]. Polychlorniated biphenyls commonly found in the environment have also been found to cause alterations in tight junction integrity [75]. Unfortunately, it now appears that because of the commonly found chemicals in our environment, it itself is contributing to breakdown of our barrier system that is in turn leading to loss of chemical tolerance. The blood-brain barrier (BBB) maintains central nervous system homeostasis by preventing entry of substances that may alter or harm neuronal function, and also allows chemicals necessary for brain function to cross. The BBB is a membrane structure composed of endothelial cells surrounded by astrocyte cell projections tightly surrounded in brain capillaries. The BBB was first discovered by bacteriologist Ehrlich in the 19th century while he was performing tissue staining. When he injected animals with staining chemicals, all of the structures in the body would be stained except the brain. When he injected into the central nervous system he found that the stain would not penetrate outside of the central nervous system. These observations led him to conclude that there was a barrier between the central nervous system and the rest of the body. When the electron microscope was invented in the 1960s, the actual BBB membrane could be demonstrated. The structural composition of the BBB easily allows the entry of oxygen, carbon, dioxide, fatty acids, ethanol, and steroid hormones. Certain amino acids and sugars may also cross the BBB necessary for energy metabolism and neurotransmitter synthesis. However, neurotransmitters cannot cross the BBB with the exception of epinephrine and norepinephrine at thin areas of the BBB found in the hypothalamus. The BBB has special sites present with thinner membranes where its permeability is penetrated easier. These are a normal part of the BBB and include three important circumventricular organs, the subfornical organ, the area postrema, and organum vasculosum of the lamina terminalis. These hypothalamic integrative centers are very important for regulating fluid electrolyte balance,


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sodium excretion, blood volume, regulation of vasopressin secretion, and detecting toxins in the blood to induce vomiting [76]. The BBB restricts B cell entry and protects the brain from general infections. Therefore, infections rarely occur in the brain, but when they do occur they are very difficult to manage. In cases of extreme infection, the BBB will lose its membrane integrity and immune cells from the peripheral system such as macrophages and bone marrow-derived progenitor cells will cross into the brain. Once the infection has been managed, the BBB membrane is reestablished [77]. Loss of BBB integrity has been proposed for the etiology of numerous disease processes including meningitis, multiple sclerosis, Alzheimer’s disease, and Parkinson’s disease [78-80]. Loss of BBB integrity may lead to infiltration of environmental compounds (haptens), dietary proteins, or pathogenic organisms (antigens) to expose them to microglia and activate a neuroinflammatory response. The BBB has demonstrated loss of integrity from alcohol exposure [81], stress responses [82], elevated homocysteine [83,84], hyperglycemia [85], prostaglandin imbalances [86], and oxidative stress [87].

Regulatory T-Cells and Chemical Tolerance Regulatory T cells, are a subpopulation of cells that downregulates the immune system, maintains tolerance to self-antigens, and down-regulates autoimmune disease. Regulatory cells are a component of the immune system that suppresses the immune responses of other cells. This is an important "selfcheck" built into the immune system to prevent excessive reactions. Regulatory T cells come in many forms, with the most well understood being those that express CD4, CD25, and Foxp3 (CD4+CD25+ regulatory T cells). These cells are involved in shutting down immune responses after they have successfully eliminated invading organisms and also in preventing autoimmune TH1 and TH2 polar shifts. They play a critical role in both the modulation of autoimmunity and loss of chemical tolerance [88-90]. Regulatory T cell function can be supported with glutathione and vitamin D. When nutritionally supporting loss of chemical intolerance, vitamin D levels should always be addressed. Research shows vitamin D plays a critical role in the development of general tolerance, immune system defense, immune balance (regulatory T-cells) and immune barrier integrity [91-92]. On a 25-hydroxy vitamin D test, it is ideal to see a level no lower than 50 ng/mL. Several nutrients have been shown to support the regulatory T cells, such as vitamin D and glutathione support [93-97].

CONCLUSION Toxicants, environmental pollutants, and inflammatory reactions lead to immune loss of chemical tolerance. Loss of immune chemical tolerance leads to increase oxidative, inflammatory, and immunoreactive responses to vulnerable tissues such as the brain and nervous system thereby promoting neurodevelopment disorders such as autism, neurodegenerative diseases such as Parkinson’s and Alzheimer’s, and neurological autoimmune disorders such as multiple sclerosis. Physiological depletion of glutathione redox systems, wind-up and amplification of NF-kappaB inflammatory expression, immune barrier system breakdown, and regulator T cell dysregulation all play key roles in maintaining healthy immune chemical tolerance. Nutritional strategies that may impact the integrity and the expression of these physiological systems may provide some potential support to address the growing concerns of environmental induced brain disease and neurological autoimmune disorders.

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REFERENCES [1] [2] [3]

[4]

[5] [6] [7]

[8] [9] [10] [11] [12] [13]

[14] [15]

[16]

[17] [18] [19]

Pollard KM, Hultman P, Kono DH. Toxicology of autoimmune diseases. Chem Res Toxicol. 2010 Mar 15;23(3):455-66. Volk HE, Lurmann F, Penfold B, Hertz-Picciotto I, McConnell R. Traffic-related air pollution, particulate matter, and autism. JAMA Psychiatry. 2013 Jan;70(1):71-7. Calderón-Garcidueñas L, Mora-Tiscareño A, Styner M, Gómez-Garza G, Zhu H, Torres-Jardón R, Carlos E, Solorio-López E, Medina-Cortina H, Kavanaugh M,D'Angiulli A. White matter hyperintensities, systemic inflammation, brain growth, and cognitive functions in children exposed to air pollution. J. Alzheimers Dis. 2012;31(1):183-91. Powell JJ, Van de Water J, Gershwin ME. Evidence for the role of environmental agents in the initiation or progression of autoimmune conditions. Environ Health Perspect. 1999 Oct;107 Suppl 5:667-72. Al-Ayadhi LY, Mostafa GA. A lack of association between elevated serum levels of S100B protein and autoimmunity in autistic children. J. Neuroinflammation. 2012 Mar 16;9:54. Miller CS. The compelling anomaly of chemical intolerance. Ann N Y Acad Sci. 2001 Mar;933:1-23. Environmental threats to healthy aging. Stein, J, Schettler, T, Rohrer B, Valenti, M. 2008. Greater Boston Physicians for Social Responsibility and Science and Environmental Health Network. Hartwig M. Immune ageing and Alzheimer's disease. Neuroreport. 1995 Jun 19;6(9):1274-6. Singh VK. Neuroautoimmunity: pathogenic implications for Alzheimer's disease. Gerontology. 1997;43(1-2):79-94. Cranor C. The legal failure to prevent subclinical developmental toxicity. Basic Clin Pharmacol Toxicol. 2008 Feb;102(2):267-73. Houlihan, et al. Body burden: the pollution in newborns. Environmental Working Group. 2005 Jul 14 . Lunder, et al. Toxic fire retardants in human breast milk. Environmental Working Group. 2003 Sept. Gruden MA, Davidova TB, Malisauskas M, Sewell RD, Voskresenskaya NI, WilhelmK, Elistratova EI, Sherstnev VV, Morozova-Roche LA. Differential neuroimmune markers to the onset of Alzheimer's disease neurodegeneration and dementia: autoantibodies to Abeta ((25-35)) oligomers, S100b and neurotransmitters. J. Neuroimmunol. 2007 May;186(1-2):181-92. Lal H, Forster MJ. Autoimmunity and age-associated cognitive decline. Neurobiol Aging. 1988 Sep-Dec;9(5-6):733-42. Benkler M, Agmon-Levin N, Hassin-Baer S, Cohen OS, Ortega-Hernandez OD, Levy A, Moscavitch SD, Szyper-Kravitz M, Damianovich M, Blank M, Chapman J, Shoenfeld Y. Immunology, autoimmunity, and autoantibodies in Parkinson's disease. Clin. Rev Allergy Immunol. 2012 Apr;42(2):164-71. Glauert HP, Tharappel JC, Lu Z, Stemm D, Banerjee S, Chan LS, Lee EY, Lehmler HJ, Robertson LW, Spear BT. Role of oxidative stress in the promoting activities of pcbs. Environ Toxicol Pharmacol. 2008 Mar;25(2):247-50. Kimura K, Teranishi S, Nishida T. Interleukin-1beta-induced disruption of barrier function in cultured human corneal epithelial cells. Invest OphthalmolVis Sci. 2009 Feb;50(2):597-603. Al-Sadi RM, Ma TY. IL-1beta causes an increase in intestinal epithelial tight junction permeability. J. Immunol. 2007 Apr 1;178(7):4641-9. Wahli W. A gut feeling of the PXR, PPAR and NF-kappaB connection. J. Intern Med. 2008 Jun;263(6):613-9.


209

[20] Xie W, Tian Y. Xenobiotic receptor meets NF-kappaB, a collision in the small bowel. Cell Metab. 2006 Sep;4(3):177-8. [21] Pascussi JM, Vilarem MJ. [[Inflammation and drug metabolism: NF-kappB and the CAR and PXR xeno-receptors]. Med. Sci (Paris). 2008 Mar;24(3):301-5. [22] Assenat E, Gerbal-Chaloin S, Larrey D, Saric J, Fabre JM, Maurel P, Vilarem MJ, Pascussi JM. Interleukin 1beta inhibits CAR-induced expression of hepatic genes involved in drug and bilirubin clearance. Hepatology. 2004Oct;40(4):951-60. [23] Ke S, Rabson AB, Germino JF, Gallo MA, Tian Y. Mechanism of suppression of cytochrome P450 1A1 expression by tumor necrosis factor-alpha and lipopolysaccharide. J. Biol Chem. 2001 Oct 26;276(43):39638-44. [24] Barnes PJ, Karin M. Nuclear factor-kappaB: a pivotal transcription factor in chronic inflammatory diseases. N. Engl J. Med. 1997 Apr 10;336(15):1066-71. [25] [25] Ellrichmann G, Thöne J, Lee DH, Rupec RA, Gold R, Linker RA. Constitutive activity of NF-kappa B in myeloid cells drives pathogenicity of monocytes and macrophages during autoimmune neuroinflammation. J. Neuroinflammation. 2012 Jan 20;9:15. [26] Bisht K, Wagner KH, Bulmer AC. Curcumin, resveratrol and flavonoids as anti-inflammatory, cyto- and DNA-protective dietary compounds. Toxicology. 2010 Nov 28;278(1):88-100. [27] Buhrmann C, Mobasheri A, Busch F, Aldinger C, Stahlmann R, Montaseri A, Shakibaei M. Curcumin modulates nuclear factor kappaB (NF-kappaB)-mediatedinflammation in human tenocytes in vitro: role of the phosphatidylinositol 3-kinase/Akt pathway. J. Biol. Chem. 2011 Aug 12;286(32):28556-66. [28] Revel A, Raanani H, Younglai E, Xu J, Han R, Savouret JF, Casper RF. Resveratrol, a natural aryl hydrocarbon receptor antagonist, protects sperm from DNA damage and apoptosis caused by benzo(a)pyrene. Reprod Toxicol. 2001 Sep-Oct;15(5):479-86. [29] Aktas C, Kanter M, Erboga M, Ozturk S. Anti-apoptotic effects of curcumin on cadmiuminduced apoptosis in rat testes. Toxicol Ind Health. 2012 Mar;28(2):122-30. [30] Roy M, Sinha D, Mukherjee S, Biswas J. Curcumin prevents DNA damage and enhances the repair potential in a chronically arsenic-exposed human population in West Bengal, India. Eur. J. Cancer Prev. 2011 Mar;20(2):123-31. [31] Ahmed T, Pathak R, Mustafa MD, Kar R, Tripathi AK, Ahmed RS, Banerjee BD. Ameliorating effect of N-acetylcysteine and curcumin on pesticide-induced oxidative DNA damage in human peripheral blood mononuclear cells. Environ Monit Assess. 2011 Aug;179(1-4):293-9. [32] Gradisar H, Keber MM, Pristovsek P, Jerala R. MD-2 as the target of curcumin in the inhibition of response to LPS. J. Leukoc Biol. 2007 Oct;82(4):968-74. [33] Maeda T, Miyazono Y, Ito K, Hamada K, Sekine S, Horie T. Oxidative stress and enhanced paracellular permeability in the small intestine of methotrexate-treated rats. Cancer Chemother Pharmacol. 2010 May;65(6):1117-23. [34] Kwon DY, Jung YS, Kim SJ, Kim YS, Choi DW, Kim YC. Alterations in Sulfur Amino Acid Metabolism in Mice Treated with Silymarin: A Novel Mechanism of Its Action Involved in Enhancement of the Antioxidant Defense in Liver. Planta Med. 2013 Jun 27. [35] Zhang D, Shen J, Wang C, Zhang X, Chen J. GSH-dependent iNOS and HO-1 mediatedapoptosis of human Jurkat cells induced by nickel(II). Environ Toxicol. 2009 Aug;24(4):404-14. [36] Tada-Oikawa S, Kato T, Kuribayashi K, Nishino K, Murata M, Kawanishi S. Critical role of hydrogen peroxide in the differential susceptibility of Th1 and Th2 cells to tributyltin-induced apoptosis. Biochem Pharmacol. 2008 Jan15;75(2):552-61. [37] Fraternale A, Crinelli R, Casabianca A, Paoletti MF, Orlandi C, Carloni E, Smietana M, Palamara AT, Magnani M. Molecules Altering the Intracellular Thiol Content Modulate NF-κB

210

[38] [39]

[40]

[41]

[42]

[43] [44]

[45]

[46] [47] [48] [49] [50] [51]

[52]

[53] [54]

[55]

Datis Kharrazian and STAT-1/IRF-1 Signalling Pathways and IL-12 p40 and IL-27 p28 Production in Murine Macrophages. PLoS One. 2013;8(3):e57866. Gosset P, Wallaert B, Tonnel AB, Fourneau C. Thiol regulation of the production of TNF-alpha, IL-6 and IL-8 by human alveolar macrophages. Eur. Respir J. 1999 Jul;14(1):98-105. Tada-Oikawa S, Kato T, Kuribayashi K, Nishino K, Murata M, Kawanishi S. Critical role of hydrogen peroxide in the differential susceptibility of Th1 and Th2 cells to tributyltin-induced apoptosis. Biochem Pharmacol. 2008 Jan 15;75(2):552-61. van Ampting MT, Schonewille AJ, Vink C, Brummer RJ, van der Meer R, Bovee-Oudenhoven IM. Intestinal barrier function in response to abundant or depleted mucosal glutathione in Salmonella-infected rats. BMC Physiol. 2009 Apr 17;9:6. doi: 10.1186/1472-6793-9-6. Kelly N, Friend K, Boyle P, Zhang XR, Wong C, Hackam DJ, Zamora R, Ford HR, Upperman JS. The role of the glutathione antioxidant system in gut barrier failure in a rodent model of experimental necrotizing enterocolitis. Surgery. 2004 Sep;136(3):557-66. Wu J, Ji H, Wang YY, Wang Y, Li YQ, Li WG, Long Y, Xia YZ, Hong H. Glutathione depletion upregulates P-glycoprotein expression at the blood-brain barrier inrats. J. Pharm Pharmacol. 2009 Jun;61(6):819-24. Agarwal R, Shukla GS. Potential role of cerebral glutathione in the maintenance of blood-brain barrier integrity in rat. Neurochem Res. 1999 Dec;24(12):1507-14. Shukla A, Shukla GS, Srimal RC. Cadmium-induced alterations in blood-brain barrier permeability and its possible correlation with decreased microvessel antioxidant potential in rat. Hum Exp Toxicol. 1996 May;15(5):400-5. Schweitzer KS, Hatoum H, Brown MB, Gupta M, Justice MJ, Beteck B, Van DemarkM, Gu Y, Presson RG Jr, Hubbard WC, Petrache I. Mechanisms of lung endothelial barrier disruption induced by cigarette smoke: role of oxidative stress andceramides. Am. J. Physiol. Lung Cell Mol Physiol. 2011 Dec;301(6):L836-46. Chelation in metal intoxication. Int. J. Environ Res. Public Health. 2010 Jul:7(7):2745-2788. Andersen O. Principles and recent developments in chelation treatment of metalintoxication. Chem. Rev. 1999 Sep 8;99(9):2683-710. Andersen O. Chemical and biological considerations in the treatment of metal intoxications by chelating agents. Mini Rev. Med. Chem. 2004 Jan;4(1):11-21. Ewan ΚB, Pamphlett R. Increased inorganic mercury in spinal motor neurons following chelating agents. Neurotoxicology. 1996 Summer;17(2):343-9. Ibim SE, Trotman J, Musey PI, Semafuko WE. Depletion of essential elements by calcium disodium EDTA treatment in the dog. Toxicology. 1992;73(2):229-37. Badaloo A, Reid M, Forrester T, Heird WC, Jahoor F. Cysteine supplementation improves the erythrocyte glutathione synthesis rate in children with severe edematous malnutrition. Am. J. Clin. Nutr. 2002 Sep;76(3):646-52. Odom RY, Dansby MY, Rollins-Hairston AM, Jackson KM, Kirlin WG. Phytochemical induction of cell cycle arrest by glutathione oxidation and reversal by N-acetylcysteine in human colon carcinoma cells. Nutr. Cancer. 2009;61(3):332-9. Marsh SA, Laursen PB, Coombes JS. Effects of antioxidant supplementation an exercise training on erythrocyte antioxidant enzymes. Int. J. Vitam Nutr Res. 2006 Sep;76(5):324-31. Zicker SC, Hagen TM, Joisher N, Golder C, Joshi DK, Miller EP. Safety of long-term feeding of dl-alpha-lipoic acid and its effect on reduced glutathione:oxidized glutathione ratios in beagles. Vet Ther. 2002 Summer;3(2):167-76. Cruzat VF, Tirapegui J. Effects of oral supplementation with glutamine and alanyl-glutamine on glutamine, glutamate, and glutathione status in trained rats and subjected to long-duration exercise. Nutrition. 2009 Apr;25(4):428-35.


211

[56] Mok E, Constantin B, Favreau F, Neveux N, Magaud C, Delwail A, Hankard R. l-Glutamine administration reduces oxidized glutathione and MAP kinase signaling in dystrophic muscle of mdx mice. Pediatr Res. 2008 Mar;63(3):268-73. [57] Johnson AT, Kaufmann YC, Luo S, Todorova V, Klimberg VS. Effect of glutamine on glutathione, IGF-I, and TGF-beta 1. J. Surg Res. 2003 May 15;111(2):222-8. [58] Bartfay WJ, Bartfay E. Selenium and glutathione peroxidase with beta-thalassemia major. Nurs Res. 2001 May-Jun;50(3):178-83. [59] Zachara BA, Mikolajczak J, Trafikowska U. Effect of various dietary selenium (Se) intakes on tissue Se levels and glutathione peroxidase activities in lambs. Zentralbl Veterinarmed A. 1993 May;40(4):310-8. [60] Wilke BC, Vidailhet M, Favier A, Guillemin C, Ducros V, Arnaud J, Richard MJ. Selenium, glutathione peroxidase (GSH-Px) and lipid peroxidation products before and after selenium supplementation. Clin. Chim Acta. 1992 Apr 30;207(1-2):137-42. [61] Ji DB, Ye J, Li CL, Wang YH, Zhao J, Cai SQ. Antiaging effect of Cordyceps sinensis extract. Phytother Res. 2009 Jan;23(1):116-22. [62] Wang YH, Ye J, Li CL, Cai SQ, Ishizaki M, Katada M. [An experimental study on anti-aging action of Cordyceps extract]. Zhongguo Zhong Yao Za Zhi. 2004 Aug;29(8):773-6. [63] Lee MK, Kim SR, Sung SH, Lim D, Kim H, Choi H, Park HK, Je S, Ki YC. Asiatic acid derivatives protect cultured cortical neurons from glutamate-induced excitotoxicity. Res. Commun Mol. Pathol Pharmacol. 2000 Jul-Aug;108(1-2):75-86. [64] Pradhan SC, Girish C. Hepatoprotective herbal drug, silymarin from experimental pharmacology to clinical medicine. Indian J. Med. Res. 2006 Nov;124(5):491-504. [65] Valenzuela A, Aspillaga M, Vial S, Guerra R. Selectivity of silymarin on the increase of the glutathione content in different tissues of the rat. Planta Med. 1989 Oct;55(5):420-2. [66] Witschi A, Reddy S, Stofer B, Lauterburg BH. The systemic availability of oral glutathione. Eur. J. Clin. Pharmacol. 1992;43(6):667-9. [67] Hagen TM, Wierzbicka GT, Sillau AH, Bowman BB, Jones DP. Bioavailability of dietary glutathione: effect on plasma concentration. Am. J. Physiol. 1990 Oct;259(4 Pt 1):G524-9. [68] Cacciatore I, Cornacchia C, Mollica A, Pinnen F, Di Stefano A. Prodrug Approach for Increasing Cellular Glutathione Levels. Molecule. 3 March 2010. [69] Vogel JU, Cinatl J, Dauletbaev N, Buxbaum S, Treusch G, Cinatl J Jr, Gerein V, Doerr HW. Effects of S-acetylglutathione in cell and animal model of herpes simplex virus type 1 infection. Med. Microbiol Immunol. 2005 Jan;194(1-2):55-9. [70] Ballatori N, Krance SM, Notenboom S, Shi S, Tieu K, Hammond CL. Glutathione dysregulation and the etiology and progression of human diseases. Biol. Chem. 2009 Mar;390(3):191-214. [71] Seelbach M, Chen L, Powell A, Choi YJ, Zhang B, Hennig B, Toborek M.Polychlorinated biphenyls disrupt blood-brain barrier integrity and promote brain metastasis formation. Environ Health Perspect. 2010 Apr;118(4):479-84. [72] Choi JJ, Choi YJ, Chen L, Zhang B, Eum SY, Abreu MT, Toborek M. Lipopolysaccharide potentiates polychlorinated biphenyl-induced disruption of the blood-brain barrier via TLR4/IRF-3 signaling. Toxicology. 2012 Dec 16;302(2-3):212-20. [73] Olsen CE, Liguori AE, Zong Y, Lantz RC, Burgess JL, Boitano S. Arsenic upregulates MMP-9 and inhibits wound repair in human airway epithelial cells. Am. J. Physiol Lung Cell Mol Physiol. 2008 Aug;295(2):L293-302. [74] Tirelli V, Catone T, Turco L, Di Consiglio E, Testai E, De Angelis I. Effects of the pesticide clorpyrifos on an in vitro model of intestinal barrier. Toxicol In Vitro. 2007 Mar;21(2):308-13.

212

Datis Kharrazian

[75] Choi YJ, Seelbach MJ, Pu H, Eum SY, Chen L, Zhang B, Hennig B, Toborek M. Polychlorinated biphenyls disrupt intestinal integrity via NADPH oxidase-induced alterations of tight junction protein expression. Environ Health Perspect. 2010 Jul;118(7):976-81. [76] Amadur, Doull, Klaassen (1991). Casarett and Doull’s Toxicology; The Basic Science of Poisons 4th ed. [77] Gehrmann J. Microglia: a sensor to threats in the nervous system? Research in Virology. 1996:147:79-88. [78] Blood-brain-barrier flux of aluminum, manganese, iron and other metals suspected to contribute to metal-induced neurodegeneration. J. Alzhemimers Dis. 2006;10(2-3):223-53. [79] Molecular mechanism of distorted iron regulation in blood-CSF barrier and regional blood brain barrier following in vivo subchronic manganese exposure. Neurotoxicology. 2006; 27(5):73744. [80] Nanoparticle iron chelators: a new therapeutic approach in Alzheimer disease and other neurologic disorders associated with trace metal imbalances. Neurosci Lett. 2006;406(3):18993. [81] Haorah J, Knipe B, Leibhart J, Ghorpade A, Persidsky Y. Alcohol-induced oxidative stress in brain endothelial cells causes blood-brain-barrier dysfunction. Journal of Leukocyte Biology. 2005.;78:1223-1232. [82] Espositie, P, Gheorghe D, Kandere K, Pang X, Connolly R, Jacobson S, Theoharides TC. Acute stress increases permeability of the blood-brain-barrier through activation of brain mast cells. Brain Research. 2001;888(1):117-127. [83] Atul F, Chauhan AK, Kisucka J, Dole VS, Loscalzo J, Handy DE, Wagner DD. Elevated levels of homocysteine compromise blood-brain-barrier integrity in mice. Blood. 2005. [84] Homocysteine attenuates blood brain barrier function by inducing oxidative stress and the junctional proteins. FASEB. 2008;22:734-7. [85] Kamada H, Yu F, Nito C, Chan PH. Influence of hyperglycemia on oxidative stress and matrix metalloproteinase-9 activation after focal cerebral ischemia/reperfusion in rats. Stroke. 2007;38:1044-1049. [86] Jali C, Taheri S, Yang Y, Sood R, Grossetete M, Estrada EY, Fiebich BL, Rosenberg GA. Cyclooxygenase inhibition limits blood-brain-barrier disruption following intracerebral injection of tumor necrosis factor-alpha in the rat. JPET. 2007;323(2):488-498. [87] Haroh J, Ramirez SH, Schall K, Smith D, Pandya R, Persidsky Y. Oxidative stress activates protein tyrosine kinase and matrix metalloproteinases leading to blood-brain barrier dysfunction. J. Neurochem. 2007;22(1). [88] Graham JG, Zhang X, Goodman A, Pothoven K, Houlihan J, Gower RM, Wang S, LuoX, Shea LD. PLG Scaffold Delivered Antigen-Specific Regulatory T cells Induce Systemic Tolerance in Autoimmune Diabetes. Tissue Eng Part A. 2013 Feb 23. [89] Gonzalez-Rey E. Keeping the balance between immune tolerance and pathogen immunity with endogenous neuropeptides. Neuroimmunomodulation. 2010;17(3):161-4. [90] Tada-Oikawa S, Murata M, Kato T. [Preferential induction of apoptosis in regulatory T cells by tributyltin: possible involvement in the exacerbation of allergic diseases]. Nihon Eiseigaku Zasshi. 2010 Sep;65(4):530-5. [91] Vassallo MF, Camargo CA Jr. Potential mechanisms for the hypothesized link between sunshine, vitamin D, and food allergy in children. J. Allergy Clin Immunol. 2010 Aug;126(2):217-22. [92] Kong J, Zhang Z, Musch MW, Ning G, Sun J, Hart J, Bissonnette M, Li YC. Novel role of the vitamin D receptor in maintaining the integrity of the intestinal mucosal barrier. Am. J. Physiol Gastrointest Liver Physiol. 2008 Jan;294(1):G208-16.


213

[93] Bock G, Prietl B, Mader JK, Höller E, Wolf M, Pilz S, Graninger WB, Obermayer-Pietsch BM, Pieber TR. The effect of vitamin D supplementation on peripheral regulatory T cells and β cell function in healthy humans: a randomized controlled trial. Diabetes Metab Res Rev. 2011 Nov;27(8):942-5. [94] Kleijwegt FS, Laban S, Duinkerken G, Joosten AM, Koeleman BP, Nikolic T, Roep BO. Transfer of regulatory properties from tolerogenic to proinflammatory dendritic cells via induced autoreactive regulatory T cells. J. Immunol. 2011 Dec 15;187(12):6357-64. [95] Hewison M. Vitamin D and immune function: an overview. Proc. Nutr. Soc. 2012 Feb;71(1):50-61. Epub 2011 Aug 18. [96] Yan Z, Garg SK, Banerjee R. Regulatory T cells interfere with glutathione metabolism in dendritic cells and T cells. J. Biol. Chem. 2010 Dec 31;285(53):41525-32. [97] Tada-Oikawa S, Murata M, Kato T. [Preferential induction of apoptosis in regulatory T cells by tributyltin: possible involvement in the exacerbation ofallergic diseases]. Nihon Eiseigaku Zasshi. 2010 Sep;65(4):530-5.

Received: July 1 2013 Revised: July 3 2013 Accepted: July 7 2013



THE POTENTIAL IMPACT OF VARIOUS PHYSIOLOGICAL MECHANISMS ON OUTCOMES IN TBI, MTBI, CONCUSSION AND PPCS Joel Brandon Brock1,2,4, Samuel Yanuck3,4, Michael Pierce1,5, Michael Powell2,6, Steven Geanopulos7, Steven Noseworthy8, Datis Kharrazian9, Chris Turnpaugh3,11, Albert Comey1,12, and Glen Zielinski2,3,13 1

Carrick Institute for Graduate Studies, Cape Canaveral, FL USA 2 F. R. Carrick Institute for Clinical Ergonomics, Rehabilitation and Applied Neurosciences, Garden City, NY USA 3 The Yanuck Center, Chapel Hill, NC USA 4 Cogence, LLC, Chapel Hill, NC USA 5 Integrated Health Systems, Denver, CO USA 6 Powell Chiropractic Clinic, Cedar Rapids, IO USA 7 New Heights Integrated Health, New York, NY USA 8 Essential Medicine, Lakewood Ranch, Florida USA 9 Bastyr University, San Diego, CA USA 11 Brain Balance Center of Mechanicsburg, Mechanicsburg, PA, USA 12 Comey Chiropractic Clinic, Largo, FL USA 13 Northwest Functional Neurology, Lake Oswega, OR USA

ABSTRACT The need for effective clinical interventions in chronic neurological diseases such as TBI and other variants of chronic neurological conditions have been called for in the literature. The cellular and neurochemical mechanisms addressed in recent literature have focused around three common themes that traverse all of these condition classes: immune and autoimmune mechanisms, inflammatory pathways and oxidative phosphorylation or other energy production damage. Limits to the effectiveness of pharmaceutical and surgical approaches are apparent, and complicated by the physiological interconnectedness of such pathways. A growing call for non-drug, non-surgical options has evolved due to the dangers of poly-pharmacy, the lifestyle illnesses, and emerging evidence pointing to functional measures and methods. This paper surveys and links selected studies of specific, measurable effects of brain injury on several body systems, and it indicates an emerging path toward outcome-based multifactorial functional neurological assessment and treatment of some of the sequelae of chronic TBI and mTBI) (mild traumatic brain injury).

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Correspondence: Dr. J. Brandon Brock, 105 Decker Court, Suite 120 Irving, TX 75062 E-mail: [email protected].

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Joel Brandon Brock, Samuel Yanuck, Michael Pierce et al.

Keywords: Concussion, TBI, mTBI, autoimmune, inflammatory pathways, neuroinflammation, neurodegeneration, neuropsychological, neuroendocrine, vestibular

INTRODUCTION While many people recover from common brain injuries during the first year of recovery, those who are left with chronic problems have been told to accept their fate according to the dogma of permanence. Brain plasticity research has brought this notion under scrutiny. Studies on the neurochemistry and sensorimotor consequences of chronic brain injury have revealed wide ranging and cross-disciplinary mechanisms. These measurable phenomena have increased the understanding of both pathological and dysfunctional syndromes within this category of illness. An increasing need for strong generalist thinking is therefore demanded in order to comprehend and utilize this bounty, and to avoid the traps of heuristic decision making and specialist-dumping in a clinical setting. Careful examination of many wide-ranging patient measures must be integrated in order to progress, such as reflexive eye movements, hormone panels, sensorimotor changes, immune and inflammatory markers, and mental and emotional states. History taking will need to expand to include lifestyle factors previously thought unrelated. The compartmentalization of diagnosis and treatment and the wanton medication of these populations of chronic brain injury may not be their only fate. Part I of this paper will survey mechanisms that span much of the above chronic neurological illness spectrum; first, through intracellular, and then, endocrine and tissue effects. This includes the underlying milieu prior to the injury, neurochemistry and receptors, fuel, immunity and inflammation, barriers, and endocrine effects. The CDC defines concussion as a subset within TBI and many sources consider it a form of mTBI (mild traumatic brain injury). There are several criteria for mTBI and concussion, so the reader is warned that each reference may define these with slightly different symptoms. Part II includes trauma effects, clinical neurological rehabilitation applications and mental health related to persistent post-concussion syndrome (PPCS).

PART I: MOLECULAR, RECEPTOR, SECRETORY AND CELLULAR DYNAMICS Adding Insult to Injury: Non-Traumatic Brain Insults in the Total Picture of TBI and mTBI Accumulated neuroinflammation and neurodegeneration from multiple concussions cause deleterious effects that are well established. The fact that non-traumatic mechanisms can create proinflammatory influences on the brain that influence the same cellular signaling mechanisms to those seen with trauma suggests that, in order to understand the total burden of brain pathology in a given patient, both traumatic (injury) and non-traumatic (insult) sources, and their interactions, must be considered. Non-traumatic sources of brain insult may be instigators of microglial priming in advance of TBI or mTBI, therefore worsening TBI or mTBI outcome.

The Potential Impact of Various Physiological Mechanisms …

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Figure 1. Chronic TBI sequelae © Samuel Yanuck 2013.

Neuron-Microglial Interactions in the Healthy Brain In the adult brain, there is a decline in gray matter density over time. For example, Sowell et al found a loss of gray matter density of approximately 32% between ages 7 and 60, and a 5% loss between 40 and 87 [186].. Thus neurons die every day. They need to be cleared, or they will drive damage associated molecular pattern (DAMP) mediated immune system activation, instigating a proinflammatory response in the brain [3,187]. Microglia are the predominant immune cells in the healthy brain [1]. In the normal, resting state, it is the job of ramified microglia to phagocytize the dead neurons, much like macrophages phagocytize apoptotic cells and tissue debris in peripheral tissues. In both cases, this housekeeping level of phagocytic activity drives the creation of anti-inflammatory mediators like IL-10 and TGFβ. Phagocytosis of apoptotic cells provides immune regulation through anti-inflammatory cytokines and regulatory T cells [2] However, since there is no appreciable drainage of lymph from the brain, except minimally at the cribriform plate, the option of clearing phagocytized debris from tissue via the lymph system, as occurs in the periphery, is not available in the brain. Therefore, microglia must fully degrade dead neurons and recycle them as building blocks and fuel. Given billions of neurons and an estimated ten microglia per neuron, and given a motif of continuous surveillance, the number of instantaneous events of microglial cells being activated or inhibited in the decision flow to instigate phagocytosis of a neuron is very large indeed. How do the microglia decide which neurons are dead? How is this process between microglia and neurons regulated in non-neutral circumstances like trauma, infection, inflammation, or neurodegeneration? Neurons control microglial activity [3]. ‘Off’ signals from neurons keep microglia in their resting state and reduce pro-inflammatory activity, while ‘On’ signals from neurons are inducible, including

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purines, chemokines, and glutamate. Thus, neurons should be envisaged as key immune modulators in the brain [3] Table 1. Inhibition of Glial Phagocytosis of Neurons (“OFF” Signals) [3] OFF Signals Released

Signal TGFβ CD22 CX3CL1 Neurotransmitters NGF BDNF NT-3 CD200 CD22 CD47 CX3CL1

Membrane Bound

Effect Inhibition of effector T cells; Promotion of immune tolerance & inflammatory resolution; loss of anti-pathogenic vigilance Inhibition of B cell activity Inhibition of microglial neurotoxicity Multiple functions Nerve growth factor Brain derived neurotrophic factor Neurotrophin-3 Inhibition of glial inflammation Inhibition of B cell activity Inhibition of glial inflammation Inhibition of microglial neurotoxicity

Table 2. Activation of Glial Phagocytosis of Neurons (“ON” Signals) [3] ON Signals Released

Signal CCL21 CXCL10 ATP & UTP Glutamate MMP3

Membrane Bound

TREM2 ligand

Effect Glial chemoattraction Glial chemoattraction Glial chemoattraction & IL-1beta release TNF-alpha release & neuroexcitotoxicity Induces glial release of TNF-alpha, IL-1beta, IL-6 (inflammatory) Promotes glial phagocytosis of neurons

In a healthy brain, the interplay of neurons and microglia is balanced. Healthy, viable neurons produce adequate OFF signals to repel microglial phagocytic interest. In addition, healthy neurons produce abundant electrical activity. The electrical activity of neurons is itself a potent inhibitor of microglial activation [4]. In the healthy, non-inflamed brain, ramified microglia secrete TGFbeta, which promotes a tolerogenic and anti-inflammatory tissue environment [5]. In addition, in a healthy brain, microglia and astrocytes express FasL, which induces apoptosis in T cells that migrate from the periphery into the brain [6]. Neurons and glia express cellular death signals, including CD95Fas/CD95L, FasL, tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) and TNF receptor (TNFR), through which they can trigger apoptosis in T cells and other infiltrating cells [2].

Factors Affecting Neuronal-Microglial ‘On’ or ‘Off’ Signaling The capacity of neurons to maintain robust frequency of firing (FOF) is essential for sustained electrical activity and neurotransmitter (NT) output, two essential ‘OFF’ signals. The central integrative state (CIS) of the neuron depends on presynaptic stimulation, neuronal oxygen and neuronal glucose. Physiological factors that have the capacity to impair these three factors can contribute to changes in neuronal FOF, thereby changing the neuron-microglial ON/OFF equation.


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The capacity of neurons to maintain robust FOF also depends on the metabolic integrity of the neurons themselves. A host of factors contribute to neuronal metabolic integrity. Among the variables that can perturb function and lead to diminished FOF are a lack of exercise, excessive accumulation of mitochondrial ROS, diminished thyroid hormone signaling, and CoQ10 deficiency (statin-induced or other). The accumulation of ROS in mitochondria depends on the balance between electron accumulation from excessive caloric consumption versus the utilization of electrons via exercise. Too much caloric intake combined with a lack of exercise yields an overabundance of electrons (general biology). They react with oxygen, creating superoxide. If this occurs in amount in excess of what can be cleared by mitochondrial antioxidant mechanisms, the mitochondria are damaged. Mitochondrial damage from ROS may be more common in patients with single nucleotide polymorphisms (snips) for glutathione or SOD. Approximately half the population has a snip for GSTM-1, the primary gene for the production of glutathione s-transferase) [188]. Sensory stimulation factors like lack of exercise, destruction of joint mechanoreceptors in arthritic conditions, poor muscular tone, diminished rib movement with respiratory disorders and other such changes can alter the neurosensory environment. Glycemic dysregulation in diabetes, hypoglycemia, insulin resistance and other such conditions can impair systemic and consequently CNS glucose levels. Many of these patients have microcirculatory problems exacerbating inadequate blood glucose levels with poor delivery to brain. Likewise, CNS oxygen levels can be impaired by respiratory disorders, disorders of microcirculation and other such problems.

Figure 2. Factors Potentially Affecting the Neuron-Microglial ON/OFF Equation © Samuel Yanuck 2013.

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Clearance and Inflammation in Injury When the brain is injured, however, the resulting inflammatory chemistry can change the equation. With inflammation, neurons and microglia both change in ways that promote microglial phagocytosis of neurons. As with any cell, inflammation compromises metabolic integrity. In neurons, this yields diminished production of neurotransmitters and reduced electrical activity. Thus, two potent “Off” signals are lost. Meanwhile, inflamed microglia change their morphology. Brain inflammation differs from inflammation in the periphery by the relative absence of leukocytes and antibodies. There is a limited traffic across this barrier and this traffic can be increased by inflammation which can recruit leukocytes into the brain [1]. However, in the inflamed brain, microglia (which are after all a specialized form of macrophage) acquire antigen presenting cell capacity [4]. Instead of inducing apoptosis in invading T cells, inflamed microglia present antigen to invading T cells. Antigenic material can be fragments of processed pathogens. This is a useful antimicrobial effect, favoring clearance of pathogen. However, microglia can also present fragments of neuronal tissue debris as antigen, promoting a self-antigenic response in the T cells to which the antigen is presented. A mild and transient form of this T cell selfantigenic activation appears to be reparative. However, prolonged or overly exuberant self-antigenic T cell activation can cause irreversible damage to brain [4]. It is noteworthy that some of the research in this field occurred before there was a full appreciation of the role of TH17 polarization in T cell/microglial interactions. Inflammation is known to induce mitochondrial uncoupling, diminishing mitochondrial integrity in all cells. Inflammation is therefore also a driver of diminished mitochondrial integrity and FOF of neurons. In a variety of inflammatory and neurodegenerative diseases, glial cells such as microglia gain antigen-presenting capacity through the expression of MHC molecules. The pro-inflammatory cytokines stimulate microglial MHC expression in the lesioned CNS areas only [4]. Neuronal signaling, a strong “Off” signal, works to suppress the immune system’s inflammatory activation in the brain so that induction of brain immunity is strongly counterregulated in intact CNS areas. The signaling activity of neurons also constitutes an inhibitory signal. The control of MHC expression by neurons is dependent on their electrical activity. Immunity in the CNS is inhibited by the local microenvironment, in particular by physiologically active neurons, to prevent unwanted immune mediated damage of neurons [4] (emphasis not original). Research on the role of T cells and peripheral innate immune cells in the brain is evolving. Most authors suggest that maintenance of the non-inflamed CNS environment depends on the ability of microglial cells to induce apoptosis in peripheral T cells that gain access to the brain. However, the failure of systemic anti-inflammatory medications to yield improvement in neuroinflammatory disorders has led some authors to a view that CNS-infiltrating T cells provide crucial antiinflammatory cytokine signals that are essential for the resolution of neuroinflammation [7]. It is noteworthy that non-steroidal, anti-inflammatory medications have been described in the literature as “resolution toxic” because they inhibit signaling mechanisms involved in the resolution of inflammation [8]. This insight may prove useful in understanding the failure of anti-inflammatories as a viable therapy to address chronic neuroinflammation. In the presence of systemic inflammation, T cells invading the CNS are likely to be influenced by pro-inflammatory cytokines and other factors into a pro-inflammatory morphology, as they are in the periphery. Once so influenced, they are likely to produce pro-inflammatory cytokines, further promoting the pro-inflammatory CNS environment. Pathogens in tissue create pathogen associated molecular patterns (PAMPs). Damaged tissue creates damage associated molecular patterns (DAMPs). Microglial pattern recognition receptors (PRRs) sense PAMPs and DAMPs, triggering phagocyte NADPH oxidase (PHOX), which turns


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molecular oxygen into reactive oxygen species (ROS). This conversion depletes the tissue of molecular oxygen, yielding hypoxia, driving hypoxia inducible factor 1α (HIF-1α), driving NF-κB, driving IL-1beta and TNF-alpha, which increase gene expression of NF-κB. NF-κB drives iNOS (inducible nitric oxide synthase) expression. Though nitric oxide (NO) is cytoprotective, the combination of NO and hypoxia impair cellular respiration, yielding excitotoxicity. Though balanced amounts of ROS are normal to microglial function, ROS in combination with NO yields peroxynitrite, driving neuronal apoptosis. In patients with antioxidant depletion, from glutathione (gsh) snips or other factors, the likelihood of microglia producing neurotoxic amounts of ROS is increased.

Figure 3. Factors Contributing to Perpetuation or Resolution of Neuroinflammation [11] © Samuel Yanuck 2013.

Microglial Priming and the Contribution of Non-Traumatic Influences to Neuroinflammation Microglial priming is a condition in which microglia move from the ramified state in which they perform housekeeping functions and reduce neuro-inflammation to a state in which they swell and fill with pro-inflammatory cytokines [9,10,11,12] Priming can be induced by aging, trauma, infection, or other stimuli. Microglia can remain in this state for long periods of time, without returning to the ramified state, but without releasing their bolus of cytokines. However, further insult to the brain will cause a flooding release of pro-inflammatory cytokines that can be damaging to the brain [9,10,11,12]. It has been established that increases in pro-inflammatory cytokines in the periphery yield upregulation of brain inflammation and potentiate neuronal death [13,14] It has also been shown that increasing the peripheral LPS (lipopolysaccharide) level can induce the activation of central proinflammatory mechanisms, even when the amount of LPS used for stimulation is minimal or when the peripheral inflammatory cytokine levels are suppressed artificially. Both central and peripheral inflammation can exacerbate local brain inflammation and neuronal death [15]. Once neuroinflammation occurs, the key question is whether it will resolve quickly or yield a chronically activated state, in which greater neuronal loss occurs. Microglia alter their morphology and activate in response to pathophysiological brain insults. Microglial phenotype is also modified by systemic infection or inflammation. Chronic systemic inflammatory components are risk factors for Alzheimer disease. This implies that crosstalk occurs between systemic inflammation and microglia in the CNS [16]. Pathogens, protein aggregates, or damaged neurons may inflammatorily activate glia, which may then kill neurons. IL-1b has been

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shown to be the main activator of microglia during brain disturbances. Systemic IL-1b can cause CNS inflammation once it enters the brain, thus linking systemic inflammation and immune activation [12]. Microglia can become over-activated through two mechanisms. First, microglia can initiate neuron damage by recognizing pro-inflammatory stimuli, such as lipopolysaccharide (LPS)). Second, microglia can become overactivated in response to neuronal damage [11]. LPS can directly activate the brain endothelium even at relatively low doses, obviating the need for systemic cytokine stimulation [9,10]. Many of the pathological events described in traumatic brain injuries can also be seen with excitotoxicity [12]. Receptor stimulation by pathogens or neuron damage contributes to nuclear factor-kappaB (NFκB) activation. Simultaneous activation of PHOX (Phagocyte NADPH oxidase) and iNOS (inducible nitric oxide synthase) in microglia resulted in the disappearance of NO, appearance of peroxynitrite and apoptosis. However, the chronic state of activation may progress to “resolution phase” where microglia are amoeboid, highly phagocytic, and produce anti-inflammatory cytokines (including IL10 and TGFb) in order to resolve the inflammation and clear up the mess [1] With successful, non-phlogistic microglial phagocytosis of apoptotic neurons, the neuron is engulfed and digested without release of additional damage associated molecular patterns (DAMPs) into the tissue environment. This favors the production of anti-inflammatory cytokines and a movement toward resolution of tissue inflammation in the brain parenchyma. If instead the neuron dies by necrosis through direct or indirect trauma, or is triggered into necrosis by a pathogen or toxin, its death releases cell fragments and cytosolic contents into the tissue environment, triggering a proinflammatory response in surrounding microglia. Neuroinflammation favors a more aggressive microglial cell phenotype and a more exuberant phagocytosis of neurons, yielding neuronal loss in excess of that necessary to bring about resolution of the initial condition.

SIDS, SIRS and CARS Acute neuroimmunological syndromes such as central nervous system injury-induced immune deficiency syndrome (SIDS), systemic inflammatory response syndrome (SIRS) and compensatory anti-inflammatory response syndrome (CARS) have been reviewed elsewhere [17]. It is unclear in the literature, however, whether a gradient of severity exists in these syndromes. For example, it is unclear whether a patient with mTBI (mild traumatic brain injury) might be expected to manifest a modest version of the apoptosis of innate immune cells and TH1 cells seen in SIDS. If this were the case, the patient might be incrementally more susceptible to chronic infection, promoting systemic and therefore neuroinflammatory mechanisms. From a clinical perspective, whether or not mild forms of these syndromes pertain, the clinician faced with a patient with a TBI or mTBI should be alert for indications of suppressed immune vigilance against pathogens. Such a circumstance would have the potential to yield chronic infection, a known driver of microglial priming and neuroinflammation.

The Injured Neuron In the realm of traumatic brain injury, the neuron is the center point of the physiological story [18]. Factors including the preexisting central integrated state of various neuronal pools, the integrity of existing neuronal circuitry, peripheral receptor integrity, level of circulating cytokine populations, polarization status of a dynamic immune system, level of glial priming and function, balance and integrity of the endocrine system, various underlying infectious organisms, genetic predisposition, associated comorbidities and the extent of damage sustained as well as related biomechanics of a


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given injury all determine neuronal integrity and probability of recovery post-injury [19]. Other factors that can impact the neuron are the nutritional and digestive status of the patient as well as vascular perfusion and autonomic integrity. The neuron’s ability to survive and maintain optimum functional capacity and appropriate cellular plasticity is vital to recovery and sustaining humanism and vitality post-neurological insult. Understanding and evaluating all converging physiological scenarios that can impact the health of the neuron and how it relates to head injury and damage to the CNS is vital when determining the extent of injury, creating appropriate treatment plans and care of patients suffering from traumatic brain injury or neurodegeneration [20]. The intracellular cascade after head injury is complex and involves organelle function, metabolic and ionic fluctuations and surface receptor interplay. This gross level interplay impacts cellular plasticity, immunoexcitotoxicty, intracellular calcium and binding proteins, caspase cascades, apoptosis, cerebral blood flow, glucose metabolism, phospholipase and free radical production, protease and cytoskeleton breakdown, endonuclease and DNA damage, nitric oxide isomers and superoxide anions [12]. On a smaller intracellular scale, organelle involvement includes changes in mitochondrial function, neurofilaments and microtubules, lysosomes, epigenetic function, protein replication, secretory vesicle production and synaptic capacity. The eventual consequence of intracellular and organelle variations will impact cellular energy, axonal and myelin integrity, cellular swelling, synaptic transmission, lipid membrane stability, synaptic transmission, and cellular summation capabilities. When damage occurs in the CNS, neurons are impacted, glial cells are altered, glutamate receptors can become sensitized, GABA receptors can become internalized, the immunological system is impacted, vasculature is compromised and the blood-brain barrier becomes damaged. This combination of events can lead to cellular damage, microglial priming and sustained inflammation within the CNS, antigen presentation of neural tissues and possible autoimmunity and compromise in the resolution process post-injury [21]. Surface receptor types, densities and their sensitivities also contribute to metabolism [22]. There are many receptor types; however, of particular interest are the ionotropic receptors including NMDA, AMPA, Kainate and voltage gated calcium channels. These receptors types allow a regulated influx of calcium into the cell that impacts multiple intracellular pathways allowing for intracellular cascades, cellular function, cellular plasticity and long term potentiation. The ultimate promotion of NMDAr(define) (N-methyl-D-aspartate, a specific type of ionotropic glutamate receptor) promotes the extracellular influx of calcium and calcium stores within the cell. The increase and appropriate regulation of cytosolic calcium leads to the proper activation of kinase dependent signaling cascades leading to cAMP (cyclic adenosine monophosphate) element binding protein activation. The activation of CREB (cAMP Response Element-Binding protein) ultimately generates the phosphorylation at SER 133 (serine 133) leading the generation of protein synthesis within the nucleus. This generates the ability for the cell to innately generate more surface receptors, intracellular structures, cytokines, neurotrophic factors, cellular efficiency, dendritic development and repair cycles vital for cell survival. The ultimate outcome of this process is synaptic plasticity and long term potentiation. This process is a large part of learning and memory and is a major mechanism of repair after damaged neural circuitry is created after head injury or in a neurodegenerative process [23]. The dysregulation of intracellular calcium, however, can lead to degenerative and excitotoxic mechanisms that are damaging. Under certain circumstance, cell surface receptors become more permeable to calcium while intracellular calcium-buffering proteins become aberrant thus causing the intracellular calcium levels to become dysregulated. Multiple neurodegenerative conditions, inflammatory scenarios and disease processes as well as excitotoxin loads and glutamate levels have the ability to alter NMDA receptors activation and skew AMPA:NMDA receptor ratios allowing a greater influx of extracellular calcium into the cell [18]. The resultant intracellular calcium dysregulation triggers pathology. The triggering of intracellular lipases causes cell membrane damage.

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Triggered nucleases destroy DNA. Calcium induced phospholipase activation promotes prostaglandins, arachidonic acid and leukotrienes which generate inflammation, vascular dysfunction, white matter disease, myelin damage, axonal damage and further free radical generation [24]. Energy uncoupling allows for protein phosphorylation, which alters gene expression and ion channel activity and changes the central integrated state and firing capacity of the neuron. Calcium induced proteolysis occurs which breaks down the cytoskeletal structure of the neuron thus altering transporting mechanisms and supportive structures of the cell body and axonal projections. This has the potential to alter antero- and retrograde function, which can alter the transportation of synaptic vesicles thus reducing synaptic activity. Activation of reactive oxygen and nitrogen species generates mitochondrial damage, NFκB activation and ultimately cellular apoptosis if persistent. A continuation of inflammation, oxidative damage and excitotoxicity can generate a situation where glial cells remain primed, neurons fail to function, plasticity is diminished and the neurochemical environment is altered. This continued process can lead to post concussive syndromes, second impact syndromes and repeat concussive symptoms despite not having another physical injury.

Figure 4. The balance of life and death receptors is epigenetically primed much like the muscle spindle system © Joel Brandon Brock 2013.

During times of oxidative stress, inflammation or neurodegeneration, energetic failure emerges among normal mitochondrial function and overall energy production of the cell [25]. This can lead to

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a breakdown in the electron transport chain and decrease mitochondrial calcium loading capacity through an activated mitochondrial permeability exchanger. The exchanger opens mitochondrial pores and allows the deposition of calcium within the mitochondria into the cellular cytosol disrupting intracellular calcium regulation. Respiratory chain uncoupling and the release of intermembrane space proteins as a result of MPT (membrane permeability transition) activation causes multiple cascades to occur [26]. These include the release of intracellular caspases, caspase independent cell death effectors, NLRP3 inflammasomes, NFκB and interferon regulatory factors. The release of cytochrome C from the mitochondria activates caspase three which programs cell death and apoptosis. These cascades collectively lead to the development of inflammation, loss of cellular energy production and perpetuate further mitochondrial and cellular dysfunction. Thus the milieu of the cell primes the receptor sensitivity even before death or life receptors are triggered. This phenomenon of “setting receptor tone” is conceptually similar to how the tympanum tension is preset to perceive or protect from sound prior to the event, and the muscle spindle tone is preset before a perturbation. The implications of this for clinical prognosis and cellular apoptosis indicate some potential for leverage through clinical cell mediator manipulation. Such manipulation could be through substances administered as well as evoked potentials. In a normal cell, when there is abnormal stress, organelle damage, accumulation of misfolded proteins or damaged mitochondria, the cell removes the damaged organelles or unwanted proteins [27]. These processes include autophagy and mitophagy. Under periods of aging, inflammation, oxidative stress, mitochondrial damage, intracellular calcium dysregulation or a decrease in cellular activation, appropriate autophagy and mitophagy is impaired. When these cellular processes are impaired after head injury, various diseases can manifest, the health of the neuron can fail and ultimately lead to cellular death and premature neurodegeneration. Copyright ©Joel Brandon Brock 2013

Mechanism of Injury

Will vary depending On time

Age / Sex / Other bodily injury

PAST MEDICAL HISTORY

Cellular damage

Axonal damage Changes to CNS Depends on area of trauma, extent of force on the head, amount of tissue ischemia, other comorbidities

Synaptic Damage

Neurofilaments

Will vary depending on severity

Mechanical and ionic Deformation Glial priming Inflammation Damage to Terminal or transporters

Twisting, Shearing, Compression Bleeding, Diffuse and Focal Damage

Structural Damage

Relates to comorbidities And number of injuries

Biomechanical forces

Neurochemical Damage

Knockout Coup Contra Coup Rotational Shearing Linear force Bleeding

Head Injury Unconscious

Chemical Cascade

Lysosome Mitochondrial Autophagy

NMDA Caspase Calpain

Excitotoxicity Reuptake transporter loss

Glutamate ↑ GABA↓

Chemical Cascade

Twisting Rotation Shearing force Blunt trauma Traction To Peripheral Vestibular System

Second impact / Post concussive prone

Bleeding / stroke / watershed

Transmitter changes

Vascular changes

Golgi Packaging damage

↓Fuel causes Cellular Oxidative stress Failure

Contusion or damage to the peripheral vestibular apparatus

Synaptic vesicle loss


Apoptosis PON iNOS SOA


Hyperkinetic TND Excitotoxic

Second impact / Post concussiveprone

Depression Pain Emotional changes

Emotional changes Head and body pain

Reactive Vasconstriction Ischemia To tissue

Excitotoxicty

Decrease in synaptic transmission

Decrease in fuel for delivery Damage to TM / round / oval window

Delineate vestibular And Auditory loss or both

Serotonin ↓ Dopamine ↓ Monoamine issue

Energy loss Intracellular debris

Fistula / TM

Or

Prone for loss in plasticity

Without therapy Recovery ↓

Damage to hair cells Or

Hearing loss Canal / Otoliths

Displacement of Otoconia

BPPV Conditions

or

Fracture to temporal bone Damage to PVN Damage to PV apparatus

Or

Inflammation Autoimmunity

Hydrops

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Figure 5. How physical forces transmute into cellular changes and clinical conditions © Joel Brandon Brock 2013.

Head injury or uncontrolled inflammation or imbalanced immunological responses can trigger abnormal neuronal surface receptor activation. This can lead to dysregulated intracellular calcium, which can cause oxidative stress, cell structure breakdown, energy production loss and activation of inflammatory cytokines. Inflammation and cellular apoptosis can ultimately lead to the released of glutamate and proinflammatory cytokines that generate more surrounding excitotoxicity to nearby cells. This can create plasticity related to abnormal circuitry activation and lead to seizure, hyperkinetic function, ischemia and GABA receptor internalization. This mechanism is the cornerstone to the onset and perpetuation of many neurodegenerative diseases that might arise or be triggered post TBI.

Neuronal Energetics and TBI Traumatic brain injury alters neuronal membrane potentials amking them more sensitive thus placing greater energy demand on a compromised system. Glucose is the obligate fuel source of the mammalian brain. While the brain can use alternate fuels, such as lactate and ketones, the efficiency with which the brain can do so varies with development stage/age as well as whether or not the brain is operating under normal physiological conditions [28]. While the brain accounts for only 2% of a human’s entire biomass it is responsible for 50% of total glucose utilization [29]. Under normal physiological conditions approximately 85% of brain glucose utilization is directed toward fueling the Na/K pumps that restore resting membrane potentials in active neurons [30]. Like the periphery, cellular uptake of glucose in the brain can be accomplished through both insulin-independent and insulin-dependent mechanisms. And while central neurons can synthesize their own insulin the majority of brain-based insulin is derived from peripheral supply [31]. The brain environment is sequestered and barriers exist to free flow of nutrients and glucose from the periphery. The two main obstacles to delivering nutrients and glucose to active neural tissue in the CNS are the blood-brain barrier (BBB) and the lack of local carbohydrate storage in neurons themselves [31]. Under conditions of concussion and traumatic brain injury, energy demands increase while glucose utilization decreasesresulting in a significant neuroenergetic mismatch [32].

Glucose Transport Across the Blood-Brain Barrier The neuronal cell membrane is an impermeable barrier that requires insulin for transport across the cell membrane. Neurons express high amounts of insulin receptors, however the majority of brain insulin is derived from peripheral production, although some evidence does exist that neurons can produce small amounts of insulin themselves [33]. Beyond the cell membrane the neurovascular unit functions not only as a static barrier but can adapt to physiological changes by altering transport systems in order to modify and facilitate ion and nutrient flux. There are two primary classes of active glucose transporters that can express on both luminal (blood facing) and abluminal (brain facing) surfaces of the neurovascular unit. These two mechanisms are dedicated glucose transporters (GLUT1) and sodium-glucose co-transporters (SGLT). GLUT1 is a member of the glucose transport molecule family, is highly expressed in the brain, and can upregulate or down-regulate nutrient transport depending on the pathophysiological state of the system [33] [33]. It is a facilitated transport system that moves glucose along a gradient and is both Na+ and insulin independent. SGLT, on the other hand, is a Na-dependent symporter (integral membrane protein involved in transport of molecules across phospholipid membrane), moving one


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glucose molecule along with two Na+ molecules in the same direction across the cell membrane in a co-transport relationship, against the glucose gradient [31]. SGLT is a secondary active transport mechanism that uses ATP generated from ion gradients. SGLT can also function in reverse, moving accumulated Na+ out of the cell into the extracellular space [34]. While GLUT1 is considered the primary glucose transport system studies have shown upregulation of the sodium-dependent glucose transporter SGLT1 in conditions of ischemia-hypoxia [33]. Because of these limitations (cellular and tissue level barriers coupled with a lack of passive diffusion and local neuronal glucose storage) the brain relies heavily on the expression of glucose transporters on the blood-brain barrier as well as the storage capacity of astrocytes. Both of these glucose transporters can be insulin sensitive or insensitive, hormonally regulated or driven by glucose concentrations [31] Other GLUT and SGLT isoforms (GLUT3, GLUT4, SGLT1, SGLT2) exist in the brain, but in lower concentrations and contribute to a lesser degree to neuroenergetics [5].

Energy Compartmentalization In the brain, energy metabolism is highly compartmentalized [35]. While neurons have both aerobic and anaerobic pathways they have little capacity to store energy. As such neurons rely heavily on glucose delivery from the periphery as well as the participation of astroglial cells, which function as the brain’s glycogen repository. This presents several problems since there are significant barriers to consistent and stable glucose supply to the brain. Furthermore astrocytic glycogenesis and glycogenolysis as well as neuronal mitochondrial function can be influenced by TBI. Since neurons do not store glycogen, neuronal glucose utilization is intimately yoked to astroglial compartmentalization of glycogen. In the absence of its own localized glycogen neurons must communicate energetically with astrocytes in order to replenish energy substrates. This allows for resetting of membrane potentials and continued neuronal viability and functionality. Astrocytes support neuronal energetics via multiple pathways, the most notable and well-studied being the Glutamine-Glutamate Cycle and the Astrocyte Neuron Lactate Shuttle (ANLS). In the former, glutamate produced by neuronal Citric Acid Cycle (TCA) mechanics passes into the extracellular space and is taken up by astroglial cells where it is converted to glutamine [36]. Astroglial glutamine then exits the astrocyte and can be taken up again by a nearby neuron where it can resupply the neurotransmitter pool or reenter the TCA cycle by being converted into either alphaketoglutarate or succinate [37]. The Astrocyte Neuron Lactate Shuttle provides substrate for neurons to engage the glycolytic pathway. Extracellular glutamate, from active neuronal signaling, increases astroglial uptake of glucose by upregulating GLUT1 [38]. Astroglial cells then drive the glycolytic process creating lactate as a metabolic byproduct. This lactate is transported out of the astroglia into neurons by a monocarboxylate transporters, MCT1 and MCT 2 respectively. Neurons express several isoforms of lactate dehydrogenase (LDH) causing the conversion of lactate to pyruvate and the initiation of neuronal glycolysis, which eventually yields more glutamate to continue the ANLS. These two systems, Glutamine-Glutamate Cycling and the Lactate Shuttle, bind astroglial cells and central neurons in a symbiotic relationship that ultimately determines the ATP potential of both functional and injured brains.

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TBI Alters Brain Energy Metabolism In 2001, Giza and Hovda outlined the neurometabolic cascade of concussion. The injured brain shifts into “hypermetabolism”, which increases the demand for ATP. At the same time energy production pathways shift away from the highly efficient oxidative phosphorylation to the much less efficient glycolysis. The net effect is neuronal acidosis, membrane dysfunction and BBB permeability. In addition evidence suggests that in the context of TBI lactate-consuming pathways that would otherwise drive ATP production via the ANLS are compromised [32]. What follows is diminished cerebral blood flow, which may be reduced by as much as 50%. This cellular energy crisis predisposes the injured brain to second injury and prolongs functional deficits associated with the injury [39]. Beyond the direct effects upon ATP producing pathways, post-injury depolarization and K efflux opens NMDA receptors. Calcium influx further impairs neuronal ATP production by impairing both oxidative phosphorylation and glycolysis. This promotes activation of apoptotic pathways, neurofilament compaction, microtubule disassembly, axonotomy and increases the production of inducible nitric oxide synthase [39]. Due to its high lipid content, the brain is highly susceptible to oxidative damage. TBI leads to a significant decrease in glutathione and ascorbic acid, the two primary intracellular antioxidants. Rat brains subjected to TBI showed a three-fold reduction in the reduced-to-oxidized glutathione ratio. Concomitant reductions in cerebral NAD+ promote mitochondrial dysfunction [32]. Reduced glutathione has been shown to impair astroglial glucose metabolism and glycogen utilization [40].

Hypoxia Epidemiological studies reveal that up to 44% of severe TBI patients experience brain hypoxia that is a direct consequence of hypoperfusion. Proinflammatory cytokine upregulation induces BBB dysfunction via IL-6 and IL-1b and an overall significant hypoglycemia, with brain glucose levels dropping by 50% in injury-induced hypoxia [41].

Peripheral Metabolic Impacts on Injured Brain Fuel Status Ives et al explored evidence of hypopituitarism following multiple concussions. Growth hormone was the most vulnerable to successive brain injury followed by gonadotropins, TSH and finally ACTH. Furthermore these hormonal imbalances may not be evident until well after the initiating injury [42]. Agha et al explored Glucagon Stimulation and Insulin Tolerance tests in a population of brain injured patients with a median interval of 7 months post-injury. Approximately 28% of patients exhibited at least one anterior pituitary hormone deficiency, 22% showed isolated deficiencies involving either GH, LH/FSH (follicle-stimulating hormone) or ACTH (adrenocorticotropic hormone) and 6% showed evidence of multiple deficiencies [43]. Both GH and ACTH exert significant influence over the action of both glucagon and insulin, and GH deficiency can impair glucose tolerance by decreasing beta cell mass and insulin production [44]. These conditions can have impacts on the injured brain primarily due to the brain’s reliance on peripherally derived insulin for glucose uptake.


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Post-Synaptic Contributions in TBI TBI and Central Processing of Viscera Traumatic brain injury can lead to various mechanisms of gastrointestinal dysfunction. These mechanisms include: impairment of digestive enzyme production, impairment of intestinal motility, disruption intestinal autonomics related to circulation, promotion of intestinal permeability, and altered interoceptive processing. Disruption of the brain-gut axis involving the cortico-pontine circuit has been demonstrated with brain imaging studies as a central mechanism of irritable bowel syndrome [45]. Central integration of cortico-pontine circuit is critical for proper vagal temporal summation and autonomic regulation necessary for regulating proper intestinal afferent and efferent communication. Additionally, traumatic brain injury can lead to significant changes of brain-gut peptides in both plasma and small intestine, which may be involved in the pathogenesis of complicated gastrointestinal dysfunction [46]. These cortico-pontine and pontine-cortical central integrations may be altered in TBI. Cortical integration is critical for proper bowel function and bowel disorders associated with lack of cortical level integration of visceral inputs have been demonstrated with percept-related fMRI [47]. Therefore it appears that TBI may potentially lead to altered gastrointestinal function from loss of cortico-pontine central processing. TBI and Intestinal Permeability One of the major consequences of TBI is lack of cortical activation of the pontine vagal system leading to altered postsynaptic autonomic changes that promote decreased intestinal autonomics and inflammatory reactions leading to intestinal permeability. Intestinal permeability induced from TBI may be a consequence of lack of post-syanaptic activation of the vagal nuclei. In a mouse model of TBI, vagal stimulation prevented TBI-induced intestinal permeability and also increased enteric glial activity [48]. This study supported the notion that the vagal nuclei disruption from TBI was the central mechanism for intestinal permeability development and that vagal activation has modulating activity on the enteric glia neuroinflammatory responses. Additionally, TBI can induce an increase in intestinal permeability, which may lead to bacterial translocation, sepsis, and system inflammation [49,50]. TBI induced intestinal permeability thus has the potential to promote a vicious inflammatory cascade involving the brain to gut axis and the gut to brain axis. Intestinal permeability has been found to increase proinflammatory cytokines at the intestinal mucosal level and cause lipopolysaccharide translocation that can disrupt brain function [51,52]. Therefore, the alteration of cortico-pontine integration from TBI can lead to gastrointestinal inflammatory consequences from intestinal permeability that then potentially further suppress brain function leading to chronic inflammatory vicious cycles between the brain and the gastrointestinal system. Traumatic brain injury can also lead to pro-inflammatory immune activation in the peripheral blood stream leading to systemic inflammatory response syndrome [53] TBI and Intestinal Mucosa Compromise At the intestinal level many changes take place in the intestinal mucosa directly after brain injury including mucosal ischemia, mucosal atrophy, and activation of intestinal inflammatory cascades. These reactions occur rapidly as early as 3 hours following brain injury and last for more than 7 days with marked mucosal atrophy [54]. Additionally, TBI induces profound effects including gastrointestinal mucosa ischemia and motility dysfunction [55]. The inflammatory reactions that occur in the intestinal mucosa following traumatic brain injury appear to increase the expression of intestinal nuclear factor kappa B and intercellular adhesion molecule-1 in the intestine leading to acute gut mucosal injury following TBI [56,57]. There is also rapid and persistent up-regulation of myeloid differentiation primary response protein 88 (Myd88) in combination with systemic inflammatory cytokine activation [58]. These inflammatory changes that occur after TBI are immediate and

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illustrate how cortical injury can lead to inflammatory consequences in the peripheral gastrointestinal mucosa lining. TBI and Breakdown of the Blood-Brain Barrier The blood-brain barrier plays a critical role in protecting the brain from immune activating substances. However, widespread breakdown of the blood-brain barrier occurs immediately after brain trauma leading to susceptibility of circulating proteins and the promotion of inflammatory sequelae [59]. It appears the blood-brain barrier breakdown occurs rapidly within hours. TBI disruption of the blood-brain barrier occurs and cerebral vascular permeability can increase fourfold within six hours of the initiating trauma. It was also found that vagal nerve stimulation attenuated cerebral vascular permeability and decreased up-regulation of perivascular aquaporin 4 after TBI [60]. Therefore TBI loss of cortico-pontine dysregulation of the vagal nuclei appears to be a central mechanism for both intestinal and blood-brain permeability. Specifically TBI induces profound breakdown of the bloodbrain and blood cerebrospinal fluid barriers (BCSFB) and release into the CSF a major chemoattractant for monocytes, CCL2, by the choroid plexus epithelium at the side of the BCSFB (blood cerebrospinal fluid barriers) leading to post-traumatic invasion of monocytes promoting the recruitment of inflammatory cells to the injured brain [61]. These inflammatory changes in the bloodbrain barrier neurovascular network have been found to ultimately lead to delayed neuronal dysfunction and degeneration [62]. In summary, in TBI loss of cortico-pontine processing disrupts vagal network integration and inflammatory sequelea that promotes breakdown of the neurovascular blood-brain barrier network leading to loss of brain barrier protection and susceptibility to further neuroinflammation. Joel Brock © copyright2013 TBI Plasticity Receptor based therapy

Canals Otoliths

Vestibular input

PMRF MRF Trigeminal

Autonomics

Dietary Nutritional Concerns

Supplements Diet

Neuron Glial Immune interaction

Brain

Glial Cells

Blood flow Transmitters

Fuel Delivery Efficiency Transmitters Brainstem output

Parasympathetic Sympathetic balance

Control immune activation Can prime or turn off Reticular Pyramidal Glial Inflammation Brain activation

Muscle tone Posture

Innate Immune Response

Gait Stability Agility Biomechanics

Barriers

P450

Toxin removal

Cytokines

Pathogen Not Killed. Tissue Inflamed. Gut Brain Lung Glial cells

Posture Vestibulo ocular

Tissue Becomes Antigen

Inadequate

Endocrine / Cortisol

Neuroinflammation Neurodegeneration

Ocular function

Neuron – Microglial Cytokine Interactions

Inflammatory Non‐inflam BDNF

Success

Excessive

Tissue Becomes Antigen

Apoptosis vs. Necrosis

Organ interaction Stress reactions

Control of hormone Blood sugar output

Non or inflammatory Cytokines

Cytokines, Hormones, NT’s Immune borders

Central integrated state

Cell growth or death

Immune activation

ROS / PON Mit failure

NMDA / Death receptors

↓Inflammation & ↓Pathogen Killing vs. ↑Inflammation & ↑Pathogen Killing

Gain and sensitivity

Loss of brain mass ROS, RNS, Other Tissue Factors

Spindle feedback Deafferentated

Apoptosis

Cytochrome Caspase NFKB or Epigenetic changes

Adrenal‐ thyroid insulin Tissue Health / death Cellular health / death Ability to be plastic / TND Glial Priming / Glial coding

Death Caspase cascade

Organ output

Self / Alt‐Self / Pathogen Antigen

Glial health / Protection of tissues

Excitotoxic Glutamate↑ gaba↓

Cell growth

T Cell Polarization Dynamic connectivity

Astrocyte barrier protection Inflammation Barrier breakdown

Pathogen Killed. Tissue Inflamed.

Factors Influencing Neuroimmunological Outcomes... Regulation of Immune separation

Biotransformation Chemical sensitivity

Astrocytes Microglial Oligodendro

Success

Resolution Adaptive Response

Vestibulospinal

Vagal control over LIver

Transmitters Hypothalamic Immune Paraventricular Mesencephalic

Right

Good and bad Needs balance

Splenic cytokines

Vagal output Biotransformation

Cerebellum Basal Ganglia

Proprioceptive Feedback

Vagal output

Inflammatory respons

Left

Energy failure

Figure 6. Stepwise progression toward immune dysfunction in brain injury © Joel Brandon Brock 2013.


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TBI Dysautonomia Various autonomic imbalances may occur after brain injury impaired cortico-pontine integration called dysautonomia [63]. It is a common consequence of TBI and has been found in 8 to 33% of TBI individuals [64]. Dysautonomia after brain injury is characterized by episodes of increased heart rate, temperature, blood pressure, muscle tone, posturing, and profuse sweating [65]. A common presentation of dysautonomia is persistent sympathetic overactivity in response to nociceptive stimuli and development of chronic pain after TBI [66,67]. In addition to chronic pain, many individuals that suffer from TBI also demonstrate prolonged uncoupling of heart rate and heart rate variability postulated to occur from cortical-pontine disconnection [68]. These outcomes have also found to be worse with those that suffer from post-traumatic hypertonia and have been linked to poor long-term outcome [69]. It appears that TBI leads may lead to altered cortico-pontine integrations leading to various types of autonomic consequences such as chronic pain, hear rate variability, abnormal sweating, and various types of imbalanced sympathetic and parasympathetic responses. TBI and Systemic Immune Dysregulation Immune system dysregulation may occur from traumatic brain injury, specifically TBI can lead to immunodeficiency and vulnerability to infections [70,71]. It appears brain injury leads to systemic immune responses from which chemokine signals from the central nervous system activate the production of hepatic immune responses and changes in systemic immunity [72]. TBI can alter immune homeostastis contributing to immunosuppression from decreased phagocytic functions of neutrophils and macrophages as well as monocyte deactivation resulting in decreased capacity of antigen presentation to lymphocytes [73]. These immune suppressive reactions may have long-term expressions. It was found that brain injury leads to immunodepression for months and to chronic central nervous system and systemic immune activation for years after the initial injury [74]. Animal lesion studies have been able to demonstrate the pre and post immunological changes that occur after brain injury. Animal induced lesion studies of the cerebellum with localized kainic acid microinjections resulted in reduction of lymphocyte percentage in peripheral white blood cells and an inhibition on the number and functions of T-cells, B-cells, and natural killer cells suggesting a role the cerebellum may play in neuroimmunomodulation [75,76]. These immune compromise changes secondary to brain lesions were also evaluated with kainate lesions of the vestibulocerebellum. The chemical lesion induced depressed secretion of hematopoietic cytokines in tissue cultures of bone marrow and thymus [77]. It appears that the brain and immune system are intimately connected and neuroimmunomodulation may be impaired after TBI leading to immunological compromise and susceptibility to infection.

The Blood-Brain Barrier Blood–Brain Barrier Role in TBI The term “leaky brain” is the jargon used to describe the increased permeability across the astrocytes that make up the blood-brain barrier. This is described as the increased passage of molecules through pericellular and transcellular permeability [78]. Shrinkage of endothelial cells causes a mechanical disarray of the tight junctional complex. This is due to drastic yet reversible changes in cell morphology leading to spatial reorganization of the junctions [78]. Brain infiltration of cells, ions, or molecules may initiate, amplify, procrastinate, repair or disrupt a CNS response [78]. It is also well understood that a fundamental principle of a mTBI is a breach in the BBB. The severity or ability to recover from a TBI may be intimately related to the pre-existing state or the severity of the breach of the BBB. Glial cell types are all capable of producing typical

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proinflammatory molecules [78]. Inflammatory cytokines have been implicated as modulators of BBB function [79]. TBI induced breaches in the BBB cause an extravasation or movement of albumin from the capillaries to the surrounding tissue in brain, changing the ion channels. This may be an independent activator of astrocytes and result in long-term neocortical abnormalities and functional decline [80]. The brain has a highly specialized glioneuronal system to buffer extracellular potassium [81]. Increased levels of potassium will cause massive reduction in blood flow. This reduction will shift the brain toward hypoxia and loss of metabolic support.

Figure 7. Cellular and barrier changes from TBI © Joel Brandon Brock 2013.

Glutamate is more concentrated in the blood. A breach in the BBB will lead to increased glutamate in brain causing an excitotoxic response and an increase in firing. Adenosine helps to maintain neurovascular control. When the BBB is breached, a complex synergy of adenosine and glutamate transporters and catalytic enzymes is altered, leading to an overall drop in adenosine availability to curb neuronal firing and increased glutamate [78]. In these examples it is reasonable to understand how a breach in the BBB, from multiple mechanisms, can lead to chronic states of neuronal compromise and predispose the brain to TBI and inhibit the recovery of a TBI. Vagal nerve stimulation attenuates the effects of TBI by protecting hippocampal neurons. Vagal nerve stimulation also attenuates the breakdown of the BBB post TBI. The attenuation of the BBB breakdown may be the mechanism of hippocampal protection [60]. This mechanism may be further described as vagal nerve stimulation induction of the cholinergic anti-inflammatory pathway, effectively inhibiting pro-inflammatory cytokines. This has been partially confirmed by vagal nerve stimulation decreasing systemic tumor necrosis factor alpha hours after TBI [82]. Some disagree and state it is due to a more localized central nervous system-specific effects of vagal nerve stimulation [83]. What is agreed on is the fact that vagal nerve stimulation attenuates post TBI BBB breakdown [82]. Not only is this a potential therapy, but also further implicates the importance of BBB integrity as an independent risk factor with regard to TBI. In adult brains, oligodendrocyte precursor cells (OPCs) are thought to maintain homeostasis and mediate long term repair in white matter after disease [79]. The activation of OPCs is supposed to represent a protective response in the damaged or diseased brain. Recently, however, reactive glia are now recognized to mediate complex mechanisms, including both beneficial and deleterious effects after brain injury and neurodegeneration [84,85]. For example, depending on context, astrocytes can either promote neuroplasticity or secrete inhibitory matrix molecules that inhibit axons [86,87]. Similarly, microglia are now known to release both pro-recovery and neurotoxic factors [88,89,90].


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OPCs can also release multiple factors to modulate neighboring cells and the microenvironment [91] These intercellular signals may be especially important, since perturbations in the blood-brain barrier (BBB) are known to be a critical part of white matter pathology in a wide range of CNS disorders [92,93]. OPCs in adult brain are precursor cells for white matter remodeling, and repair injury and demyelination. They can play a surprisingly deleterious role in cerebrovascular injury and demyelination in white matter [79]. With TBI or other mechanisms causing inflammatory changes in brain, even before demyelination occurs, BBB leakage and neutrophil infiltration can be observed [79]. MMP2 (matrix metalloproteinase-2) and -9, are known to mediate BBB injury [94,95]. In studies after an initiating trauma or event causing a BBB breach, the early phase of BBB leakage at 3 days, white matter MMP9 expression is increased, mostly in OPCs and at 7 or 14 days, a secondary expression of MMP9 occurs in cerebral endothelial cells [79]. No other glial cell types (mature oligodendrocytes, astrocytes, microglia) appear to produce MMP9 in the model of cerebral hypoperfusion and chronic hypoxic stress [82]. No significant MMP9 increases occur in blood neutrophils nor plasma at day 3. Importantly, MMP9 expressing OPCs were located close to cerebral endothelial cells and OPCs existed near the BBB leakage areas at the acute phase of white matter injury [79]. After brain injury and disease, progenitor/precursor cells in the adult brain are believed to help compensate for lost brain function [96,97]. OPCs can be triggered to become mature oligodendrocytes or cortical projection neurons after white matter injury [98]. OPCs can rapidly respond to white matter injury and produce MMP9 that appears to open the BBB and trigger secondary cascades of cerebrovascular injury and demyelination [79]. This could serve as a model to explain a more severe consequence of a “seemingly” mild injury/event causing severe effects on brain function. Inhibition of the early MMP9 phase in OPCs also prevented the secondary expression of MMP9 in cerebral endothelium on day 7 and subsequently the development of white matter injury and demyelination as well as cognitive deficits in cerebral hypoperfusion. OPC-derived MMP9 in the acute phase may trigger further secondary cascades of cerebrovascular damage in white matter [79].

Figure 8. Oligodendrocyte cascade [79].

OPCs do not produce MMP9 under normal conditions, but after treatment with nonlethal levels of the inflammatory cytokine IL-1beta (similar to that in a TBI), MMP9 secretion is markedly increased. IL-1beta–treated OPCs degrade the tight-junction protein ZO-1 in cerebral endothelial cells without affecting cell survival. Consistent with this effect on tight junctions, conditioned medium from IL1beta–stimulated OPCs significantly increased endothelial permeability and neutrophil transmigration [79]. This effect is dependent on MMP. This suggests that stimulated OPCs (potentially from TBI) release MMP9, which degrades the BBB in white matter. This represents a mechanism for white

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matter disease at an early stage, and creates further damage and downstream inflammation and demyelination. The state of the BBB both prior to and immediately after injury plays a major role in the probability of, the severity, and the long-term consequences a TBI. TBI and Its Effect on the Adrenals and Hormones Deficiencies in circulating hormones may not be apparent immediately after injury but can be demonstrated days to weeks thereafter. Aimaretti et al. reported an incidence of pituitary dysfunction in 33% of TBI patients 3 months after injury, complete panhypopituitarism in 5.7%, multiple defects in another 5.7% and a single hormone deficit in 21%. Secondary hypoadrenalism was found in 8.5% but considering those with panhypopituitarism or multiple hormone abnormalities that might include the adrenal hormones, this incidence may be as high as 20% [99]. In a prospective comparison of 80 TBI patients to 41 trauma patients without TBI, measuring cortisol and ACTH levels twice daily for 9 days after injury, adrenal failure, which was defined as two consecutive cortisols of ≤ 15µg/dL or one cortisol of ≤ 5µg/dL, occurred in 53% of the TBI patients at a mean time of 2.4 days and suggested a secondary cause. Patients with adrenal failure were more severely injured, demonstrated more episodes of hypotension and more often required vasoactive drug support [100]. From such data, it would appear that the risk of secondary hypoadrenalism after TBI is somewhat higher than 25%. Recently published guidelines recommend acute endocrine evaluation only for patients with documented fractures in the sella turcica or diabetes insipidus. Other authors, however, suggest early endocrine assessment for all patients with moderate-to-severe TBI and routine endocrine testing for all TBI patients at 3 and 12 months. It is also suggested that evaluation be performed for primary and secondary adrenal failure in patients that demonstrate continuing hyponatremia or hypoglycemia or require persistent vasoactive drug treatment during acute care [99]. Endocrine evaluation should include a baseline blood cortisol concentration, a serum ACTH measurement and thyroid studies before the administration of any preparation containing steroids. Although some authors recommend a morning cortisol blood test, stress decreases the normal diurnal variation in cortisol release, making random values acceptable. In both primary and secondary adrenal failure this measurement should be low. The actual concentration that defines a low value is somewhat controversial because of the expected increase in cortisol during ‘stress’ caused by TBI. Therefore, values between 200 and 700 nmol/l or over 15mgm/dl are suggested as minimal basal concentrations expected after trauma [100]. HPA (hypothalamic-pituitary-adrenal) injury may also produce underproduction of thyroid stimulating hormone (TSH) as ‘central’ hypothyroidism, indicated by low TSH and tetraiodothyronine (T4) blood concentrations. The ‘euthyroid sick syndrome’ is expected in such critically injured patients, but in that condition the TSH remains normal. Growth hormone and the several gonadal hormones produced by the pituitary gland may also be low but do not require acute replacement, although treatment during later recovery will be important [100]. Utilization of the traditional ‘high-dose’ (250 mg) versus ‘low-dose’ (1 mg) ACTH stimulation test remains controversial. The higher pharmacological amount may allow a partially dysfunctional gland to release a sufficient amount of hormone to appear falsely normal, while the lower dose is perhaps more difficult to accurately administer. Similarly, criteria regarding the magnitude of response that confirms a responsive adrenal gland have been controversial. Criteria include either a specific post-stimulation (usually 60 min) cortisol concentration (e.g., above 500 nmol/l, or 25 mg/dl) or a specified incremental increase from basal levels (e.g., >250 nmol/l or >9 mg/dl). Bernard et al. found 78% of their TBI patients had a basal cortisol value of under 414 nmol/l, but after a 250 mg ACTH stimulation, only 13% failed to increase the serum cortisol concentration by less than 250 nmol/l [101]. These data again emphasize that the diagnosis of hypoadrenalism often depends upon the criteria selected [100].


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Cortisol is measured in the blood as both an unbound (‘free’) form, which is the biologically active hormone, and as cortisol bound with cortisol-binding globulin (CBG). CBG is commonly low in critical illness/injury, especially when the serum albumin is less than 2.5 gm/dl and may be one cause of an apparent low cortisol serum concentration. Measurement of free-cortisol, therefore, has been suggested as the more accurate assessment of adrenal output. Testing methods for CBG and free cortisol, however, are rarely available [99]. Acute hypoadrenalism after TBI may contribute to hypotension, hyponatremia or hypoglycemia during patient care. Its incidence remains unclear due to variable definitions and testing methods, but appears to be approximately 25%, including both secondary causes related to injury to the central hypothalamic-pituitary axis and primary adrenal failure. We recommend serum testing of basal cortisol, ACTH, and post-ACTH stimulation cortisol at 60 min when hypoadrenalism is suspected. Basal cortisol below 15 mg/dl suggests either primary or secondary adrenal failure and may warrant treatment. Failure of the cortisol concentration to increase by at least 9 mg/dl after stimulation suggests primary adrenal gland hypoadrenalism. Treatment with intravenous hydrocortisone during acute care should be initiated if clinical circumstances warrant. Thyroid function should also be evaluated and, if needed, hormone replacement should be provided if adrenal insufficiency is treated. It is generally recommended that even if acute treatment is not given, all patients should be evaluated for adrenal, thyroid and growth hormone deficiency 3 months after severe TBI [99]. It has been previously reported that experimental mild traumatic brain injury results in increased sensitivity to stressful events during the first post-injury weeks, as determined by analyzing the hypothalamic-pituitary-adrenal (HPA) axis regulation following restraint-induced stress. This is the same time period when rehabilitative exercise has proven to be ineffective after a mild fluidpercussion injury (FPI) [100]. These findings suggest that the increased sensitivity to stressful events during the first post-injury weeks, after a mild FPI, has an impact on hippocampal neuroplasticity [100]. An earlier paper described an increased sensitivity to restraint-induced stress during the first two post-injury weeks as indicated by increases in corticosterone (CORT) and ACTH compared to uninjured rats [100]. The stress response involves the activation of the HPA axis resulting in the release of ACTH from pituitary cells. ACTH stimulates the adrenal gland to release glucocorticoids, such as CORT, which in turn results in the inhibition of ACTH secretion [102]. It has been well characterized that stress decreases neuronal plasticity and favors neurodegeneration [103]. The effects of stress on the central nervous system are most notable within the hippocampus where it substantially influences neuronal excitability and long-term potentiation (LTP). The hippocampus has a high density of glucocorticoid receptors [104]. These receptors exert a variety of effects besides the autoregulation of the stress response, such as influencing mood, learning and memory [105]. Moreover, stress-related increases in glucocorticoids have been associated with cell death and cognitive impairments [106]. Among the effects of stress is the inhibition of hippocampal brain-derived neurotrophic factor (BDNF) [107]. The anatomical and vascular characteristics of the hypothalamic-pituitary complex increase its vulnerability during TBI. Particularly, diffuse TBI, where metabolism and neural connectivity are compromised [108]. Given the above-mentioned effects of glucocorticoids on hippocampal synaptic plasticity and BDNF expression, it is feasible that impaired neuroendocrine function interferes with BDNFmediated restorative processes after TBI. For example, a hyper-response to stress following TBI may play a role in the inability to increase BDNF during the subacute period, as seen in rats with a mild injury [109]. Affective disorders and cognitive impairments after TBI play a substantial part in decreasing quality of life. A dysregulation of the stress response has been linked to affective disorders in TBI patients. In effect, alterations in the regulation of the HPA axis contribute to negative mood states

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associated with depression [110]. In addition to showing a hyper-responsiveness to stress after TBI, we now provide evidence that post-injury stress has an effect on BDNF regulation within the hippocampus. The effects of stress on cognitive abilities also need to be considered, particularly given BDNF’s effects on plasticity. An increase in glucocorticoids, in human subjects, is associated with impaired memory and hippocampal deterioration [111]. These data add some pieces to the puzzle in understanding the hyper-response and the delay of exercise-induced increases in BDNF during the subacute period. However, they also emphasize the need for more studies regarding HPA dysregulation after a mild TBI. Understanding some of the molecular mechanisms influencing the response to stress will allow us to better address posttraumatic affective and behavioral disorders as well as enhancing rehabilitative therapies. There were 113 charts that were retrospectively reviewed of traumatic brain injury patients within 10 days of their injury. They all had a high-dose corticotropin stimulation test performed because of haemodynamic instability. Blood cortisol concentrations were measured at baseline, 30 and 60 minutes after the administration of high-dose corticotropin. The incidence of adrenal insufficiency was determined according to various definitions used in the literature [101]. Primary adrenal insufficiency defined by an abnormal baseline cortisol concentration and an abnormal response to the high-dose corticotropin stimulation test was present in 13–28% of patients according to the cut-off values used. The incidence of adrenal insufficiency varies from 25 to 100% in the first 10 days after traumatic brain injury when the charts of 113 traumatic brain injury patients were reviewed [101]. Adrenal insufficiency has emerged in recent years to be a crucial and prevalent problem in intensive care. Hypopituitarism has recently been reported to occur in 35–80% of patients in rehabilitation following head injury. Adrenal insufficiency accounts for 30–50% of these cases [101]. Underestimation of the true incidence of adrenal insufficiency and potentially under-treated patients may be occurring by using only the low-dose stimulation test to define adrenal insufficiency [101]. A concentration of 414 nmol/l is considered to be the normal minimum value in response to severe stress, particularly hypotension. Hence, it is viewed as the minimal appropriate concentration for intensive care patients. A concentration below 690 nmol/l has been suggested instead since patients undergoing surgery or sustaining trauma almost invariably have cortisol concentrations above this value. The intensive care literature tends to support this view. Response to high-dose corticotropin stimulation test, in a study by Annane and colleagues, suggested a rise in plasma cortisol concentration by >250 nmol/l was the appropriate response of the adrenal glands in intensive care patients with sepsis [112]. This definition is probably the most widely used cut-off to interpret a stimulation test in intensive care. Classically, a rise above 500 or 550 nmol/l is considered normal based on the response of non-critically ill patients to insulin-induced hypoglycaemia [101]. Primary adrenal insufficiency defined by an abnormal baseline and abnormal post high-dose corticotropin stimulation test cortisol concentration was present in 13–28% of patients depending on whether a 60 or 30 min sampling time after high-dose corticotropin was used, respectively. Whichever definition was used, the incidence of primary adrenal insufficiency is markedly reduced if the 60 min (rather than the 30 min) cortisol values were used to define adrenal insufficiency [101].This study showed that the incidence of adrenal insufficiency in severe traumatic brain injury varies enormously depending on the definition used. The incidence of adrenal insufficiency defined by baseline cortisol concentrations may be as high as 100%. Primary adrenal insufficiency accounts for 13–25% of the cases. It also demonstrated that sampling for cortisol at 60 min after a high-dose corticotropin stimulation test is more appropriate than doing so at 30 min. 414 mmol/l is probably a more useful cut off in a traumatic brain injury population [103]. Although fatigue is a common experience in the general population it is particularly bothersome to those with TBI [113]. Depending on the scales used to measure fatigue and time since injury, its


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prevalence has been reported in 16–80% of individuals after injury. Associated symptoms include depression, sleep disturbance, pain, cognitive and motor disturbances [113]. Neuroendocrine abnormalities as manifested by pituitary dysfunction can occur after TBI. Oneto-several hypothalamic-pituitary axes may be affected; posterior pituitary dysfunction typically resolves during the first several months post-injury, whereas anterior pituitary problems are more likely to persist [113]. Although several lines of evidence indicate that TBI may predispose the pituitary to injury, neuroendocrine dysfunction is rarely considered in current TBI management. Autopsy studies of fatal head-injury victims confirm that up to one third sustain anterior pituitary gland necrosis. Moreover, numerous case reports, retrospective reviews, and recent prospective cohort studies have documented acute and chronic posttraumatic hypopituitarism [100]. Activation of the HPA axis is an important protective response during critical illness. Untreated adrenal insufficiency (AI) may lead to hemodynamic instability and poor outcome. [100] The molecular mechanism of the effects of glucocorticoids on chronic inflammation is not well understood, but there is increasing evidence that they inhibit the action of transcription factors such as AP-1 and NF-kappaB [114]. Glucocorticoids are potent inhibitors of the activation of NF-kappaB, which may account for most of their anti-inflammatory actions [115]. Glucocorticoids are effective inhibitors of NF-kappaB, but they have endocrine and metabolic side effects when given systemically [115]. Activation of NF-kappaB, for example by cytokines, is blocked by glucocorticoids. Glucocorticoid-receptor complexes bind to the p65 subunit of NF-kappaB, and this prevents NFkappaB activation of the inflammatory genes. Synthesis of nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, alpha (IkBα) is stimulated by the binding of glucocorticoidglucocorticoid-receptor complexes to a glucocorticoid response element in the promoter region of the IkBα gene [115]. It may be unwise to block the activation of NF-kappaB for prolonged periods, because the factor plays such a critical part in the immune response and other defensive responses [115]. Part I revealed a wide range and number of cellular and tissue/hormone processes that can be measured and manipulated. Part II describes clinical level measures and interventions.

PART II: CLINICAL CONSEQUENCES AFFECTING SPECIFIC BRAIN SYSTEMS Neuroanatomical Considerations Evidence of anatomical brain damage has long been a hallmark in diagnosis of brain injury. For the chronic post-concussion patient this has historically been elusive. Researchers consider concussion to be the result of mechanical trauma to the head or neck that leads to functional impairment without overt structural damage [115]. This results in no gross changes or brain abnormalities seen on imaging [116,117]. A traumatic head injury mechanism combined with a lack of positive findings on imaging is the primary diagnostic scenario. This, the symptom checklists, the opinion of a physician familiar with the patient and ongoing observation by family, coaches or the patient themselves, are standard diagnostic tools. These are commonly used strategies in identifying the presence of concussion and are relied upon for clinical, return to activity and legal purposes in most settings [118,119,120,121]. Current neuroscience has reached a point where evidence of the neuroanatomical consequences of concussion can be identified. The initiating structural damage appears to result from stretching and

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disruption of neuronal, glial and axonal cell membranes; while cell bodies and myelin sheaths are less affected [122,123]. These injuries are microscopic, involving cellular structures, as well as microvasculature and the blood-brain barrier. Although techniques to identify microscopic structural damage are not readily available to clinicians, the pursuit of this information is clinically relevant. Investigators looking at extent of tissue damage using advance imaging techniques have been able to use the data in predicting individuals who will likely have an uncomplicated recovery from concussion versus those who progress to chronic post-concussion syndrome [124] Postmortem studies of individuals who survived concussion and later died due to apparently unrelated circumstances have provided early evidence of microscopic brain damage in concussion. These types of studies, performed as early as the 1950’s and 1960’s, continue to provide evidence of damage post-concussion. Historically, the overall impression has been that post-concussion brain damage occurs diffusely in the white matter [155,126] More recently diffusion tensor imaging, tractography, perfusion studies and functional neuroimaging have been utilized in identifying areas of damage in individuals with mild traumatic brain injury. These advanced neuroimaging techniques support the notion of axonal and vascular lesions [128,129,130, 131]. Additionally, a mouse model of concussion has provided evidence that degeneration in the gray matter, involving extensive dendrite degeneration and synapse reduction with very minimal cell death, may be a major neuropathological feature in mTBI [132]. Chronic head injury at the concussive or subconcussive level has been associated with morphological change in the brain that is similar to those seen in Alzheimer’s disease and other neurodegenerative disorders. Cortical degeneration with neurofibrillary tangles, neurite heads, neuronal dropout and accumulation of Tau and transactive response DNA-binding protein 43 (TDP-34) proteins are found the human brain chronically after repetitive concussion and subconcussion trauma [133,134,135,136]

Figure 9. Neuroanatomical damage at the cellular level © Joel Brandon Brock 2013.

Work has been done to identify which regions of the brain are most often affected in concussion. In severe and moderate brain injury the location of damage is fairly consistent with proximity to mechanical trauma, contrecoup deformation, areas of the brain in contact with more rigid structures and those displaced by swelling [137,138]. For the chronic post-concussion patient there is less predictability in the specific region of damage. Medial frontal, dorsolateral frontal, occipital, subcortical and corpus callosum have all been reported as damaged in this population [113,


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139,140,141] In a subset of chronic post-concussion patients with depression, the frontal and temporal white matter have been identified as injured [142]. Corticocerebellar circuitry disruption has been found as well [115,124,143] Structural involvement of the thalamus was inferred using graph theory analysis and proposed as a useful marker in identifying mTBI [144]. Sheering stresses around the brainstem have been investigated by recreating a series of recorded head to head collisions in football and analyzing the threshold of force that may be necessary to produce a lasting concussion syndrome [145]. Additionally, the tissue stressor from concussive trauma has been associated with vascular damage to both the small vessels and integrity of the blood-brain barrier [146,147] The immediate trauma associated concussion results in a host of other changes at the cellular and molecular levels. They include involvement of the immune and endocrine systems. They affect the metabolism and biochemistry of the brain, as well as distant sites in the body [148,149]. There is very strong and growing evidence that both the immediate and ongoing “non-anatomical” consequences are associated with the vast majority of the difficulties faced by the post-concussion patient [150,151,152]. Visual and Vestibular Dysfunction in the mTBI Patient Beyond neurocognitive testing, many additional methodologies have been evaluated to assess the consequences and natural history of mTBI. These forms of functional analysis offer new windows for the clinician to assess the severity of mTBI and monitor response to treatment and level of recovery. Further, they imply promising new avenues of treatment for the mTBI patient. Vestibular dysfunction in mTBI Vestibular impairment is a common consequence of mTBI. As many as 65% of mTBI pateints will experience some form of vestibular dysfunction during their recovery [153]. Vestibular lesions have been shown to directly produce central inflammatory changes. Unilateral vestibular deafferentation has been demonstrated to result in significant microglial and astroglial activation in the vestibular nuclei [154]. Rat models of vestibular lesion via arsanilate transtympanic injection manifest significant central vestibular inflammatory changes. Elevations in the number of tumor necrosis factor alpha immunoreactive (TNF-alpha-Ir) cells in the bilateral medial and inferior vestibular nuclei can be seen as early as 4 hours after vestibular lesion, with NF-kappaB upregulation following 8 hours after the lesion, and manganese superoxide dismutase (MnSOD) elevation after 24 hours. Similar changes have been demonstrated in rat models of mechanical unilateral vestibular deafferentation [140]. As a consequence, thorough evaluation and management of vestibular dysfunction in mTBI patients may show promise as a means of limiting central inflammatory processes. Benign paroxysmal positional vertigo is the most common form of posttraumatic vertigo [139]. As this is a relatively straightforward condition to evaluate via Dix-Hallpike testing, and manage with canalith repositioning maneuvers, Dix-Hallpike testing should be employed in all mTBI patients with vestibular complaints [139]. Sherer et al. evaluated blast-induced mTBI patients reporting persistent dizziness via videonystagmography (VNG), rotational chair, cervical vestibular-evoked myogenic potentials, computerized dynamic posturography, and self-report measures [155]. Evidence of central and peripheral vestibular dysfunction was identified at a higher frequency in symptomatic patients. Abnormal nystagmus or oculomotor findings were present in 50% of symptomatic subjects. Rotational chair testing found evidence of peripheral vestibulopathy in 25% of symptomatic patients, and central vestibular pathology in 17% of symptomatic subjects [141]. Computerized dynamic posturography (CDP) has been proposed as a means to monitor the status of vestibular function. CDP testing assesses the patient’s ability to maintain postural stability against a standardized series of balance and postural challenges. Approximate entropy (ApEn), a measurement of how likely a postural correction is to recur within a time series, is thought to decrease with mTBI

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[156]. A person swaying in a predictable manner represents a lowered capacity to adapt to subtle changes in environmental stability, and thus lower postural control dynamics. ApEn has been shown to decrease with mTBI, and shifts in stabilization strategies toward greater anterior-posterior and decreased medial-lateral control [142]. This raises the likelihood that concussed patients have a chronic risk of falls without appropriate neurorehabilitation. Treven et al. demonstrated the utility of CDP to assess and quantify balance deficits in ambulatory mTBI. They revealed that standardized functional measures utilized for determining release from acute mTBI rehabilitation settings do not consistently and specifically assess balance. Many patients that have reached discharge level from acute rehab setting maintain a high degree of balance deficit [157]. This persistent instability raises the risk of reinjury and further trauma. Assessment of vestibular dysfunction has been effectively demonstrated through the use of vestibular-visual-cognitive interaction tasks [158]. Changes in static visual acuity, perception time, target acquisition, target following (TF), dynamic visual acuity (DVA), and gaze stabilization have been demonstrated in blast-induced mTBI patients. Rehabilitation procedures involving the vestibuloocular reflex, cervico-ocular reflex, and depth perception, as well as somatosensory balance exercises, dynamic gait, and aerobic function exercises have been employed to effectively manage these systems [144]. Vestibular rehabilitation therapy (VRT) has been shown to be helpful for patients with persistent dizziness and balance dysfunction for whom gait and balance dysfunction did not resolve with rest alone [159]. Subjective dizziness and objective measures of gait and balance have shown to be improved after protocols of rehabilitation involving gaze stabilization exercises, standing and dynamic balance exercises, and canalith repositioning maneuvers where indicated [145]. Similarly, target following and dynamic visual acuity scores returned to normative levels after an 8-week vestibular physical therapy protocol. Gaze stabilization similarly improved after 8 weeks of VRT [144].


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Figure 10. mTBI progression to visual and vestibular dysfunction © Joel Brandon Brock 2013.

Visual Dysfunction in mTBI Visual dysfunction has been shown to be extremely prevalent in the mTBI population. Ciuffreda et al. assessed for frequency of occurrence of oculomotor dysfunction in TBI, considering accommodation, version, vergence, strabismus, and cranial nerve palsy. They found that oculomotor dysfunction is the norm in TBI [160]. Convergence insufficiency (CI) has been shown to be present in roughly 9% of the visually symptomatic TBI population without simultaneous vestibular dysfunction, saccade or pursuit dysfunction, cranial nerve palsies, visual field deficits, visuospatial neglect, or nystagmus. In many cases it appears that CI may occur in the absence of obvious dysfunction in visual and vestibular systems, rendering a thorough evaluation even more necessary [161]. The neural substrates of eye movements involve diffuse networks including the frontal lobes, parietal lobes, and cerebellar cortices. These systems also serve within networks that facilitate executive functions and higher cognitive experience. Impairments of eye movements have thus been demonstrated to have considerable clinical utility in both diagnosing and rehabilitating the mTBI patient. TBI patients demonstrate aberrancies in predictive components of smooth pursuit eye movements [162]. These deficits in average target prediction, eye position error, and eye position variability positively correlated with executive function and attentional measures on the California Verbal Learning test (CVLT-II), without apparent reduction in IQ noted on the Weschler Abbreviated Scale of Intelligence (WASI). Impairment of predictive smooth pursuit eye movements thus may be a sensitive indicator of impaired attention processing. Smooth pursuit movements coupled with target blanking, wherein the target being pursued is intermittently obscured, necessitates the generation of greater predictive eye movements [163]. This process requires greater reliance on brain regions involved in cognitive processing. Deficits in CVLTII performance have been shown to more positively correlate with oculomotor variability during target blanking than during target tracking [163]. Maruta et al. demonstrated the presence of diffuse axonal injury (DAI) within the frontal lobes in mTBI via diffusion tensor imaging. Fractional Anisotropy indicates frequent involvement of the anterior corona radiata, the uncinate fasciculus, the genu of the corpus callosum, and the cingulum bundle. They compared various measures of eye movement performance to fractional anisotropy (FA) and diffusion tensor imaging (DTI), as well as to neurocognitive tests. Variability of gaze position errors during predictive smooth pursuit proved to be a sensitive measure that correlated with neurocognitive testing data and DTI findings. The degree of variability correlated with the mTBI spectrum severity [164]. They determined that performance variability during predictive visual tracking is a valid and useful indicator of damage to frontal white matter tracts, and is similarly indicative of impaired cognitive function [164]. Similar correlations have been shown between dysfunction in saccade eye movements and measures of neurocognition. Mulhall indicated that bedside tests of saccades utilizing infrared oculography (IRO) produced saccadic impairment data that positively correlated with impairments on neurocognitive tests [165]. Recovering TBI patients were shown to have decreased rates of self-paced saccades, impaired ability to suppress inappropriate saccades in single memory-guided and antisaccade tests, prolonged saccadic latencies, and hypometric saccades in visually guided reflex saccade tests. This implies that IRO testing should be part of any mTBI management protocol [165]. Increased duration of reflexive saccade latencies has also been shown to be present in mTBI [166]. Portable saccadometry has been utilized to evaluate boxers pre- and post-bouts. Latency distributions have been shown to be significantly altered after blows to the head, with these effects

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reversible over a short period of time. Latency requires cortical decision mechanisms, and is directly affected by processes that affect cerebral function [166]. Drew et al. investigated the relationship between dysfunctional visuospatial orientation processes and difficulty with orienting attention. Saccadic targets were presented with varying temporal gaps and reaction times were assessed. They found that mTBI patients demonstrated significantly longer saccadic reaction times than controls when the time gap between saccades was short, but not when the temporal gap was long. Shifts in attention require disengagement from the point of fixation, both cognitively and visually. This process appears impaired in mTBI [167]. Heitger found that eye movement function was impaired in post-concussion syndrome, with eye movement deficits found on measures relating to motor functions executed under both conscious and semi-conscious control, as well as on several eye movement functions that are beyond conscious control and indicative of sub-cortical brain function [168]. They demonstrated specific deficits in antisaccade performance, a task that in non-mTBI individuals that requires attentional focus, inhibitory control, working memory, and the ability to generate voluntary goal-directed behavior [169]. They recommended that eye movement testing be utilized with post-concussion syndrome patients to evaluate for incomplete recovery of function [169]. Given the interaction between visual and vestibular function within the maintenance of balance and gait, it is perhaps unsurprising that TBI patients demonstrate abnormal caloric irrigation and optokinetic circularvection testing, as well as lower anterior and posterior and higher medial and lateral center of mass displacements and velocities during gait assessment [170]. Rehabilitation of eye movement dysfunction has been shown to be effective in mTBI patients. Ciuffreda et al. demonstrated a 90% rate of improvement from oculomotor rehabilitation, with reduction in both symptoms and objective findings that persisted at a 2- to 3-month follow-up, demonstrating both the efficacy of optometric rehabilitation and significant neural plasticity in mTBI patients [171]. Novel forms of rehabilitation have been shown to have efficacy in treating the visual and vestibular dysfunction, and may hold promise in the treatment of those same dysfunctions in mTBI patients. Optokinetic stimulation has been shown to activate areas often involved in mTBI, including the prefrontal cortex/frontal eye fields, areas involved in generation of saccades, and modulation of the parieto-insular vestibular cortex, an area involved in visual-vestibular interaction [172]. Repetitive optokinetic stimulation has been shown to be useful for rehabilitation of vestibular deficits and in causing adaptive changes in locomotion in healthy subjects [173,174,175]. Optokinetic stimulation has shown efficacy restoration of mobility in acute stroke patients [176,177]. Vagal nerve stimulation has been shown to be effective in limiting the vasogenic edema that develops secondary to the disruption of the blood-brain barrier in TBI, thus limiting central inflammation and neuronal damage [60,178]. Within a virtual reality environment, combinations of optokinetic stimulation and habituation, visual and physical perturbations, and postural stability exercises have been shown to decrease visual and physical motion intolerance and impairment in static balance [179]. Further research is needed with respect to these interventions. Given the interaction between the visual and vestibular systems, the frequency of impairment noted in these systems, and their potential influence on central inflammatory processes, thorough and sensitive evaluation of these systems is a prerequisite for effective management of mTBI. Neuropsychological Effects: Multi-Systems Approach to Persistent Post-Concussion Syndrome (PPCS) Neurocognitive effects of concussion/TBI are unpredictable. Research to date has given us a wealth of information concerning the mechanism of injury, acute pathophysiology, chronic pathophysiology, imaging, neuro-immune and HPA axis contribution. With all of this information there are still few tools available for clinicians to diagnose the extent of cognitive impact and even


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fewer tools available for prognosis and treatment. Why is it that some who have suffered more severe TBI have complete resolution of cognitive symptoms but those with a relatively mild history of injury have such great difficulty with executive function, attention, anxiety, pain, fatigue, and depression? This leaves clinicians with little choice but to react to symptoms as they occur, thus allowing the potential harm of unrecognized, undiagnosed chronic pathophysiology and dysfunction to fester. The treatment for persistent post-concussion syndrome (PPCS) due to mTBI does not address the cause, and mostly consists of rest and cognitive behavioral therapy with limited results for those suffering from PPCS [180]. Medications to treat concomitant depression, attention deficit and anxiety are often prescribed. There are two current sets of research criteria for the post-concussive disorder: the International Classification of Diseases, 10th Edition (ICD-10), and the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV). According to the DSM-IV the individual with postconcussion syndrome will have trouble paying attention, concentrating, changing focus from one activity to another, performing more than one mental activity at the same time, remembering information, and learning new information. Three or more of the following symptoms occur after the trauma and last at least 3 months: fatigue; insomnia; headache; vertigo or dizziness; anger that occurs without a good reason; anxiety, depression, or mood swings; and personality changes such as inappropriate behavior, apathy, or lack of spontaneity. The impairment represents a significant decline from pre-trauma functioning and causes significant difficulty with school or workplace performance. According to the ICD-10, a person must have a history of “head trauma with loss of consciousness” preceding the onset of symptoms by a period of up to 4 weeks and at least three of six symptom categories. These include:      

Headaches, dizziness, general malaise, excessive fatigue, or noise intolerance. Irritability, emotional lability, depression, or anxiety. Subjective complaints of concentration or memory difficulty. Insomnia. Reduced tolerance to alcohol. Preoccupation with these symptoms and fear of permanent brain damage.

The ICD-10 criteria do not require “objective” evidence of cognitive problems. Both models attempt to clearly state the symptoms and parameters for diagnosis, however they do not offer much of a direction for understanding pathophysiology once the diagnosis has been made. A clear understanding of the pathophysiology as it relates to multiple systems and circuits will guide research toward better models of prognosis, care and prevention. Complete or nearly complete recovery from concussion occurs in a timely manner in the majority of individuals, however there is a minority of those who have symptoms that persist for months to years [181]. The research is not clear as to how to predict who will be more likely to experience chronic symptoms. Bigler et al. described PPCS as it is related to structural damage to specific predictable or likely brain regions impacted by brain injury using biomechanical models. Recent advances in imaging using DTI have detected axonal damage previously undetectable. The anatomical regions most likely to suffer structural damage with concussion include the posterior frontal lobe, medial temporal lobe, midbrain structures, fornix, hypothalamus, pituitary, cerebral peduncle, entorhinal cortex and hypothalamus. So, within a few centimeters are critical brain structures that, if affected, could represent the structural basis to many symptoms associated with concussion [182]. Rao and Lyketsos indicate that the PPCS nomenclature is too vague and that the more accurate description is ‘frontotemporal syndrome’ as this better describes the regions most affected by injury. There is considerable evidence linking the vestibular system and objective findings utilizing digital

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posturography and videonystagmography for ocular involvement and precise evaluation of central circuits involved [183] We recognize that the same symptoms classified as PPCS can be seen in people without history of concussion or trauma [184]. This is possibly involving the same pathophysiological characteristics with a different etiology. The methodological quality of neuropsychological research for concussion, although plentiful over the past decade, has lacked scientific rigor [185]. When looking at the confounding factors that must be considered in the design of PPCS research, Bigler notes that the major symptoms of PPCS; fatigue, sleep disorder, headache, dizziness/vertigo, irritability, affective lability, anxiety, apathy and personality changes, share such great overlap that exist with other psychiatric disorders such as depression [182] [182].

Figure 11. Development of mental health problems in the context of mTBI milieu © Joel Brandon Brock 2013.

It appears, as is noted in the research cited above, that PPCS shares a great deal of similarity with depression, anxiety, attention deficit disorder (ADD) and OCD. The common thread that holds PPCS, depression, anxiety, OCD and ADD may be a chronic, immune mediated, inflammatory process also known as immuno-excitotoxicity as well as shared anatomical circuitry [12]. Research conducted which points out the effect peripheral musculoskeletal injury has on cognition is similar to that seen with concussion, indicating that injury itself, regardless of anatomical location can affect objective test scores previously attributed to concussion alone. Thus a narrow assessment of pre- and post-injury neuropsychological scores should be avoided [185]. This finding may indicate that systemic inflammation occurring outside the CNS may play a role in the function of cognitive circuitry. There appear to be significant shortcomings in conceiving PPCS, mTBI and chronic TBI as a wholly neuropsychological condition requiring a neuropsychological approach to researching treatment, diagnosis and prognosis. A comprehensive model that addresses multi-system physiology including but not limited to sensorimotor processing and neuro-immune function is likely to emerge. The probability of chronic immune inflammatory processes being involved and the likelihood of compromised neural circuitry may be discovered with sensitive analysis of sensorimotor function of neural circuitry shared by cognitive and behavioral centers. A research model can be crafted that incorporates a multisystem approach to function as opposed to simply ameliorating symptoms. With


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this in mind the direction research can take regarding care must be tangible, quantifiable and very different from rest and cognitive therapy. Research needs to address sensorimotor function of specific circuits underlying cognitive and behavioral symptoms within PPCS (i.e., vestibular aspects of posture and ocular function). Recognizing the pathophysiology as it relates to past medical history, family history, genetics, multiple system involvement and systemic peripheral contributions to central nervous system (CNS) function will yield new directions in research, preventive and post-injury care. Research in several disciplines has indicated that blending the study of the evolutionarily conserved, shared underlying neural circuitry common to the visual, vestibular, memory, immune and autonomic regulatory nuclei have been fruitful and are needed if we are to make progress in chronic brain injury outcomes. There appear to be significant shortcomings in conceiving PPCS, mTBI and chronic TBI as a wholly neuropsychological condition requiring a neuropsychological approach to researching treatment, diagnosis and prognosis. A comprehensive model that addresses multi-system physiology including but not limited to sensorimotor processing and neuro-immune function is likely to emerge, which addresses compromised cognitive and behavioral neural circuits that reciprocally affect each other’s frequency of firing. Generating productive clinical questions to investigate must be a disciplined thinking process starting at the molecular level, progressing up through the cellular, receptor, tissue, and sensorimotor, visual and vestibular systems. Only after this Socratic querying can the collection of quantifiable evidence begin and have meaning. Further, both laboratory based neurochemical-immune assessments as well as comprehensive functional neurological examination must be collected and considered. This will necessarily lead to more precise rehab methods and chemical management of chronic brain injuries.

Figure 12. Overview of clinical Socratic thinking in chronic brain injury assessment and care © Joel Brandon Brock 2013.

CONCLUSION Many factors in a given patient’s physiology can influence the outcome of TBI or mTBI, yielding widely divergent potential outcomes from head trauma, including PPCS. The clinician’s ability to understand a given patient depends upon skilled assessment and appreciation of these variables, their potential interconnections, and their impact at cellular and systems levels. An increasing need for strong generalist thinking is therefore required in order to comprehend and utilize the bounty of recent research, and to avoid the traps of heuristic decision-making and overemphasis on specialized niches in both the research and clinical settings.

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Recognizing pathophysiology as it relates to past medical history, family history, genetics, multiple system involvement and systemic peripheral contributions to central nervous system (CNS) function will yield new directions in research, preventive and post-injury clinical care. Research in several disciplines has indicated that blending the study of the evolutionarily conserved, shared underlying neural circuitry common to the visual, vestibular, memory, immune and autonomic regulatory nuclei have been fruitful. Their expansion and integration are needed if we are to make progress in improving chronic brain injury outcomes. In both research and clinical settings, careful examination of many wide-ranging patient measures must be integrated in order to progress, including reflexive eye movements, hormone panels, sensorimotor changes, immune and inflammatory markers, mental and emotional states, and other factors required to appreciate each patient’s uniqueness. History taking will need to expand to include lifestyle factors previously thought unrelated. The health status of individuals pre-concussion will be a significant factor in determining PPCS risk in any individual. In the research setting, accounting for physiological variables that can impact TBI and mTBI outcomes is essential in appreciating potential non-homogeneity of patient populations enrolled in a given study. In the clinical setting, accounting for the same physiological variables creates the opportunity to identify key clinical targets that can markedly improve outcomes or, if ignored, stall progress. Once identified, these clinical targets must be addressed with best-matched methodologies, not all of which will be pharmacological. Understanding the post-injury, and ideally the pre-injury status of these patients, utilizing outcome-based multifactorial neurological assessment and treatment are key in the emerging path for effective concussion care.

REFERENCES [1]

Brown GC, Neher JJ. Inflammatory neurodegeneration and mechanisms of microglial killing of neurons. Mol. Neurobiol. 2010;41:242-247. [2] Griffiths MR, Gasque P, Neal JW. The Multiple Roles of the Innate Immune System in the Regulation of Apoptosis and Inflammation in the Brain. J. Neuropathol Exp Neurol. 2009;68(3):217-226. [3] Biber K, Neumann H, Inoue K, Boddeke HW. Neuronal ‘On’ and ‘Off’ Signals Control Microglia. Trends Neurosci. 2007;30(11):596-602. [4] Neumann H. Control of Glial Immune Function by Neurons. Glia. 2001;36:191-199. [5] Neumann H, Kotter MR, Franklin RJ. Debris clearance by microglia: an essential link between degeneration and regeneration. Brain. 2009;132(Pt 2):288-95. [6] Wraith DC, Nicholson LB. The adaptive immune system in diseases of the central nervous system. J. Clin. Invest. 2012;122(4):1172-9. [7] Schwartz M, Shechter R.Systemic inflammatory cells fight off neurodegenerative disease. Nat Rev. Neurol. 2010;6(7):405-10. [8] Yacoubian S, Serhan CN. New endogenous anti-inflammatory and proresolving lipid mediators: implications for rheumatic diseases. Nat. Clin. Pract Rheumatol. 2007;3(10):570-9. [9] Dilger RN, Johnson RW. Aging, microglial cell priming, and the discordant central inflammatory response to signals from the peripheral immune system. J. Leukoc Biol. 2008;84(4):932-9. [10] Mangano EN, Hayley S.Inflammatory priming of the substantia nigra influences the impact of later paraquat exposure: Neuroimmune sensitization of neurodegeneration. Neurobiol Aging. 2009;30(9):1361-78.


247

[11] Block ML, Zecca L, Hong JS. Microglia-mediated neurotoxicity: uncovering the molecular mechanisms. Nat Rev Neurosci. 2007;8(1):57-69. [12] Blaylock RL, Maroon J. Immunoexcitotoxicity as a central mechanism in chronic traumatic encephalopathy – A unifying hypothesis. Surg. Neurol Int. 2011;2:107. [13] Cunningham C, Campion S, Lunnon K, Murray CL, Woods JF, Deacon RM, Rawlins JN, Perry VH. Systemic Inflammation Induces Acute Behavioral and Cognitive Changes and Accelerates Neurodegenerative Disease. Biol. Psychiatry. 2009;65(4):304-12. [14] Perry VH, Cunningham C, Holmes C.Systemic infections and inflammation affect chronic neurodegeneration. Nat. Rev. Immunol. 2007 Feb;7(2):161-7. [15] Cunningham C, Wilcockson DC, Campion S, Lunnon K, Perry VH. Central and Systemic Endotoxin Challenges Exacerbate the Local Inflammatory Response and Increase Neuronal Death during Chronic Neurodegeneration. J. Neurosci. 2005;25(40):9275-84. [16] Perry VH, Nicoll JA, Holmes C. Microglia in neurodegenerative disease. Nat. Rev. Neurol. 2010 Mar;6:193-201. [17] Meisel C, Schwab JM, Prass K, Meisel A, Dirnagl U.Central nervous system injury-induced immune deficiency syndrome. Nat. Rev. Neurosci. 2005 Oct;6(10):775-86. [18] Shaw NA. The neurophysiology of concussion. Prog. Neurobiol. 2002;67(4):281-344. [19] Johnson VE, Stewart W, Smith DH. Traumatic brain injury and amyloid-β pathology: a link to Alzheimer's disease? Nat. Rev. Neurosci. 2010;11(5):361-70. [20] Henry LC, Tremblay S, Leclerc S, Khiat A, Boulanger Y, Ellemberg D, Lassonde M. Metabolic changes in concussed American football players during the acute and chronic post-injury phases. BMC Neurol. 2011;11:105. [21] Das M, Mohapatra S, Mohapatra SS. New perspectives on central and peripheral immune responses to acute traumatic brain injury. J. Neuroinflammation. 2012;9:236. [22] Yun J, Gaivin RJ, McCune DF, Boongird A, Papay RS, Ying Z, Gonzalez-Cabrera PJ, Najm I, Perez DM. Gene expression profile of neurodegeneration induced by alpha1B-adrenergic receptor overactivity: NMDA/GABAA dysregulation and apoptosis. Brain. 2003;126(Pt 12):2667-81. [23] Marambaud P, Dreses-Werringloer U, Vingtdeux V. Calcium signaling in neurodegeneration. Mol. Neurodegener. 2009;4:20. [24] Doble A. The role of excitotoxicity in neurodegenerative disease: implications for therapy. Pharmacol Ther. 1999;81(3):163-221. [25] Malkus KA, Tsika E, Ischiropoulos H. Oxidative modifications, mitochondrial dysfunction, and impaired protein degradation in Parkinson's disease: how neurons are lost in the Bermuda triangle. Mol. Neurodegener. 2009;4:24. [26] Green DR, Galluzzi L, Kroemer G. Mitochondria and the autophagy-inflammation-cell death axis in organismal aging. Science. 2011;333(6046):1109-12. [27] Mizushima N, Levine B, Cuervo AM, Klionsky DJ.Autophagy fights disease through cellular self-digestion. Nature. 2008;451(7182):1069-75. [28] Babikian T, Prins ML, Cai Y, Barkhoudarian G, Hartonian I, Hovda DA, Giza CC. Molecular and physiological responses to juvenile traumatic brain injury: focus on growth and metabolism. Dev Neurosci. 2010;32:431-441. [29] Fehm HL, Kern W, Peters A. The selfish brain: competition for energy resources. Prog. Brain Res. 2006;153:129-140. [30] Hyder F, Rothman DL, Shulman RG. Total neuroenergetics support localized brain activity: Implications for the interpretation of fMRI. PNAS. 202;99:10771-10776. [31] Shah K, DeSilva S, Abbruscato T. The Role of Glucose Transporters in Brain Disease: Diabetes and Alzheimer’s Disease. Int. J. Mol Sci. 2012;13:12629-12655.

248


[32] Prieto R, Tavazzi B, Taya K, Barrios L, Amorini A, Di Pietro V, Marmarou C. Brain energy depletion in a rodent model of diffuse traumatic brain injury is not prevented with administration of sodium lactate. Brain Res. 2011;1404:39-49. [33] Vemula S, Roder K E. A functional role for sodium-dependent glucose transport across the blood brain barrier during oxygen glucose deprivation. J. Pharmacol Exp. Ther. 2009;328(2)487-495. [34] Eskandari S, Wright EM, Loo D. (2005, March) Kinetics of the reverse mode of the Na+/glucose cotransporter. J. Membr Biol. 2005;204(204):23-32. [35] Moreno A, Jego P, Cruz F, Canals S. Neurophysiological, metabolic and cellular compartments that drive neurovascular coupling and neuroimaging signals. Front Neuroenergetics. 2013;5:3. [36] Shen J. Modeling the glutamate-glutamine neurotransmitter cycle. Front Neurogenetics. 2013;5:1-13. [37] Caprette DR. Substrate Oxidation: Krebs Reactions. 2005. http://www.ruf.rice.edu /~bioslabs/studies/mitochondria/mitokrebs.html [38] Stobart JL, Anderson CM. Multifunctional role of astrocytes as gatekeeper of neuronal energy supply. Front Cell Neurosci. 2013;7:38. [39] Giza CC, Hovda DA. The neurometabolic cascade of concussion. J. Ath Train. 2001;36(3):228235. [40] Lavoie S, Allaman I, Petit J, Do KQ, Magistretti PJ. Altered glycogen metabolism in cultured astrocytes from mice with chronic glutathione deficit; relevance for neuroenergetics and schizophrenia. PloS One. 2011;6(7):e22875 [41] Yan EB, Hellewell SC, Bellander B, Agyapomaa DA, Morganti-Kossmann M. Post-traumatic hypoxia exacerbates neurological deficit, neuroinflammation and cerebal metabolism in rats with diffuse traumatic brain injury. J. Neuroinflammation. 2011;8:147. [42] Ives JC, Alderman M, Stred SE. Hypopituitarism after multiple concussions: a retrospective case study in an adolescent male. J. Ath Train 2007;42(3):431-439. [43] Agha A, Rogers B, Sherlock M, O’Kelly P, Tormey W, Phillips J, Thompson CJ. Anterior pituitary dysfunction in survivors of traumatic brain injury. J. Clin. Endocrinol. Metab. 2004;89(10):4929-4936. [44] Oliveira C, Meneguz-Mreno RA, Aguiar-Oliviera MH, Barreto-Filho JA. Emerging role of the GH/IGF-I on cardiometabolic control. Arq Bras Cardiol. 2011;97(5): 434-439. [45] Chang L. Brain responses to visceral and somatic stimuli in irritable bowel syndrome: a central nervous system disorder? Gastroenterol. Clin. North Am. 2005;34(2):271-9. [46] Hang CH, Shi JX, Li JS, Wu W, Li WQ, Yin HX. Levels of vasoactive intestinal peptide, cholecystokinin and calcitonin gene-related peptide in plasma and jejunum of rats following traumatic brain injury and underlying significance in gastrointestinal dysfunction. World J. Gastroenterol. 2004;10(6):875-80. [47] Kwan CL, Diamant NE, Pope G, Mikula K, Mikulis DJ, Davis KD. Abnormal forebrain activity in functional bowel disorder patients with chronic pain. Neurology. 2005;65(8):1268-77. [48] Bansal V, Costantini T, Ryu SY, Peterson C, Loomis W, Putnam J, Elicieri B, Baird A, Coimbra R. Stimulating the central nervous system to prevent intestinal dysfunction after traumatic brain injury. J. Trauma. 2010;68(5):1059-64. [49] Bansal V, Costantini T, Kroll L, Peterson C, Loomis W, Eliceiri B, Baird A, Wolf P, Coimbra R. Traumatic brain injury and intestinal dysfunction: uncovering the neuro-enteric axis. J. Neurotrauma. 2009;26(8):1353-9. [50] Feighery L, Smyth A, Keely S, Baird AW, O'Connor WT, Callanan JJ, Brayden DJ. Increased intestinal permeability in rats subjected to traumatic frontal lobe percussion brain injury. J. Trauma. 2008;64(1):131-7;discussion 137-8.


249

[51] Maes M, Kubera M, Leunis JC. The gut-brain barrier in major depression: intestinal mucosal dysfunction with an increased translocation of LPS from gram negative enterobacteria (leaky gut) plays a role in the inflammatory pathophysiology of depression. Neuro Endocrinol Lett. 2008;29(1):117-24. [52] Leclercq S, Cani PD, Neyrinck AM, Stärkel P, Jamar F, Mikolajczak M, Delzenne NM, de Timary P. Role of intestinal permeability and inflammation in the biological and behavioral control of alcohol-dependent subjects. Brain Behav. Immun. 2012;26(6):911-8. [53] Lenz A, Franklin GA, Cheadle WG. Systemic inflammation after trauma. Injury. 2007;38(12):1336-45. [54] Hang CH, Shi JX, Li JS, Wu W, Yin HX. Alterations of intestinal mucosa structure and barrier function following traumatic brain injury in rats. World J. Gastroenterol. 2003;9(12):2776-81. [55] Santos A, Gonçalves P, Araújo JR, Martel F. Intestinal permeability to glucose after experimental traumatic brain injury: effect of gadopentetate dimeglumine administration. Basic Clin. Pharmacol Toxicol. 2008;103(3):247-54. [56] Hang CH, Shi JX, Li JS, Li WQ, Yin HX. Up-regulation of intestinal nuclear factor kappa B and intercellular adhesion molecule-1 following traumatic brain injury in rats. World J. Gastroenterol. 2005;11(8):1149-54. [57] Hang CH, Shi JX, Li JS, Li WQ, Wu W. Expressions of intestinal NF-kappaB, TNF-alpha, and IL-6 following traumatic brain injury in rats. J. Surg. Res. 2005;123(2):188-93. [58] Ling HP, Li W, Zhou ML, Tang Y, Chen ZR, Hang CH. Expression of intestinal myeloid differentiation primary response protein 88 (Myd88) following experimental traumatic brain injury in a mouse model. J. Surg. Res. 2013;179(1):e227-34. [59] Fukuda K, Tanno H, Okimura Y, Nakamura M, Yamaura A. The blood-brain barrier disruption to circulating proteins in the early period after fluid percussion brain injury in rats. J. Neurotrauma. 1995;12(3):315-24. [60] Lopez NE, Krzyzaniak MJ, Costantini TW, Putnam J, Hageny AM, Eliceiri B, Coimbra R, Bansal V. Vagal nerve stimulation decreases blood-brain barrier disruption after traumatic brain injury. J. Trauma Acute Care Surg. 2012;72(6):1562-6. [61] Szmydynger-Chodobska J, Strazielle N, Gandy JR, Keefe TH, Zink BJ, Ghersi-Egea JF, Chodobski A. Posttraumatic invasion of monocytes across the blood-cerebrospinal fluid barrier. J. Cereb. Blood Flow Metab. 2012;32(1):93-104. [62] Shlosberg D, Benifla M, Kaufer D, Friedman A. Blood-brain barrier breakdown as a therapeutic target in traumatic brain injury. Nat. Rev. Neurol. 2010;6(7):393-403. [63] Baguley IJ, Heriseanu RE, Cameron ID, Nott MT, Slewa-Younan S. A critical review of the pathophysiology of dysautonomia following traumatic brain injury. Neurocrit Care. 2008;8(2):293-300. [64] Kirk KA, Shoykhet M, Jeong JH, Tyler-Kabara EC, Henderson MJ, Bell MJ, Fink EL. Dysautonomia after pediatric brain injury. Dev. Med. Child Neurol. 2012;54(8):759-64. [65] Hendricks HT, Heeren AH, Vos PE. Dysautonomia after severe traumatic brain injury. Eur. J. Neurol. 2010;17(9):1172-7. [66] Baguley IJ, Heriseanu RE, Nott MT, Chapman J, Sandanam J. Dysautonomia after severe traumatic brain injury: evidence of persisting overresponsiveness to afferent stimuli. Am. J. Phys. Med. Rehabil. 2009;88(8):615-22. [67] Nampiaparampil DE. Prevalence of chronic pain after traumatic brain injury: a systematic review. JAMA. 2008;300(6):711-9. [68] Baguley IJ, Heriseanu RE, Felmingham KL, Cameron ID. Dysautonomia and heart rate variability following severe traumatic brain injury. Brain Inj. 2006;20(4):437-44.

250


[69] Hoarau X, Richer E, Dehail P, Cuny E. A 10-year follow-up study of patients with severe traumatic brain injury and dysautonomia treated with intrathecal baclofen therapy. Brain Inj. 2012;26(7-8):927-40. [70] Frisina PG, Kutlik AM, Barrett AM. Left-Sided Brain Injury Associated With More HospitalAcquired Infections During Inpatient Rehabilitation. Arch. Phys. Med. Rehabil. 2013;94(3):51621. [71] Esmaeili A, Dadkhahfar S, Fadakar K, Rezaei N. Post-stroke immunodeficiency: effects of sensitization and tolerization to brain antigens. Int Rev Immunol. 2012;31(5):396-409. [72] Anthony DC, Couch Y, Losey P, Evans MC. The systemic response to brain injury and disease. Brain Behav Immun. 2012;26(4):534-40. [73] Roquilly A, Lejus C, Asehnoune K. [Brain injury, immunity and infections]. Ann Fr Anesth Reanim. 2012;31(6):e97-100. [74] Kamel H, Iadecola C. Brain-immune interactions and ischemic stroke: clinical implications. Arch. Neurol. 2012;69(5):576-81. [75] Peng YP, Qiu YH, Qiu J, Wang JJ. Cerebellar interposed nucleus lesions suppress lymphocyte function in rats. Brain Res Bull. 2006;71(1-3):10-7. [76] Peng YP, Qiu YH, Chao BB, Wang JJ. Effect of lesions of cerebellar fastigial nuclei on lymphocyte functions of rats. Neurosci Res. 2005;51(3):275-84. [77] Ghoshal D, Sinha S, Sinha A, Bhattacharyya P. Immunosuppressive effect of vestibulocerebellar lesion in rats. Neurosci Lett. 1998;257(2):89-92. [78] Damir J. Are you in or out? Leukocyte, ion, and neurotransmitter permeability across the epileptic blood-brain barrier. Epilepsia. 2012;53(Suppl. 1):26-34. [79] Pan W, Stone KP, Hsuchou H, Manda VK, Zhang Y, Kastin AJ. Cytokine signaling modulates blood-brain barrier function. Curr. Pharm. 2011;17:336-338. [80] Tomkins O, Friedman O, Ivens S, Reiffurth C, Major S, Dreier JP, Heinemann U, Friedman A. Blood-brain barrier disruption results in delayed functional and structural alterations in the rat neocortex. Neurobiol Dis. 2007;25(2):367-377. [81] Kofuji P, Newman EA. Potassium buffering in the central nervous system. Neuroscience. 2004;129(4):1045-56. [82] Bansal V, Ryu SY, Lopez N, Allexan S, Krzyzaniak M, Eliceiri B, Baird A, Coimbra R. Vagal stimulation modulates inflammation through a ghrelin mediated mechanism in traumatic brain injury. Inflammation. 2012;35:214-220. [83] Naritoku DK, Terry WJ, Helfert RH. Regional induction of fos immunoreactivity in the brain by anticonvulsant stimulation of the vagus nerve. Epilepsy Res. 1995;22:53-62. [84] Fitch MT, Silver J. CNS injury, glial scars, and inflammation: Inhibitory extracellular matrices and regeneration failure. Exp. Neurol. 2008;209(2):294–301. [85] Myer DJ, Gurkoff GG, Lee SM, Hovda DA, Sofroniew MV. Essential protective roles of reactive astrocytes in traumatic brain injury. Brain. 2006;129(pt 10):2761–2772. [86] Xin H, et al. Increasing tPA activity in astrocytes induced by multipotent mesenchymal stromal cells facilitate neurite outgrowth after stroke in the mouse. PLoS One. 2010;5(2):e9027. [87] Silver J, Miller JH. Regeneration beyond the glial scar. Nat. Rev. Neurosci. 2004;5(2):146–156. [88] Ransohoff RM, Brown MA. Innate immunity in the central nervous system. J. Clin. Invest. 2012;122(4):1164–1171. [89] Tremblay ME, Stevens B, Sierra A, Wake H, Bessis A, Nimmerjahn A. The role of microglia in the healthy brain. J. Neurosci. 2011;31(45):16064–16069. [90] Yenari MA, Kauppinen TM, Swanson RA. Microglial activation in stroke: therapeutic targets. Neurotherapeutics. 2010;7(4):378–391.


251

[91] Du Y, Dreyfus CF. Oligodendrocytes as providers of growth factors. J. Neurosci. Res. 2002;68(6):647–654. [92] Yang Y, Rosenberg GA. Blood-brain barrier breakdown in acute and chronic cerebrovascular disease. Stroke. 2011;42(11):3323–3328. [93] Saunders NR, Ek CJ, Habgood MD, Dziegielewska KM. Barriers in the brain: a renaissance? Trends Neurosci. 2008;31(6):279–286. [94] Asahi M, Wang X, Mori T, Sumii T, Jung JC, Moskowitz MA, Fini ME, Lo EH. Effects of matrix metalloproteinase-9 gene knock-out on the proteolysis of blood-brain barrier and white matter components after cerebral ischemia. J. Neurosci. 2001;21(19):7724–7732. [95] Rosenberg GA, Estrada EY, Dencoff JE. Matrix metalloproteinases and TIMPs are associated with blood-brain barrier opening after reperfusion in rat brain. Stroke. 1998;29(10):2189–2195. [96] Moskowitz MA, Lo EH, Iadecola C. The science of stroke: mechanisms in search of treatments. Neuron. 2010;67(2):181–198. [97] Hermann DM, Chopp M. Promoting brain remodeling and plasticity for stroke recovery: therapeutic promise and potential pitfalls of clinical translation. Lancet Neurol. 2012;11(4):369– 380. [98] Rivers LE, Young KM, Rizzi M, Jamen F, Psachoulia K, Wade A, Kessaris N, Richardson WD. PDGFRA/NG2 glia generate myelinating oligodendrocytes and piriform projection neurons in adult mice. Nat. Neurosci. 2008;11(12):1392–1401. [99] Aimaretti G, Ambrosio MR, Di Somma C, Gasperi M, Cannavò S, Scaroni C, Fusco A, Del Monte P, De Menis E, Faustini-Fustini M, Grimaldi F, Logoluso F, Razzore P, Rovere S, Benvenga S, Degli Uberti EC, De Marinis L, Lombardi G, Mantero F, Martino E, Giordano G, Ghigo E. Residual pituitary function after brain injury-induced hypopituitarism: a prospective 12-month study. J. Clin. Endocrinol Metab. 2005;90(11):6085-92. [100] Cohan P, Wang C, McArthur DL, Cook SW, Dusick JR, Armin B, Swerdloff R, Vespa P, Muizelaar JP, Cryer HG, Christenson PD, Kelly DF. Acute secondary adrenal insufficiency after traumatic brain injury: a prospective study. Crit. Care Med. 2005;33(10):2358-66. [101] Bernard F, Outtrim J, Menon DK, Matta BF. Incidence of adrenal insufficiency after severe traumatic brain injury varies according to definition used: clinical implications. Br. J. Anaesth. 2006;96(1):72-6. [102] Dallman MF, Akana SF, Jacobson L, Levin N, Cascio CS, Shinsako J. Characterization of corticosterone feedback regulation of ACTH secretion. Ann. NY Acad. Sci. 1987;512:402-14. [103] McEwen BS, Magarinos AM. Stress and hippocampal plasticity: implications for the pathophysiology of affective disorders. Hum Psychopharmacol. 2001 Jan;16(S1):S7-S19. [104] Joëls M, de Kloet ER. Effect of corticosteroid hormones on electrical activity in rat hippocampus. J. Steroid Biochem. Mol. Biol. 1991;40(1-3):83-6. [105] de Kloet ER. Stress in the brain. Eur. J. Pharmacol. 2000;405(1-3):187-98. [106] Sapolsky RM. Glucocorticoids, stress, and their adverse neurological effects: relevance to aging. Exp. Gerontol. 1999;34(6):721-32. [107] Grønli J, Bramham C, Murison R, Kanhema T, Fiske E, Bjorvatn B, Ursin R, Portas CM.Chronic mild stress inhibits BDNF protein expression and CREB activation in the dentate gyrus but not in the hippocampus proper. Pharmacol. Biochem. Behav. 2006;85(4):842-9. [108] Barkhoudarian G, Hovda DA, Giza CC. The molecular pathophysiology of concussive brain injury. Clin. Sports Med. 2011;30(1):33-48. [109] Griesbach GS, Hovda DA, Molteni R, Wu A, Gomez-Pinilla F. Voluntary exercise following traumatic brain injury: brain-derived neurotrophic factor upregulation and recovery of function. Neuroscience. 2004;125(1):129-39.

252


[110] Vreeburg SA, Hoogendijk WJ, van Pelt J, Derijk RH, Verhagen JC, van Dyck R, Smit JH, Zitman FG, Penninx BW. Major depressive disorder and hypothalamic-pituitary-adrenal axis activity: results from a large cohort study. Arch. Gen. Psychiatr. 2009;66(6):617-26. [111] Newcomer JW, Selke G, Melson AK, Hershey T, Craft S, Richards K, Alderson AL. Decreased memory performance in healthy humans induced by stress-level cortisol treatment. Arch. Gen. Psychiatry. 1999;56(6):527-33. [112] Sprung CL, Annane D, Keh D, Moreno R, Singer M, Freivogel K, Weiss YG, Benbenishty J, Kalenka A, Forst H, Laterre PF, Reinhart K, Cuthbertson BH, Payen D, Briegel J; CORTICUS Study Group. Hydrocortisone therapy for patients with septic shock. N Engl J Med. 2008;358(2):111-24. [113] Englander J, Bushnik T, Oggins J, Katznelson L. Fatigue after traumatic brain injury: Association with neuroendocrine, sleep, depression and other factors. Brain Inj. 2010;24(12):1379-88. [114] Barnes PJ, Karin M. Nuclear factor-kappaB: a pivotal transcription factor in chronic inflammatory diseases. N Engl. J. Med. 1997;336(15):1066-71. [115] Patterson Z, Holahan M.Understanding the neuroinflammatory response following concussion to develop treatment strategies. Front Cell Neurosci. 2012;6(58):1-10. [116] McCrory P, Meeuwisse W, Aubry M, Cantu B, Dvorak J, Molloy M, Johnston K. Consensus statement on concussion in sport- Third International Conference on Concussion in Sport held in Zurich, November 2008. Phys Sportsmed. 2009;37(2):141-159. [117] Schrader H, Mickreviciene D, Gleizniene R, Jakstiene S, Surkiene D, Stovner L, Obelieniene D. Magnetic resonance imaging after most common form of concussion. BMC Med Imaging. 2009; 9(11):1-6. [118] Harmon KG, Drezner JA, Gammons M, Guskiewicz KM, Halstead M, Herring SA, Kutcher JS, Pana A, Putukian M, Roberts WO. American Medical Society for Sports Medicine position statement: concussion in sport.Br. J. Sports Med. 2013;47(1):15-26. [119] Marshall S, Bayley M, McCullagh S, Velikonja D, Berrigan L. Clinical practice guidelines for mild traumatic brain injury and persistent symptoms. Can Fam Physician. 2012;58(3):257-67 [120] Mott TF, McConnon ML, Rieger BP. Subacute to chronic mild traumatic brain injury. Am. Fam Physician. 2012;86(11):1045-51. [121] Herbert DL. Medical-legal issues of mild traumatic brain injury. Curr. Sports Med. Rep. 2007;6(1):20-4. [122] Spain A, Daumas S, Lifshitz J, Rhodes J, Andrews P, Horsburgh K, Fowler J. Mild fluid percussion injury in mice produces evolving selective axonal pathology and cognitive deficits relevant to human brain injury. J. Neurotrauma. 2010;27:1429-38. [123] Svetlov SI, Prima V, Kirk DR, Gutierrez H, Curley KC, Hayes RL, Wang KK. Morphologic and biochemical characterization of brain injury in a model of controlled blast overpressure exposure. J. Trauma. 2010;69(4):795-804. [124] Messé A, Caplain S, Pélégrini-Issac M, Blancho S, Montreuil M, Lévy R, Lehéricy S, Benali H. Structural integrity and post-concussion syndrome in mild traumatic brain injury patients. Brain Imaging Behav. 2012;6(2):283-92. [125] Oppenheimer DR. Microscopic lesions in the brain following head injury. J. Neurol. Neurosurg Psychiatry. 1968;31(4):299-306. [126] Strich J. Diffuse degeneration of the cerebral white matter in severe dementia following head injury. J. Neurol. Neurosurg Psychiatry. 1956;19(3):163-185. [127] Bigler E, Maxwell W. Neuropathology of mild traumatic brain injury: relationship to neuroimaging findings. Brain Imaging and Behav. 2012;6(2):108-136.


253

[128] Slobounov S, Zhang K, Pennell D, Ray W, Johnson B, Sebastianelli W. Functional abnormalities in normally appearing athletes following mild traumatic brain injury: a functional MRI study. Exp. Brain Res. 2010;202(2):341-354. [129] Zourdiakis G, Udit Patidar N, Castillo E. Levin H. Papanicolaou A. Functional connectivity changes in mild traumatic brain injury assessed using magnetoencephalography. J. Mech. Med. Biology. 2012;12(2):1-13. [130] Lewine J, Davis J, Bigler E, Thoma R, Hill D, Funke M, Hall, S. Objective documentation of traumatic brain injury subsequent to mild head trauma: Multimodal brain imaging with MEG, SPECT and MRI. J. Head Trauma Rehabil. 2007;22(3):141-155. [131] Hattori, N, Swan M, Stobbe G, Uomoto J, Minoshima S, Djang D, Lewis, Differential SPECT activation patterns associated with PASAT performance may indicate frontocerebellar functional dissociation in chronic mild traumatic brain injury. J. Nucl. Med. 2009;50(7):105461. [132] Gao X, Chen J. Mild traumatic brain injury results in extensive neuronal degeneration in the cerebral cortex. J. Neuropathol Exp. Neurol. 2011;70(3):183-91. [133] Dekosky ST, Blennow K, Ikonomovic MD, Gandy S. Acute and chronic traumatic encephalopathies: pathogenesis and biomarkers. Nat. Rev. Neurol. 2013;9(4):192-200. [134] Stern RA, Riley DO, Daneshvar DH, Nowinski CJ, Cantu RC, McKee AC. Long-term consequences of repetitive brain trauma: chronic traumatic encephalopathy. PM R. 2011;3(10 Suppl 2):S460-7. [135] Baugh CM, Stamm JM, Riley DO, Gavett BE, Shenton ME, Lin A, Nowinski CJ, Cantu RC, McKee AC, Stern RA. Chronic traumatic encephalopathy: neurodegeneration following repetitive concussive and subconcussive brain trauma. Brain Imaging Behav. 2012;6(2):244-54. [136] McKee A, Stein T, Nowinski C, Stern R, Daneshvar D, Alvarez V, Wojtowicz S. The spectrum of disease in chronic traumatic encephalopathy. Brain. 2013;136(Pt 1):43-64. [137] Maas AI, Stocchetti N, Bullock R. Moderate and severe traumatic brain injury in adults. Lancet Neurol. 2008;7(8):728-41. [138] Hardman JM, Manoukian A. Pathology of head trauma. Neuroimaging Clin N Am. 2002;12(2):175–87. [139] Liu W, Wang B, Wolfowitz R, Yeh P, Nathan D, Graner J, Pham D. Perfusion deficits in patients with mild traumatic brain injury characterized by dynamic susceptibility contrast MRI. NMR Biomed. 2013;26(6):651-63. [140] Bonne O, Gilboa A, Louzoun Y, Kempf-Sherf O, Katz M, Fishman Y, Bocher M. Cerebral blood flow in chronic symptomatic mild traumatic brain injury. Psychiatry Res. 2003;124(3):141-152. [141] Lipton M, Gellella E, Lo C, Gold T, Ardekani B, Shifteh K, Branch C. Multifocal white matter utrastructural abnormalities in mild traumatic brain injury with cognitive disability: A voxelwise analysis of diffusion tensor imaging. J. Neurotrauma. 2008;25:1335-42. [142] Rao V, Mielke M, Xu X, Smith G, McCann U, Bergey A, Mori S. Diffusion tensor imaging atlas-based analyses in major depression after mild traumatic brain injury. J. Neuropsychiatry Clin. Neurosci. 2012;24(3):309-315. [143] Peskind E, Petrie E, Cross D, Pagulayan K, McCraw K, Hoff D, Satoshi Minoshima S. Cerebrocerebellar hypometabolism associated with repetitive blast exposure mild traumatic brain injury in 12 Iraq War veterans with persistent post-concussive symptoms. Neuroimage. 54(Suppl 1)2011;S76-S82. [144] Nathan DE, Wang BQ, Wolfowitz RD, Liu W, Yeh PH, Graner JL, Harper J, Pan H, Oakes TR, Riedy G. Examining intrinsic thalamic resting state networks using graph theory analysis: implications for mTBI detection. Conf Proc IEEE Eng Med Biol Soc. 2012;5445-8.

254


[145] Zhang L, Yang KH, King AI. 2004A proposed injury threshold for mild traumatic brain injury. J. Biomech. Eng. 2004;126(2):226-36. [146] Len T, Neary J. Cerebrovascular pathology following mild traumatic brain injury. Clin. Physiol Funct Imaging. 2011;31(2):85-93. [147] Marchi N, Bazarian J, Puvenna V, Janigro M, Gosh C. Consequences of repeated blood-brain barrier disruption in football players. PLoS ONE. 2013;8(3):1-11. [148] Griffin GD. The injured brain: TBI, mTBI, the immune system, and infection: connecting the dots. Mil Med. 2011;176(4):364-8. [149] Caso JR, Leza JC, Menchén L. The effects of physical and psychological stress on the gastrointestinal tract: lessons from animal models. Curr. Mol. Med. 2008;8(4):299-312. [150] Barkhoudarian G, Hovda D, Giza C. The molecular pathophysiology of concussive brain injury. Clin. Sports Med. 2011;30:33-48. [151] Redell JB, Moore AN, Grill RJ Jr, Johnson D, Zhao J, Liu Y, Dash PK. Analysis of Functional Pathways Altered Following Mild Traumatic Brain Injury. J. Neurotrauma. 2013;30(9):752-64 [152] Blennow K, Hardy J, Zetterberg H. The neuropathology and neurobiology of traumatic brain injury. Neuron. 2012;76(5):886-899. [153] Johnson EG. Clinical management of a patient with chronic recurrent vertigo following a mild traumatic brain injury. Case Rep Med. 2009;2009:910596. [154] Liberge M, Manrique C, Bernard-Demanze L, Lacour M. Changes in TNF-alpha, NFκB and MnSOD protein in the vestibular nuclei after unilateral vestibular deafferentation. J. Neuroinflammation. 2010;7:91. [155] Scherer MR, Burrows H, Pinto R, Littlefield P, French LM, Tarbett AK, Schubert MC. Evidence of central and peripheral vestibular pathology in blast-related traumatic brain injury. Otol. Neurotol. 2011;32(4):571-80. [156] Sosnoff JJ, Broglio SP, Shin S, Ferrara MS. Previous mild traumatic brain injury and posturalcontrol dynamics. J. Athl Train. 2011;46(1):85-91. [157] Pickett TC, Radfar-Baublitz LS, McDonald SD, Walker WC, Cifu DX. Objectively assessing balance deficits after TBI: Role of computerized posturography. J. Rehabil Res. Dev. 2007;44(7):983-90. [158] Gottshall KR, Hoffer ME. Tracking recovery of vestibular function in individuals with blastinduced head trauma using vestibular-visual-cognitive interaction tests. J. Neurol Phys Ther. 2010;34(2):94-7. [159] Alsalaheen BA, Mucha A, Morris LO, Whitney SL, Furman JM, Camiolo-Reddy CE, Collins MW, Lovell MR, Sparto PJ.Vestibular rehabilitation for dizziness and balance disorders after concussion. J. Neurol. Phys Ther. 2010;34(2):87-93. [160] Ciuffreda KJ, Kapoor N, Rutner D, Suchoff IB, Han ME, Craig S.Occurrence of oculomotor dysfunctions in acquired brain injury: a retrospective analysis. Optometry. 2007;78(4):155-61. [161] Alvarez TL, Kim EH, Vicci VR, Dhar SK, Biswal BB, Barrett AM. Concurrent Vision Dysfunctions in Convergence Insufficiency with Traumatic Brain Injury. Opt. Vis. Sci. 2012;89:1740-1751. [162] Suh M, Kolster R, Sarkar R, McCandliss B, Ghajar J. Deficits in predictive smooth pursuit after mild traumatic brain injury. Neurosci. Let. 2006;401:108–113. [163] Suh M, Basu S, Kolster R, Sarkar R, McCandliss B, Ghajar J. Increased oculomotor deficits during target blanking as an indicator of mild traumatic brain injury. Neurosci. Let. 2006;410:203–207. [164] Maruta J, Suh M, Niogi SN, Mukherjee P, Ghajar J. Visual tracking synchronization as a metric for concussion screening. J. Head Trauma Rehabil. 2010 25(4):293-305.


255

[165] Mulhall LE, Williams IM, Abel LA. Bedside tests of saccades after head injury. J. Neuroophthalmol. 1999;19(3):160-5. [166] Pearson BC, Armitage KR, Horner CW, Carpenter RH. Saccadometry: the possible application of latency distribution measurement for monitoring concussion. Br. J. Sports Med. 2007;41(9):610-2. [167] Drew AS, Langan J, Halterman C, Osternig LR, Chou LS, van Donkelaar P. Attentional disengagement dysfunction following mTBI assessed with the gap saccade task. Neurosci. Lett. 2007;417(1):61-5. [168] Heitger MH, Jones RD, Macleod AD, Snell DL, Frampton CM, Anderson TJ. Impaired eye movements in post-concussion syndrome indicate suboptimal brain function beyond the influence of depression, malingering or intellectual ability. Brain. 2009;132(Pt 10):2850-70. [169] Gooding DC, Basso MA. The tell-tale tasks: a review of saccadic research in psychiatric patient populations. Brain Cogn. 2008;68(3):371-90. [170] Basford JR, Chou LS, Kaufman KR, Brey RH, Walker A, Malec JF, Moessner AM, Brown AW. An assessment of gait and balance deficits after traumatic brain injury. Arch. Phys. Med. Rehabil. 2003;84(3):343-9. [171] Ciuffreda KJ, Rutner D, Kapoor N, Suchoff IB, Craig S, Han ME.Vision therapy for oculomotor dysfunctions in acquired brain injury: a retrospective analysis. Optometry. 2008;79(1):18-22. [172] Kikuchi M, Naito Y, Senda M, Okada T, Shinohara S, Fujiwara K, Hori SY, Tona Y, Yamazaki H. Cortical activation during optokinetic stimulation - an fMRI study. Acta Otolaryngol. 2009;129(4):440-3. [173] Vitte E, Sémont A, Berthoz A. Repeated optokinetic stimulation in conditions of active standing facilitates recovery from vestibular deficits. Exp. Brain Res. 1994;102(1):141-8. [174] Loader B, Gruther W, Mueller CA, Neuwirth G, Thurner S, Ehrenberger K, Mittermaier C. Improved postural control after computerized optokinetic therapy based on stochastic visual stimulation in patients with vestibular dysfunction. J. Vestib Res. 2007;17(2-3):131-6. [175] Ohyama S, Nishiike S, Watanabe H, Matsuoka K, Takeda N. Effects of optokinetic stimulation induced by virtual reality on locomotion: a preliminary study. Acta Otolaryngol. 2008;128(11):1211-4. [176] Chitambira B. A case report on the use of a novel optokinetic chart stimulation intervention for the restoration of voluntary movement and mobility in a patient with an acute hemorrhagic stroke. NeuroRehabilitation. 2009;25(4):251-4. [177] Chitambira B. Use of an optokinetic chart stimulation intervention for restoration of voluntary movement, postural control and mobility in acute stroke patients and one post intensive care polyneuropathy patient: A case series. NeuroRehabilitation. 2011;28(2):99-104. [178] Lopez NE, Krzyzaniak MJ, Costantini TW, Putnam J, Hageny AM, Eliceiri B, Coimbra R, Bansal V.Vagal nerve stimulation decreases blood-brain barrier disruption after traumatic brain injury. J. Trauma Acute Care Surg. 2012;72(6):1562-6. [179] Rábago CA, Wilken JM. Application of a mild traumatic brain injury rehabilitation program in a virtual realty environment: a case study. J. Neurol Phys Ther. 2011;35(4):185-93. [180] Willer B, Leddy JJ. Management of concussion and post-concussion syndrome. Curr. treat Options Neurol. 2006;(8)5:415-426. [181] Iverson GL. Misdiagnosis of the persistent post-concussion syndrome in patients with depression. Arch. Clin. Neuropsychol. 2006;21(4):303-310. [182] Bigler ED. Neuropsychology and clinical neuroscience of persistent post-concussive syndrome. J. Int .Neuropsychol Soc. 2008;14(1):1-22. [183] Maruta J, Jacobs EF, Lee SW, Ghajar J. A unified science of concussion. Ann. NY Acad Sci. 2010;1208:58-66.

256


[184] Rao V, Lyketsos C. Neuropsychiatric sequelae of TBI. Psychosomatics. 2000;41(2):95-103. [185] Comper P, Hutchison M, Magrys S, Mainwaring L, Richards D. Evaluating the methodological quality of sports neuropsychology concussion research: A systematic review. Brain Injury. 2010;24(11):1257-1271. [186] Mapping cortical change across the human life span. Sowell ER, Peterson BS, Thompson PM, Welcome SE, Henkenius AL, Toga AW. Nature Neuroscience. 2003 Mar;6(3):309-15. [187] Microglia-mediated neurotoxicity: uncovering the molecular mechanisms. Block ML, Zecca L, Hong JS. Nat Rev Neurosci. 2007 Jan;8(1):57-69. [188] Ye Z, Song H, Higgins JP, Pharoah P, Danesh J. Five glutathione s-transferase gene variants in 23,452 cases of lung cancer and 30,397 controls: meta-analysis of 130 studies. PLoS Med. 2006 April;3(4):e91.

Received: June 23 2013. Revised: July 2 2013 Accepted: Jul 3 2013.



DIME (DIPLOMATIC, INFORMATION, MILITARY AND ECONOMIC POWER) EFFECTS MODELING SYSTEM: APPLICATIONS FOR THE MODELING OF THE BRAIN Newton Howard1 and Gerry Leisman2,3,4 1

2

Mind-Brain Institute, Massachusetts Institute of Technology, Cambridge F.R. Carrick Institute for Clinical Ergonomics, Rehabilitation & Applied Neurosciences CERAN, Garden City, NY USA 3 The National Institute for Brain & Rehabilitation Sciences, Nazareth, Israel 4 Biomedical Engineering, Department of Biomechanics, ORT-Braude College of Engineering, Karmiel, Israel

ABSTRACT This paper describes an analysis framework for estimating the effects of Diplomatic, Informational, Military, and Economic (DIME) activities in the context the brain. We are proposing to evaluate and recommend a set of candidate models of the flow and evolution of cognition and intention as the starting point for developing a DIME Effects Modeling System (DEMS) for command and control by the brain and nervous system. We identified the needs as: (1) understanding and representing the underlying causality within the population, (2) formulating models that are both sensitive and computable, and (3) validating the predictions of cognitions, intentions, and behaviors by model.

Keywords: DIME, intention awareness, DEM, SOA, PMSEII

INTRODUCTION Can computational models of human behavior and of the nervous system be useful in facilitating our understanding of how networks of the brain communicate? Can seemingly non-related fields of science offer insights in understanding the nature of neural processing and rehabilitation. Understanding the development of human brain organization is critical for gaining insight into brain organization and functions in adulthood as well as for investigating disorders such as autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD), where normal developmental processes are disrupted. Neuroimaging studies of development have primarily focused on structural changes from childhood, to adolescence, and into adulthood. Studies have suggested that the human brain undergoes vast developmental changes in grey and white matter structure between childhood and adulthood. These changes are thought to reflect synaptic pruning and myelination observed at the 

Correspondence: Dr. Newton Howard E-Mail: [email protected]

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neuronal level [1,2]. In spite of growing for patterned brain development, the functional organization of the human brain in childhood is not well understood and it is also not clear how the above structural changes translate to differences in functional brain organization between children and adults. Changes in the functional modeling of the brain and nervous system is a potential useful approach to better understand the nature of normal and abnormal processing as well as being able to generate hypotheses for subsequent empirical study. Modeling techniques from the defense industry hold promise for assisting in a better understanding of nervous system function and dysfunction. These graph-theoretic metrics have also proven useful in modeling the large-scale functional and structural organization of the human brain [3-6]. In a graphical representation of a brain network, a node corresponds to a brain region while an edge corresponds to the functional connectivity between two brain regions. Functional connectivity networks of the human brain derived from electroencephalograms (EEGs), magnetoencephalograms (MEGs), and task-free functional magnetic resonance imaging (fMRI) data have been shown to exhibit small-world characteristics [4,7,8]. These studies suggest that small-world metrics are suited to quantify the global topological properties of large-scale organization of the human brain. Recently, in addition to small-world metrics, Bassett and colleagues used graph theoretic metrics such as hierarchy to characterize local topological properties of large-scale organization of the human brain. Using structural brain imaging data and modeling of interregional covariance in cortical thickness, they reported that hierarchical organization in anatomical human brain networks is characterized by the presence of frontal hubs [9]. A recent study of aging by Meunier and colleagues investigated the modular organization of large-scale functional brain networks using Newman’s graph-based modularity metric. They reported that while both young and older adults showed modularity of network organization, the topological roles of the specific brain regions as well as the inter-modular connectivity was significantly different between the two groups [10]. The use of small-world metrics along with more advanced graph theoretic metrics to characterize local organization of complex networks provides a new approach for investigating large- scale functional organization of the human brain at multiple levels of granularity. The development and evaluation of computable models for assessing the flow and evolution of a population’s beliefs, intentions, and behaviors within the diplomatic, informational, military, and economic (DIME) aspects of regional conflicts is not fundamentally unlike the nature of brain organization and reorganization as a result of experience. These military models may, in turn, have value in allowing us to better understand the nature of brain organization and reorganization as a result of experience. These models were part of a quest by the US Army to assess and manage the social aspects of stability operations in overseas conflict. The resulting collective models are hereafter referred to as the DIME Effects Model (DEM). We identify and characterized at least five classes of models that could be applicable to the DEMS. The identification of possible models was supported by a broad, but necessarily limited, literature search that spanned political theory, demographics, group behavior research, biostatistics, genetic theory, social networking and group beliefs and motivations. From this search, a classification of models into five types was made. These model classes are broad, with considerable variation in breadth, depth of detail and time span across the model instances found. Each of the model classes was intended to provide an approach to modeling the population, its beliefs and motives and its likely behaviors, as well as the underlying state of the Political, Military, Economic, Social and Informational Infrastructure (PMESII). The five classes we defined are:

System Dynamic Models This class of model generally consists of a system of differential equations that describe the relationships between attributes of the system state as the system evolves through time. Given an initial state X(0), a future state X(t) can be calculated. In practice, only the smallest systems of up to a

DIME (Diplomatic, Information, Military and Economic Power) Effects Modeling System 259 few dozen equations can be solved unless the systems are assumed to be linear (all higher order derivatives = 0). Much larger systems can be represented and solved under the assumption of linearity, which often is acceptable for short time periods and small variations in the state attributes. An example of such a model is represented in Figure 1.

Figure 1. Represents dynamical causal modeling for fMRI. Dynamical causal modeling (DCM) tries to infer directed connectivity among brain regions or sources. These models distinguish between a neuronal level, which models neuronal interactions among regions and an observation level, which, for fMRI, models the ensuing hemodynamic responses. Here, we look at the attentional modulation of evoked responses (in the context of visual motion processing) and see that it is best explained by an increased sensitivity of excitatory populations of neurons in V5 to forward afferents from earlier visual areas. Left: This example uses a DCM with two neuronal states (populations) per region which affords an explicit model of intrinsic (between-population) connectivity within a region. In addition, by using positivity constraints (through the exponential in the neuronal state equation), the model reflects the organization of real cortical hierarchies, whose extrinsic connections are excitatory (glutamatergic). Excitatory and inhibitory neuronal states for the ith region are denoted by x(i)⊇{xE(i), xI(i)} and exogenous (experimental) inputs (such as photic stimulation, motion or attention) are encoded by u⊇{u1, u2, …}. By comparing these sorts of DCM, one can disambiguate among competing hypotheses about the locus of context-sensitive changes in coupling, I(u). Middle: In all three models considered here, photic stimulation enters V1 and motion modulates the connection from V1 to V5, and all assume reciprocal and hierarchical extrinsic (between region) connections. The models differ in how attention modulates the influences on the excitatory population in V5 (green ellipses): model 1 assumes modulation of backward extrinsic connections, model 2 assumes modulation of intrinsic connections and model 3 assumes modulation of forward connections. Right: The results of Bayesian model comparison (upper graph) are shown in terms of the log evidence for each model: Model 3 (modulation of the forward connections by attention) is selected over other two models. The lower graph shows the predicted and observed regional responses under this model. In all, photic stimulation enters V1 and the motion variable modulates the connection from V1 to V5. Models 1, 2 and 3 all assume reciprocally and hierarchically organized connections. They differ in how attention modulates the influences on V5; Model 1 assumes modulation of the backward extrinsic connection, Model 2 assumes modulation of intrinsic connections in V5 and Model 3 assumes modulation of the forward connection. (See Marreiros and colleagues [11] for details).

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State Transition Models A state transition model exemplified in Figure 2 represents the state of the population beliefs and PMESII as a hierarchical state graph with nodes representing system state and links representing transition probabilities between the states. The hierarchical structure of the graph embeds sub-graphs within nodes, so that substrates can be defined within a state and so on. A node in a sub-graph represents a total state for the population system being modeled, and a system can be in only one state at a time. A state transition model may also be composed of a number of disconnected state graphs, each representing state transitions for an independent part of the system.

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B Figure 2. (A) is a block diagram of a neural prosthetic system including a cognitive state machine which illustrates a control system for a prosthetic device in which neural signals originating in the brain may be recorded from a neural implant and transmitted for processing. The neural activity decoded from a subject may transition through different stages between forming an intention to reach and executing the reach. Reach execution may not involve movement of the arm itself, but may involve movement of a virtual arm instead. (B) Represents a schematic block diagram of a cognitive state model of three movement types see the patent of Andersen et al., 2005 [12].

DIME (Diplomatic, Information, Military and Economic Power) Effects Modeling System 261 Rehabilitation applications might include limb prostheses which may operate in response to muscle contractions performed by the user. Some of these prostheses are purely mechanical systems. Other prostheses may incorporate electronic sensors to measure muscle activity and use the measured signals to operate the prosthesis. These types of prostheses may provide only crude control to users that have control over some remaining limb musculature. Prosthetic devices and other assistive aids that require control over some remaining limb musculature may not be useful for individuals who have suffered from upper spinal cord injury, strokes, and neurodegenerative diseases. Prosthetic devices that operate in response to electrical signals measured by a sensor implanted in the subject's brain are being contemplated for assisting these individuals. A prosthetic system may use a decoder to predict an intended action, such as a reach, from processed signals generated from measured neural activity. The decoder may include a cognitive state machine, which transitions between cognitive states based on transition rules. Mathematically, this corresponds to a state space model for cognitive processes. States may be continuously or discretely valued and may be observable or hidden. The transition rules may be described by a matrix of probabilities. Classifiers may classify the processed signals into period and direction classifications. The period classifications may correspond to neural/behavioral periods and the direction classifications may correspond to intended directions. The state machine may transition between cognitive states in response to receiving certain classifications for a predetermined period of time. For example, for a reach, the state machine may transition between a planning state and a reach state in response to receiving a planning classification for a predetermined period of time, e.g., 500 ms. Other state transition models may additionally require that a direction classification is received for the duration of a planning period and/or that a cognitive “go” signal is received. The cognitive states in the state transition model may be defined based on observation, hypothesis, and experimentation. The cognitive states may also be developed using mathematical modeling techniques such as hidden Markov modeling techniques.

Social Network Models These are graph-structured models of relationships between people or groups of people. Nodes represent the individuals or groups and vertices represent relationships such as communication or influence. A nervous system-based exemplar is provided in Figure 3(D). If one were to make a picture of one’s social network, what would it look like? Would it look like a regular structure, like a lattice as represented in 3(C)? Or would there be strange detours and longrange connections between friends’ friends as represented in Figure 3(A) or 3(B)? It would probably be something more like the irregular graph than the lattice as represented in Figure 3(C). People do not form friendships in a regular, orderly manner conforming to strict rules of structure. Instead, people form local clusters of friends or cliques and some people act as bridges between cliques to connect them and form the small-world topography familiar to social networks as represented in Figures 3(A) and (B). This is one of the points Watts and Strogatz [13] illustrated with their social network models. A ring lattice may be a poor analog for a real-life friendship network, but a ring lattice with a few perturbations of the edges does a good job of capturing two characteristics of social graphs: local structure and random edges that allow a small world. Figure 3(D) represents such an example with applications of connectography represented in Figure 3(D).

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Figure 3. Graph-structured models of relationships between people or groups of people employing the (A) WattsStrogatz model (B) Sociometry (C) Lattice Models and (D) Connectography of short and long range connections. Multimodal studies have shown that cellular and whole-brain networks demonstrate consistent topological features.

Group Ideology Models. This type of model represents the beliefs and intentions of groups within a population and suggests what actions the groups are likely to take in the future. The model is implemented using one or more symbolic reasoner to provide an “analyze-plan-act-coordinate” loop for each group. The groups are goal-driven with goals defined by their adopted ideology, and may be in conflict with the goals of other groups. The groups have beliefs which may be inaccurate, incomplete and inconsistent. Groups take actions to fulfill their goals, and actions may be directly mediated by the state of the PMESII. Again, brain applications are provided in Figure 4.

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B Figure 4. Continued on next page.

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D Figure 4. Provides an illustration of a simplified path model of inmate group behavior with nonrecursive and duplicate paths not shown to reduce visual complexity as illustrated in (A), these control processes are the result of three other sets of processes in the organization: (B) conflictive, (C) structural, and (D) normative. Additionally, the extent of controls used will result in a comparison of actual inmate behavior to that level desired by the organization [14]. The use of material control will also be affected by inmate efforts to control the allocation of material resources such as job allocations and other scarce resources [15]. The conflictive, structural, and normative controls used, whether positive or negative, interact dynamically with inmate compliance and these other processes [see 16].


Group Dynamics Models The DEM is situated at the brigade level because that is where the necessary operational and architectural resources exist today. The DEM model should be able to run its full analysis cycle in roughly one hour to accommodate the current status reporting procedure at the brigade level. The analysis should include high fidelity predictions within a time frame of days, accompanied by lower fidelity predictions that span months. The system should facilitate situation assessment when one brigade relieves another on station, as well as sharing information between cooperating brigades. Finally, the DEM should be granular enough to represent cultural differences in different theaters and adaptive as the theater evolves. This type of model represents the behaviors and intentions of groups within a population and suggests what actions the groups are likely to take in the future based on their internal and external dynamic relationships. Although similar to the Group Ideology model in mechanization, the knowledge within this class of model is focused on group dynamics rather than ideology, and is therefore more general and more re-usable. Figure 5 provides such an example of this model applied to the brain.

Figure 5. Group Dynamic Models: A group consists of two or more people with a common relationship. If the group members shared leadership, developed their own purpose or goal or worked together continuously, rather than occasionally, it could become a team. In 1965, Tuckman [17] proposed The Forming – Storming – Norming – Performing model of stages of group development. In 1977, Tuckman added a fifth stage called Adjourning (reproduced from Langton & Robbins [18] in [Fig. 5]). Forming- is the first stage, characterized by uncertainty. Members of a group do not know each other well. Through communication connectivities become stronger in ways similar to those found in Fig. 3(D). Storming- is the second stage characterized by conflict when group members know each other better. It happens often, that at this stage many conflicts occur, the motor learning equivalent might be piano lessons where the motor skills have not reached levels of automaticity. It is at this stage that the need of a leader becomes higher. Norming- is the third stage characterized by cohesiveness. At this stage, the team becomes organized as in brain connectivity function in adolescence as opposed to early childhood [19]. Team members effectively begin working together, helping each other and asking for others’ opinion. The team started fulfilling its purpose. Performing- is the fourth stage in which group energy has moved from acquaintanceship to performance, where tasks can now be optimized. This concept can also be represented in brain dynamics as optimized functional connectivities.

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D Figure 6. Represents the evaluation of unconscious body movement synchrony and implicit interpersonal interactions between two participants examined by observing the neural correlates and functional connectivities within and among the brain regions of interacting participants. Results of unconscious fingertip movements between two participants are represented while simultaneously recording EEG in a face-to-face setting. Participants were asked to straighten their arms, point and hold their index fingers toward each other, and look at the other participant's fingertip. Face-to-face interactions closely approximate real-life situations and reinforce the social nature of interpersonal interactions. (A) Represents the total number of functional connections that showed significant phase synchrony of inter- and intra-brain in theta (4~7.5 Hz) and beta (12~30 Hz) frequency range. The overall number of significant phase synchrony increased after training in inter-brain connections, but not in intra. (B) Represents the topography of the phase synchrony connections between all 168 cortical ROIs of the two participants (Left brain: leader, right brain: follower) when contrasting post- against pre-training in theta (4~7.5 Hz) and (C) beta (12~30 Hz). Inter-brain connections were found mainly in the inferior frontal gyrus (IFG), anterior cingulate (AC), parahippocampal gyrus (PHG), and postcentral gyrus (PoCG) (see Yun et al 2012). (D) Functional connectivity captures brain interactions via fluctuations in the observed activity; graphical modeling can extract connectomes, i.e. graphs of brain connectivity, with statistically well-posed and controlled methods. Learning brain connectivity faces the complexity of brain graphs that contrasts with the small amount of data at the subject level. At the group level, connectivity information can be convolved with inter-subject variability (see Ng et al. [20]).


SYSTEM ARCHITECTURE The DEMS is meant to be a state-of-the-art tool for analysts at the brigade level to use for planning and evaluating the effectiveness of the effects-based operations, particularly focused on integration of diplomatic, informational, military, and economic effects. Because the DEM is an integration of ideas from several disciplines of science, a component based framework approach is the best investment for the DEM. A component-oriented framework allows the DEM to evolve as data visualization technologies evolve. Our research confirmed that the initial framework necessary to setup the DEM exists and is already integrated with the major defense programs we are tending to as commercialization opportunities for the DEM.

Development Methods Our development methods followed Xtreme programming methodology, working in short iterations to reach through all layers of the architecture to implement a small, well-defined use case. We elicited feedback on each iteration’sprototype to further integrate the look and feel with which the analyst expects to work.

Figure 7. Extreme program methodology.

Service Frameworks The envisioned architecture is a distributed infrastructure promoting application integration and collaboration across services and applications. It uses the Service Oriented Architecture (SOA) style exemplified in Figure 8 to define, govern, and implement core service interfaces including discovery. It uses an event-driven architecture style for message routing and collaboration between users. It contains a suite of tools specifically designed to aid tying intelligence applications together. The value of this architecture lies specifically in its collaborative potential and in its open architecture.

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Figure 8. Distributed Infrastructure in a service oriented architecture.

Collaborative Framework The collaboration framework is an event-based service integration framework, or more simply, a service bus. Systems are composed of compliant applications and services that interact via the collaboration framework. The framework supports peer-to-peer and client-server configurations and runs on laptops or almost any Windows hardware. The value of the collaborative framework in the architecture is that it allows end-users to collaborate and share their data. More than just a screen-scraping technique, two collaborating usersare actually sharing data, while maintaining separate presentation mechanisms. For example, suppose two analysts are collaborating on new intelligence data about a person of interest. The collaboration framework allows them to share their data about the person with each other, even though one analyst is using that data to evaluate the link analysis network for that person while the other analyst is using the data to simulate a belief model for that person. The following services make up the collaboration framework. 

Collaboration Data Manager Service. The CDM is an in-process object management and event notification service. It handles activities such as creation and deletion of objects and client subscriptions.

DIME (Diplomatic, Information, Military and Economic Power) Effects Modeling System 269 

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Session Manager Service. The SM is a Windowed Client Adapter that provides the user interface for connecting to local or remote Session Brokers, managing their sessions, subscribing to sessions and connecting the collaboration to the subscribed session. Session Broker Service. The SB manages available sessions on a single system. It handles activities such as keeping track of available sessions, session types, channel types, subscriptions, and session creation and deletion. Interop Services. IS is responsible for providing information about available Collaboration Sessions on a system, bridging message traffic between heterogeneous Collaboration channels. Channel Adapter Service. CA enables collaboration messages to be sent and received across process (or system) boundaries. It is responsible for serializing and de-serializing collaboration and session messages into a format appropriate for the Collaboration Channel that they are communicating on.

Solution Framework Complementing the collaboration framework, the solution framework is an object-oriented execution environment (Figure 9) for integrating components to form a Windows application, including service discovery.

Figure 9. Object oriented execution environment providing a collaboration framework.

It provides basic components and mechanisms for connecting them together and defining their interaction. Ultimately, it is the framework that allows a user to work with related elements across multiple data sources. A PMESII element in the link analysis component window can be dragged and dropped into the belief value model component window and analyzed immediately, even though the components are different applications. This ability allows the framework to integrate multiple vendors seamlessly to boost the analyst’s view into the data.

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TESTING AND EVALUATION The value of a suite of models such as the DIME Effects Modeling System is directly related to the extent to which the models can be tested and evaluated against the real world they purport to model. But the testing and evaluation of models such as DEMS is not an easy task. This section will provide a background for the complex issues facing evaluation of DEMS, and provide a set of recommendations to guide further work. When the output of a model is compared to the observations of the real world, discrepancies can arise in two ways: (1) the model has an error in its implementation, but may otherwise be properly founded, or (2) the model was implemented completely as desired, but the underlying foundations of the model were flawed. Outcome (1) is the area of test and evaluation known as verification testing, while outcome (2) is the problem of validation. Verification testing is normally conducted with pre-defined and pre-certified test cases whose expected outputs are thought to be “correct” with respect to the real world. A second issue in verification testing is the extent to which the system under test is fully exercised. It may take a very large number of pre-certified test cases to provide coverage of all aspects of the system under test. Validation testing of models requires head-to-head comparison with the real world. If the output of the models agrees reasonably with the observations of the real world, the model can claim at least local (for a particular case) validity. After many trials over a broad range of conditions, the outputs of the suite of models may continue to agree reasonably with the observations of the real world, thus establishing convergent validity. It is important to note that a system may have known faults (not fully verified) and still be valid. However verified or valid the suite of models might be, utility is still a separate question. Does the DEMS benefit the users? If the outputs of the model are no more refined than the average educated estimates of the user, it is of no real help. The DEMS is useful to the extent that it can lead users to better decisions with better outcomes. To measure this, the utility tests must be fully interactive with real users in a real and dynamic world. For all these test processes (verification, validation and utility testing), a rich set of formal experimental methods exists. But for testing the DEMS, a set of deep and difficult challenges also exists. Underlying all of the elegant and useful work in formal experimental design are two important ideas: the experimental unit, and replication. The experimental unit defines that chunk of reality that can be sufficiently isolated from its surroundings and controlled against external factors so that the observation of its outcome can be cleanly linked to its inputs. In many sciences, the experimental unit is easy: a test tube with culture medium and organisms, a plot of land, an aluminum bar. But for DEMS, how is a part of an interconnected social, political and economic system isolated without disrupting its very nature? Even if an experimental unit can be reasonably defined, replication is an even harder challenge. Many experimental units must be found, all of them “identical” for the purposes of an experiment. Because social systems carry the memory of their past, it requires special care if any living experimental unit will be used more than once. Further complicating the evaluation of the DEMS is the issue of correctness. How should a unit of a social system behave if manipulated in some planned way? Is the way a social system responded in the past a reasonable guide to how another similar social system will respond in the present? For now, political science and sociology provide only weak guidance as to what would be “correct” behaviors for DIME manipulations. Lastly, one of the fundamental issues in testing is the ability to isolate and repair the sources of discrepancies between the outcome that was expected and the outcome that is observed. Even with a solid notion of correctness of model predictions, this can be a difficult problem. For DEMS, evolution

DIME (Diplomatic, Information, Military and Economic Power) Effects Modeling System 271 of a set of useful models will require a strong approach to separating the effects of initial conditions, model parameter settings and model structure.

CONCLUSION We have reported on the requirements and technology-base for a suite of models to support intheater assessment and prediction of the effects of Diplomatic, Informational, Military and Economic (DIME) activities on the political, economic and social infrastructure. Of particular interest is the ability to model the spread of ideas, motivations and beliefs within the non-combatant population and how to apply these models to the nature of brain function and in rehabilitation applications. The challenges associated with this research area include understanding the causality between elements of the population, formulating models that are both sensitive and computable, and validating the predictions of a population’s beliefs and intentions at some future time. This research focuses on providing insight on the specification of a DEM model. It proposes what the desired properties would be and describes the architecture the DEM would be situated in. Additionally, this report evaluated 24 sources regarding the most promising uses of social modeling in computer science, biology, sociology, and political science to derive the most desirable characteristics of the DEM model and to anticipate where it would present challenges. The report also evaluated how such a system would be verified and validated. Biswal and associates [21] compiled the largest publicly-accessible fMRI dataset, consisting of over 1,400 scans from 35 different centers. All of the data, along with some tools for analysis, are freely available for download from NITRC [22]. One might wonder why an fMRI dataset of this scope has not been assembled until now; after all, fMRI isn’t that new a technique, having been around for about 20 years now. The answer (or at least, one answer) is that it’s not so easy–and often flatly impossible–to combine raw fMRI datasets in any straightforward way. What allowed Biswal to consolidate datasets to such a degree is that they focused exclusively on one particular kind of cognitive task. Or rather, they focused on a non-task: all 1400+ scans in the 1000 Functional Connectomes Project are from participants being scanned during the “resting state”. The typical finding is that, when you contrast this resting state with activation during virtually any kind of goal-directed processing, you get widespread activation increases in a network that’s come to be referred to as the default network. One of the main (and increasingly important) applications of resting state fMRI data is in functional connectivity analyses, which aim to identify patterns of co-activation across different regions rather than mean-level changes associated with some task. The fundamental idea is that one can get traction on how the brain operates by studying how different brain regions interact with one another spontaneously over time, without having to impose an external task set. The newly released data is ideal for this kind of exploration, since you have a simply massive dataset that includes participants from all over the world scanned in a range of different settings using different scanners. Biswal et al. report that functional parcellation of the brain using seed-based connectivity (i.e., identifying brain regions that co-activate with a particular “seed” or target region shows marked consistency across different sites, revealing what Biswal et al. call a “universal architecture”. This type of approach by itself isn’t particularly novel, as similar techniques have been used before. But no one’s done it on anything approaching this scale as it has been in computer science with the results reported in Figure 10.

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Figure 10. Functional parcellation of the brain using seed-based connectivity [see Biswall et al.].

One can observe that different seeds produce difference functional parcellations across the brain (the brighter areas denote ostensive boundaries).

REFERENCES [1] [2]

[3]

[4]

[5] [6]

Leisman G, Koch, P. Networks of Conscious Experience: Computational Neuroscience in Understanding Life, Death, and Consciousness. Rev. Neurosci. 2009;20(3):151-176. Leisman G, Machado C, Melillo R, Mualem R. Intentionality and “free-will” from a neurodevelopmental perspective. Front Integr Neurosci. 2012;6:36. doi: 10.3389/ fnint.2012.00036. Supekar K, Menon V, Rubin D, Musen M, Greicius MD. Network analysis of intrinsic functional brain connectivity in Alzheimer's disease. PLoS Comput Biol. 2008;4:e1000100. doi:10.1371/journal.pcbi.1000100. Achard S, Salvador R, Whitcher B, Suckling J, Bullmore E. A resilient, low-frequency, smallworld human brain functional network with highly connected association cortical hubs. J. Neurosci. 2006;26:63–72. Sporns O, Honey C.J. Small worlds inside big brains. Proc. Natl. Acad. Sci. USA. 2006;103:19219–19220. Bullmore E, Sporns O. Complex brain networks: graph theoretical analysis of structural and functional systems. Nat. Rev. Neurosci. 2009;10:186–198.

DIME (Diplomatic, Information, Military and Economic Power) Effects Modeling System 273 [7]

[8] [9]

[10] [11] [12] [13] [14]

[15]

[16]

[17] [18] [19]

[20] [21]

[22]

Micheloyannis S, Pachou E, Stam CJ, Vourkas M, Erimaki S, Tsirka V. Using graph theoretical analysis of multi channel EEG to evaluate the neural efficiency hypothesis. Neurosci Lett. 2006;402:273–277. Stam CJ. Functional connectivity patterns of human magnetoencephalographic recordings: a ‘small-world’ network? Neurosci Lett. 2004;355:25–28. Bassett DS, Bullmore E, Verchinski BA, Mattay VS, Weinberger DR, et al. Hierarchical organization of human cortical networks in health and schizophrenia. J. Neurosci. 2008;28:9239–9248. Meunier D, Achard S, Morcom A, Bullmore E. Age-related changes in modular organization of human brain functional networks. Neuroimage. 2009;44:715–723. Marreiros SJ, Kiebel KJ, Friston. Dynamic causal modelling for fMRI: a two-state model. NeuroImage. 2008;39(1):269–278. Andersen RA, Pesaran, B, Mitra P, Meeker D, Shenoy KV, Cao S, Burdick JW. Cognitive state machine for prosthetic systems. US Pat. 6,952,687 B2 Oct. 4, 2005. Watts DJ, Strogatz SH. Collective dynamics of 'small-world' networks. Nature. 1998;393(6684):409–410. Toch, H. Violence from without and within: safety. In: Braswell M, Montgomary Jr R, Lombardo L, editors. Prison violence in America. 2nd ed. Cincinnati, OH: Anderson Publishing; 1994. p. 11-26. Marquart J, Crouch B. Judicial reform and prison control: The impact of Ruiz vs Estellean on Texas penitentiary. In: Braswell M, Montgomary Jr R, Lombardo L, editors. Prison violence in America. 2nd ed. Cincinnati, OH: Anderson Publishing; 1994. p. 265-290. Patrick S, Dorman PM, Marsh RL. Simulating correctional disturbances: The application of organization control theory to correctional organizations via computer simulation. J Artif Societies Soc Sim. 1999;2(1). http://jasss.soc.surrey.ac.uk/2/1/1.html Tuckman, BW. Developmental sequence in small groups. Psychol Bull. 1965;63:384-399. Langton N, Robbins SP. Fundamentals of Organizational Behaviour. 3rd ed. Ontario, Canada: Pearson Education; 2006. Leisman G. Children’s language production: How cognitive neuroscience and industrial engineering can inform public education policy and practice Forum on Public Policy. A Journal of the Oxford Roundtable. 2012;2012(1):1-14. Ng B, Varoquaux G, Poline J-B, Thirion B. A novel sparse graphical approach for multimodal brain connectivity inference. Med Image Comput Comput Assist Interv. 2012;15(Pt 1):707-714. Biswal BB, Mennes M, Zuo XN, Gohel S, Kelly C, Smith SM, Beckmann CF, Adelstein JS, Buckner RL, Colcombe S, Dogonowski AM, Ernst M, Fair D, Hampson M, Hoptman MJ, Hyde JS, Kiviniemi VJ, Kötter R, Li SJ, Lin CP, Lowe MJ, Mackay C, Madden DJ, Madsen KH, Margulies DS, Mayberg HS, McMahon K, Monk CS, Mostofsky SH, Nagel BJ, Pekar JJ, Peltier SJ, Petersen SE, Riedl V, Rombouts SA, Rypma B, Schlaggar BL, Schmidt S, Seidler RD, Siegle GJ, Sorg C, Teng GJ, Veijola J, Villringer A, Walter M, Wang L, Weng XC, WhitfieldGabrieli S, Williamson P, Windischberger C, Zang YF, Zhang HY, Castellanos FX, Milham MP. Toward discovery science of human brain function. Proc Natl Acad Sci USA. 2010 Mar 9;107(10):4734-4739. Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC). (cited 2012 Aug 15). Available from: http://www.nitrc.org/projects/fcon_1000/.

Received: January 31 2012 Revised: August 15, 2012 Accepted: February 15 2013.



ANATOMICALLY ACCURATE HEAD MODELS AND THEIR DERIVATIVES FOR DENSE ARRAY EEG SOURCE LOCALIZATION Jasmine Song1, Kyle Morgan1, Sergei Turovets1, 2, Kai Li1, Colin Davey1, Pavel Govyadinov2, Phan Luu1, 3, Kirk Smith4, Fred Prior4, Linda Larson-Prior4, and Don M. Tucker1, 3 1

Electrical Geodesics, Inc., Eugene, OR USA Neuroinformatics Center, University of Oregon, Eugene, OR USA 3 Department of Psychology, University of Oregon, Eugene, OR USA 4 Electrical and Optical Imaging, Neuroimaging Laboratory, Washington University, St. Louis, MO USA 2

ABSTRACT Electroencephalography (EEG) is a brain imaging technology that is noninvasive, cost effective, and provides millisecond temporal resolution. Improved spatial resolution of EEG measures can benefit multiple clinical and research applications, including the assessment of Traumatic Brain Injury (TBI), stroke, and neurodevelopmental disorders. Recent advances in electrode arrays have made it feasible to achieve dense array sampling (128, 256 and 512 channels) of brain potentials on the head surface, and then localize the sources of the measured fields to the surface of the cortex to provide spatially resolved information. Accurate dense array source localization requires i) moving beyond simplistic models of the human head (such as homogeneous multi-shell spheres) and ii) accurate knowledge of regional conductivities of head tissues. These requirements are particularly important for children because the size, shape and electrical properties of the head tissues undergo rapid developmental changes from infancy through adolescence. In this paper we apply high performance computing with finite difference methods (FDM) to solve the forward EEG problem with skull and head conductivity models that are appropriate for children as well as adults. We show that the improved structural (MRI and CT based) head models may improve high-resolution EEG source localization by correcting systematic biases in EEG source localization due to conductivity misspecifications and structural uncertainties. We also demonstrate how these same advances in electromagnetic head models may be used to model effects of non-invasive brain stimulation such as Transcranial Magnetic Stimulation (TMS) and Transcranial Electrical Stimulation (TES).

Keywords: EEG, pediatric, atlases, models, source localization, MRI, CT, SEP, mismatch



Correspondence: Sergei Turovets, PhD, Electrical Geodesics, Inc., 1600 Millrace Dr. Suite 200. Eugene, OR, 97403, USA E-Mail: [email protected].

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Jasmine Song, Kyle Morgan, Sergei Turovets et al.

INTRODUCTION Electroencephalography (EEG) provides important information on brain activity for a range of applications, including research on normal cognitive development in children, brain monitoring of neonates in intensive care, and early detection of brain pathology such as epilepsy. In adults, imaging technologies may use ionizing radiation (computed tomography (CT) or radionucleotides (positron emission tomography (PET), single photon emission tomography (SPECT), or they may require that the subject remains still during image acquisition (magnetic resonance imaging (MRI) or CT). In children, radiation exposure and sedation are particularly problematic. Better spatial resolution for the inexpensive and noninvasive EEG measure, such as through accurate source localization, could improve both research and health care [1]. A fundamental limitation to the use of source localization techniques lies in the relatively sparse sensor arrays used in standard EEG monitoring systems (19-21 electrodes in the standard 10-20 system). These conventional recording arrays provide inadequate spatial coverage [2] both in terms of the inter-electrode distances (~5 cm) and the coverage of basal regions of the head [3]. Many laboratories now acquire data from dense arrays of 64, 128, or 256 channels [4]. By increasing the spatial sampling of the volume and decreasing the inter-electrode distance, dEEG has been shown to provide a significantly improved spatial resolution from scalp recorded data [5]. At present, the use and validation of dEEG and Electromagnetic Source Imaging (ESI) in infants and children is hindered by the lack of accurate pediatric head models. To generate an ESI solution, two independently specified problems must be solved: (1) the forward problem, or volume conduction head model, which includes a set of conditions that specify the way in which currents propagate from their site of generation at the cortex to the site of measurement at the scalp, and (2) the inverse problem. The inverse problem requires mapping the recorded surface potentials to the cortical sources space in the volume conductor model, and this is a problem for EEG because it is highly underspecified. While many studies have shown that “realistic” volume conductor head models generate more accurate ESI solutions [2, 3, 6], the impact of the structural head tissue geometry, conductivity specifications, computability and necessity of additional variables such as tissue anisotropy or inhomogeneity remain poorly understood [7, 8]. These parameters are particularly critical for infants and children, where both shape and density of the skull and the structure of the cortex cannot be approximated by adult head models [9, 10]. The human skull and brain undergo rapid and significant growth from birth to about 2 years of age, with slower but continued growth through the 6th postnatal year [9-11]. Ossification of the skull begins at approximately 11 weeks gestational age [12] and is not fully complete until the 3rd to 4th decade of life [11]. While adult bone represents a layering of cortical (external and internal) and diploic bone, infant cranial bone (birth – 6 months of age) is primarily cortical bone [13]. This difference can be expected to lead to a significant change in skull resistivity from infancy to adulthood [14]. In addition, the developing skull exhibits large discontinuities, the fontanels (Figure 2a, 3a and 5 in this paper), which form at the intersection of 3 or more ossifying bone edges. These usually ossify over the first 2 years after birth, but the cranial sutures remain incompletely ossified at least until early adulthood. The open sutures and fontanels, as well as the unique shape of infant heads, must be modeled for accurate source localization [6 -8,18-23]. In addition to differences in the bony cranium, significant changes in brain volume, regional tissue composition and ventricular volume are seen in infants and children. The few imaging studies of normal brain development in children from birth to 2 years report that this is a period of significant dynamic micro- and macro-structural change [9,10]. During this period, brain volume increases 115%, lateral ventricular volume increases an amazing 288%, and white matter volume, a reflection of axonal myelination, increases substantially. This rapid growth trajectory is maintained into the 10th

Head Models for dEEG Source Localization

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year and is further reflected in differences in fractional anisotropy and mean diffusivity across the developmental period [15]. The importance of including age-specific regional brain anisotropy is not fully understood. The human brain exhibits large changes in regional anisotropy between the ages of 0-9, in addition to major changes in brain and tissue volumes from ages 0-2 that almost certainly are of critical importance to accurate modeling. In the course of creating accurate and useful pediatric head models, it would be useful to evaluate the age ranges in which changes in brain and tissue volume, in addition to regional anisotropies, significantly impact the accuracy of electrical source localization. Several studies have addressed the issue of conductivity parameter misspecifications in adult head models including anisotropy and inhomogeneity. The effects of these parameters have been studied using analytic forward solutions in multi-shell spheres or MRI-based boundary element models (BEM) and finite element models (FEM) [18, 19, 38]. For example, Pohlmeier et al. [20] showed that by using an equivalent dipole approach (continuous dipole fit) one can obtain up to a 6 mm error increase with 20% skull misspecifications in both spherical and realistically shaped models. The uncertainty in the reported skull conductivity data range, in fact, can be up to a factor of 10. On the other hand, simulations by Huiscamp et al. [21] showed source localization error up to 20 mm for conductivity misspecification. More recently, Acar and Makeig [22] reported effects of forward model variation and mismatch on EEG source localization in adults using the BEM and equivalent dipole techniques. They compared models derived from subject specific MR images and models warped to digitized individual head shapes from the MNI adult atlases [24] as well as the best fit spherical models. The four-layer (warped to electrodes) MNI models were found to be the best approximations to the ground truth of the individual head models for four adult subjects. We are unaware of similar studies in children across the developmental spectrum, except the paper by Roche-Labarbe et al. [23] on neonatal head BEM simulations with structural variations (fontanels, the whole skull layer). In our approach, the subject head model geometry is created through: (1) high-resolution segmentation of head tissues, (2) cortical ribbon surface extraction with topology correction (to insure a correct and continuous surface), and (3) tessellation of the cortical surface (for example, 1 cm squares) for dipole seeding. This detailed geometric model is then populated with the estimated conductivity for each tissue. At this point the forward model can be used to create the subject specific Lead Field Matrix (LFM) by individually activating each current dipole with unit magnitude and calculating the resultant scalp electrical potentials at the sensor locations. A complete formal description of the forward and inverse problems has been presented previously [1,27, 28, 40]. The structural changes that mark the development of the skull and brain are accompanied by changes in brain function and cognition [29]. While simple cognitive functions such as processing of sensory information and responses to sound and language are present at birth, the integration of higher order cognitive coordinating centers such as the prefrontal cortex show a protracted course of development [30]. Anomalies in the development of cerebral connections are relevant to a number of developmental disorders, including attention deficit hyperactivity disorder (ADHD), autism spectrum disorders (ASD) and schizophrenia (SZP). At least some of the characteristic features of these disorders have been attributed to disruptions in dynamic neural network interactions [31], a full elucidation of which requires neuroimaging with adequate temporal resolution. Although changes in network dynamics might be quantifiable using electrophysiological methods alone, the greatest benefit would derive from a clear definition of regional components of such networks. For that reason, accurate head models that would enable finer scale resolution of anatomical regions involved in network interactions using dEEG represent a much-needed tool. Furthermore, such head models would aid in the development of non-invasive multi-modal imaging by enabling the co-registration of age-specific anatomical images. This need, which is currently being addressed in adult populations, is particularly wanting in infants and children.

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In this paper we conducted a simulation study based on Finite Difference Modeling (FDM) to examine the error when a rescaled or warped adult head model, an older child’s head model, or inaccurate skull conductivities, are used in pediatric ESI. Specifically, we analyzed several pediatric head models based on: (1) the reference model, a 6 month old infant MRI co-registered with the infant’s own CT; (2) the same MRI with warped adult CT atlas skull, with no fontanels but with adjusted thickness; (3) a child head model from a preschool age group warped to the 6 month old infant head shape; (4) a child head model from a teenage group warped to the reference infant head shape; and (5) an adult male head model warped to the reference infant head. In contrast to previous studies, where a skull compartment was derived from MRI, we used the infant’s or children’s own CT in all models. The CT provides an excellent representation of bone structure and density of the skull, the most resistive tissue of the head and therefore having the largest impact in electrical modeling. All models have differentiated five tissue layers: scalp, skull, CSF, brain grey matter (GM) and white matter (WM), as well as internal air pockets in sinuses and throats. The effects of geometry variations (such as the presence or absence of fontanels) and the skull conductivity variations were also examined systematically. All models were analyzed for six skull conductivity values, ranging from the lowest value reported in the literature 0.004 S/m through the average adult value 0.018 S/m to the average scalp conductivity (effectively no skull). The "synthetic ground truth" EEG was generated separately in each model for the “true” conductivity value. In the model mismatch studies, the ground truth EEG was generated in the reference infant model. Inverse solutions were examined in the true, warped, or modified models using minimum norm (MN) and sLORETA methods of distributed linear inverse source localization [8]. In addition, we examined the impact of different resolutions in medical images and FDM computation on ESI accuracy comparing the source localization results in the reference infant models for 0.5 mm, 1 mm, and 2 mm FDM resolutions. Finally, we illustrated the impact of model mismatch on source localization accuracy with a Somatosensory Evoked Potential (SEP) experiment with two adults. The mismatched models were created intentionally by warping or geometry swapping with a different subject’s head model.

METHODS All research retrospective and prospective protocols involving human subjects were approved by Institutional Review Boards (IRB) at both project sites (Eugene, OR and Saint Louis, MO), with informed consent obtained from the subjects recruited in the prospective studies. Figure 1 summarizes the head model creation, data collection, and model analysis path. Each of the steps starting with structural anatomical data and ending with source localization on cortex is outlined in Figure 1 and described in detail below. MRI and CT data collection: The reference models of soft head tissues for adult subjects were derived from T1-weighted MR images of the heads of a 36-year-old healthy Asian male (subject A1) and two healthy Caucasian males: a 42-year-old (subject A2), and the Atlas Man (subject A0, also known as Colin27 at the MNI website [24]). The first two images were obtained with a 3T Allegra and the third with 1.5 T Magnetom Symphony scanners (Siemens Healthcare, Erlangen, Germany). The bone structure for these three subjects was derived from CT scans recorded with a GE CT scanner (General Electrics, Fairfield, United States). The acquisition matrix was 256 × 256 × 256 with a voxel size of 1mm × 1mm × 1mm in both the CT and T1 scans. Retrospective pediatric CT and MRI data were acquired by data mining the clinical image repository of the Washington University BJC Health System in St. Louis, Missouri, United States. A query preparatory to research was conducted against a system that indexes Radiology reports [37]. This initial query identified 174,000 possible pediatric records. The more focused search on recent years 2006-2012 and based on the search string “CT+MR+CH (Children’s Hospital)” was submitted


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to the repository and yielded 11,000 potentially useful cases. Based on an initial sampling of this data, we predicted a 5% acceptance rate of data appropriate for constructing pediatric head models. An additional search term indicating head/brain (CT + MR + brain + head + CH) resulted in a total 2,500 exam reports. Search criteria were iteratively refined by review of radiology report text for actual presence of both MRI and CT scans, and by no more than a 6 month time interval between the two scans. As a result, 385 subjects were selected for retrieval and visual examination using a research PACS (Philips Healthcare, Andover, MA). Exclusion criteria were further refined through visual inspection for gross anomalies, resulting in data for 131 subjects being selected, de-identified, and entered into the study. Further reduction in the subject population occurred during morphometric analysis and visual inspection due to factors such as clipped field of view and subtle motion artifacts. Ultimately a total of 63 usable pediatric subjects (covering the age range between 0 to 18 years old) were entered into analysis. This represents 16% of the 385 subjects that passed initial screening or 0.04% of the initially identified potential subjects available in the clinical repository.

Figure 1. The diagram showing the data and workflow in source localization. MRI and CT may be subjectspecific or warped from atlases. Sensor locations may be also subject-specific from Geodesic Photogrammetry System [36], or based on average sensor locations. Conductivities may be estimated [28] or values from the literature may be used. Lead fields calculation performed with FDM (this paper) or other known methods (FEM, BEM) [7]. Inverse matrix may be one of the published methods, e.g.: Minimum Norm, LORETA, sLORETA and LAURA [8].

Somatosensory EEG data collection experimental paradigm and recording: Two adult male subjects (A1 and A2) were positioned in a comfortable chair with their feet flat on the floor and rested their head on a chin-rest to avoid head movement artifacts. Each participant was instructed to remain relaxed and refrain from blinking as much as possible while staring at a fixation point throughout the

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EEG recording. Digit I of the left and right hands were stimulated individually using a custom-made piezo-electric stimulator. During the recording, the piezo was lightly taped to the digit of interest, and the participant’s hand was placed between two cotton towels to muffle the “tap” sound created by the stimulator. The stimulations were segmented into blocks in which each digit was stimulated at a rate of 2Hz for 200 seconds, resulting in 400 trials per block. Each digit was stimulated for one block before the tapper was moved to the other hand, and then was moved back once, resulting in 4 staggered blocks and 800 trials per digit. EEG was acquired using a 256-channel array EGI EEG 300 system and sensor positions were determined using the Geodesic Photogrammetry System (GPS) [36]. Head Model Construction: To build anatomically accurate head model geometry, the T1 MRI images were automatically segmented into seven tissue types (brain gray matter, brain white matter, CSF, scalp, eyeballs, air and skull), and then the CT images were coregistered (or warped) to the MRI using EGI’s segmentation and image processing package, BrainK [32,33]. BrainK is a set of automated procedures for characterizing the tissues of the human head from MRI, CT, and photogrammetry [36] images. BrainK achieves five major tasks: (1) image segmentation, (2) registration of head model components (MRI, CT, and EEG sensor positions from Geodesic Photogrammetry), (3) cortical surface extraction, (4) tessellation of the cortical surface for oriented dipoles, or generation of dipole triples on the gray matter grid, and (5) Talairach transformation (not used in the present analyses). BrainK MRI segmentation recognizes the white matter (WM) and the gray matter (GM). It partitions these into two hemispheres and it differentiates cerebellum from cerebrum. In addition, an entire head mask and the two eyeballs are recognized as well in the segmentation component. The eyeballs are important for the electrical head model because of the large far fields generated by their cornea-retinal potentials. In the development of BrainK, Li [32] introduced a novel Relative Thresholding (RT) method for accurate tissue segmentation in the presence of MRI field inhomogeneity. Given the results of RT performed on a region of interest (ROI), BrainK also implements a novel sophisticated morphological image analysis (SMIA) technique and a cell complex based morphometric image analysis (CCMIA) method for white matter extraction, gray matter extraction, scalp extraction, and, topology correction of the cortical surface mesh. BrainK uses a priori knowledge (including structural, geometrical, and morphological observations on the neuroanatomy, and radiological observations on the structural imaging) to enable automated, accurate, and fast segmentation (performed by a trained technician in 20-30 minutes). Once the initial tissue segmentation has been conducted, there are several workflow paths that can be chosen based on the available subject specific data. Each workflow scenario represents a different way in which a skull can be registered. For example, the scenario Atlas to MRI is used when an individual CT scan is unavailable but an individual T1 MRI is. In this scenario, an adult atlas skull will be registered to the MRI geometry and will act as a guide for bone placement within the head. Due to the developmental differences in skull geometries in infants (i.e. presence of fontanels), an individual CT is always preferred. In this study, the workflow CT to MRI was used to generate all subject specific head models; a scenario that takes a subject’s own CT and warps it to the geometry defined in the MRI. In all scenarios, when the skull registration is conducted, the resulting head segmentation includes the following tissue types: WM, GM, CSF, bone, flesh, eyeball and air, in which the WM and the GM are further partitioned into two cerebral hemispheres and the cerebellum (Figure 2a). For all workflow scenarios, following skull registration, a generic Geodesic Sensor Net spherical sensor cloud is warped onto the head contour of the subject. For the scenarios of Atlas to MRI, MRI to CT, and CT to MRI, an additional sensors-to-head registration procedure is conducted to register the EEG sensor position cloud onto the head surface using several fiducial landmarks. For the scenario Atlas to EEG sensors, an individual sensor cloud from Geodesic Photogrammetry acts as a template


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for which any given head model warps to the physical positions of the sensors measured with photogrammetry. This allows users to rescale a generic head model atlas to the individual’s actual head shape. A head model (one that has a full brain segmentation and skull registration) is required to be completed before sensor transformation can be accomplished. After sensor registration, dipoles are allocated in two modes: oriented or triples. If the individual’s MRI is available, the cortical surface is extracted, tessellated into patches, and an oriented dipole is fitted to the vector sum of the normals of all the triangles in the surface mesh of each patch, thereby describing an equivalent dipole model for that surface patch. If the individual’s MRI is not available, then triple dipoles (fitting x, y, z components of the unknown orientation) are distributed evenly throughout the cortical gray matter of an atlas brain on a regular grid with a user specified spacing (typically 7 mm or 5 mm).

Figure 2. (a) BrainK Segmentation and CT to MRI coregistration differentiating scalp, skull, CSF, GM and WM in model C1 (a 6 month old subject). (b) A 128 sensor net registered on the same infant head. (c) Cortical surface generated. (d) Oriented dipoles set assigned to each cortical.

Forward Problem: The relevant frequency spectrum in EEG and MEG is well below 1 kHz, and most studies deal with frequencies between 0.1 and 70 Hz. Therefore, the volume conduction in EEG/MEG can be well described by the quasi-static approximation of Maxwell’s equations, the Poisson equation. The electrical forward problem can be stated as follows: given the positions, orientations and magnitudes of current sources, as well as geometry and electrical conductivity of the head volume Ω calculate the distribution of the electrical potential on the surface of the head (scalp) ΓΩ. Mathematically, it means solving the linear Poisson equation [7]:  ()=S, in 

(1)

with no-flux Neumann boundary conditions on the scalp: ()  n = 0, on ΓΩ .

(2)

Here  = ij(x,y,z) is an inhomogeneous tensor of the head tissues conductivity and S = -I ( r-r+) +I ( r-r-) is the source current configuration constructed in the simplest case from a source and a sink of strength I at the vector locations r+ and r- . Having computed potentials (x,y,z) and current densities J=- (), the magnetic field B can be found through the Biot-Savart law. In this paper, we do not consider anisotropy or capacitance effects (the latter because the frequencies of interest are too small), but they can be included in a straightforward manner. Eq. (1) becomes complex-valued, and complex admittivity should be used [7, 38].

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Lead Fields Calculations and Numerical Implementation: Lead Fields are defined as forward projections of unit strength dipoles’ potential fields from cortex to scalp sensors. It is a matrix with the dimension: number of sensors (typically 256 or 128) by number of dipoles (typically 2400). The EEG session specific LFM requires a session specific set of sensor coordinates. A generic LFM for a given subject head volume can be calculated for more dense coverage of scalp (several thousand points) and then potentials for session specific sensor locations interpolated from this generic LFM on scalp. It can be accomplished by the “brute force” approach launching separately the forward solver for each dipole position. However, one can reduce the required number of forward solutions drastically by using the reciprocity principle for LFM calculations [7, 38, 40]. We have implemented both these approaches as they can be parallelized effectively in a multi-core cluster environment or desktops with modern Graphic Processing Units (GPUs: http://www.gpgpu.org/). To solve Eq. (1) numerically we built a finite difference forward problem solver for the volume conduction based on the multi-component alternating directions implicit (ADI) algorithm [27,28, 40]. The numerical method is a generalization of the classic ADI algorithm, but with improved stability in 3D. We chose the FDM approach over FEM and BEM methods for its simplicity of implementation from the MRI/CT tissue segmentation map that produces a cubed lattice of nodes. Therefore, meshes are easy to construct (once segmentation is accomplished) as the cubic/rectangular elements can be mapped directly from the voxels of the medical images (3D MRI/CT scans), including all relevant anatomical details (in contrast to BEM and FEM). To set up the boundary conditions in the heterogeneous biological media within a complex geometry like the human head, the method of the embedded boundaries is used in FDM. Here an object of interest is embedded into a cubic computational domain with extremely low conductivity values in the external complimentary regions. This effectively guarantees there are no current flows out of the physical area (the Neumann boundary conditions, Eq. (2), is naturally satisfied). The forward computations using high resolution structural models and the inverse conductivity search, which is composed of multiple forward solutions, represent computationally intensive tasks and require high performance computing. The electrical forward and inverse conductivity optimization models have been implemented in a parallel C/C++ code (OpenMP and MPI) and CUDA to run on multi-core cluster and GPGPU platforms [27,40]. EEG Source Localization: Estimating the source of EEG with distributed source models consists in first, allocating a grid of unit strength dipole sources with fixed locations and orientations in the whole brain volume or on the cortical surface, computing LFM for this dipole set, and then, estimating inverse solution for amplitudes of dipoles on this grid using the computed LFM and the scalp EEG data. For fixed positions and orientations, at a given time, the relation between source moments and the data can be stated as:

  KJ   , N 1

(3) N 1

where  ° e is the electric potential;J ° j is the (unknown) amplitude and orientation of N N source distribution;K ° e j is the lead field matrix linking the current sources to the electric potential;  °

N e 1

is the additive noise component (perturbation); N e is the number of electrodes;

N j is the size of source distribution; N d is the number of dipoles. Estimating the source amplitudes consists in solving this noisy linear system. Considering the physics of data formation in EEG, source estimation is ill-posed ( Ne = N j ). For a given data set,



there is no unique source distribution. Further, after discretizing to a limited number of sensors, the corresponding K operator is ill conditioned, thus the solution is highly sensitive to small perturbations

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in data and the model. This problem belongs to the linear ill-posed inverse problems. Methods for solving this problem, called inverse procedures, must take regularizing schemes into account to prevent the oscillatory behavior of the solutions in presence of noise. The basic regularization methods range from constrained Minimum Norm (MN) [2-5,8] to minimization of regularized least-square cost functions such as:





2 Jˆ  arg min   KJ   L(J ) , J

where

 is a positive scalar that is called the regularization parameter, and balances the data fidelity 2

2

  KJ and prior term L(J ) ;  represents the square of the l2 -norm. The prior regularization operator L(g) contains the priors that one wishes to take into account. For example, this term

operator can be taken in the form of the identity operator, which produces solutions with a minimum norm (MN), the gradient or weighted Laplacian operators (LORETA), local autoregressive average (LAURA), cortical surface laplacian (CSL), l1 -norm of the source amplitudes. In this paper, the MN

and sLORETA [8] methods for the EEG inverse problem are used. The analytic solution for the MN 1

1/2 T T method is Jˆ  K  KK   I N e   . The sLORETA solution is following: Jˆl   C Jˆ  Jˆl , ll

th th where Jˆl is the current density estimate at the l dipole and  C Jˆ  is the l diagonal of

ll

1

C Jˆ  K  KK T   I N e  K

, for l= 1, …, Nj. The distributed inverse problems can be divided into two scenarios. Scenario 1 (triple dipoles) estimates an unknown current density distribution, including both orientations and amplitudes of the source distribution. Scenario 1 assumes N j  3N d and K ° T

square (RMS) R   R1 ,L , RN d  °



T

J   J ,L , J Nd  °   1

N j 1

N d 1

is defined as Ri  T

N e 3N d

J

2 i,x

in Eq. (3). The root mean

2 2  J i,y  J i,z

 3, where

, J i   J i,x J i,y J i,z  ° , for i  1,L , N d .  Scenario 2 (oriented dipoles) estimates only unknown amplitudes of the source distribution given known orientations of dipoles. Since Scenario 2 assumes N j  Nd in Eq. (3), there is no need in 31

calculation of RMS.

RESULTS Model Warping Several head models based on 3 original retrospective pediatric MRI/CT volumes (C1, C2, C3), and 3 prospective adult MRI/CT volumes (A0, A1 and A2) were created (see Table 1). The pediatric models represent the most distinct developmental age clusters [37]: infants 0 – 2 years old (C1), preschoolers 2- 6 years old (C2) and school age children 6 – 17 years old (C3). In most studies presented here, an infant model (C1, see Figure 2) for a 6 month-old was chosen as the ground-truth reference model. It was compared with derivative models from a preschooler pediatric model (C2) (6

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years old), a teenager head model (C3) (14 years old), and an adult model (A1) to assess the effects of head model mismatch on source estimation results. The notations for those rescaled models (warped to the physical size of C1, but retaining the original morphology and having LFMs recalculated) are: C2’, C3’, A1’ (see Table 2). We also created a 6 month old model with only the adult skull atlas (A0) warped and adjusted by thickness to match subject C1’s specific MRI (notation A0s) and an adult mismatched model (A2 warped to A1, A2’). In all cases of warping the older age models to the reference infant model C1 the fontanel structure was lost (see Figure 3).

Figure 3. Skulls of three typical geometries. (a) The reference infant model C1 contains frontal and occipital fontanels. (b) Skull of the warped model A0s (only skull of A0 warped and adjusted to C1 MRI). (c) Skull of the warped model A1’ (the whole adult head rescaled to the infant size). Notice that warped models have no fontanels. Table 1. The original human subject models Age (years) Gender Original MRI/CT

C1 0.5 NA yes

C2 6 NA yes

C3 14 NA yes

A0 NA M yes

A1 36 M yes

A2 42 M yes

Table 2. Derivative head models Warped Target Model All Tissue Warped Average Literature Values for Tissue Conductivity Derivative LFM

C2’ C1 Yes Yes

C3’ C1 Yes Yes

A1’ C1 Yes Yes

A2’ A1 Yes Yes

A0s C1 No (skull only) Yes

Yes

Yes

Yes

Yes

Yes

The quality of the warping process can be evaluated based on the data presented in Tables 3 and 4, which show distances between left and right prearicular fiducial landmarks in the original models and after rescaling. The distances after warping match the original C1 model fiducial distance with accuracy better than 1% and about 0.1% in warping A2 to A1. Table 3. Distance between Fiducial Landmarks for Original Head Models Model Distance (cm)

C1 12.24

C2 13.73

C3 14.81

A1 15.88

A2 15.64

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Head Models for dEEG Source Localization Table 4. Distance between Fiducial Landmarks for Warped Head Models Model Distance (cm)

C2 12.20

C3’ 12.12

A1’ 12.16

A2’ 15.90

Effect of Head Geometry Mismatch on Source Estimation Accuracy For this evaluation, a forward projection from a dipole source (near the occipital fontanel) oriented perpendicular to its corresponding cortical patch was generated (Figures 4a and 4b). For all head models used to estimate the source shown in Figure 4a, LFMs were generated using three orthogonal moments for each dipole location (“triples”). For all LFM calculations, the following conductivity values were used based on the average literature values: 0.46 S/m (scalp), 0.018 S/m (skull), 1.79 S/m (CSF), 0.25 S/m (GM), 0.33 S/m (WM). To investigate the model mismatch effects we compared estimated source solutions obtained from the original model (C1) and the derivative models (C2’, C3’, and A1’). The MN technique was used to estimate the sources. The metric employed for source localization accuracy in this paper is the localization error distance (LED). The LED is the Euclidean distance between the locations of the true dipole and the dipole with maximum intensity in the source estimation. Smaller LEDs represent more accurate estimates.

Figure 4. Source estimates as a function of head model. (a) Location of source generator from C1; (b) Forward projection of scalp potential for dipole shown in (a); (c) ESI solution obtained with C1 model; (d) ESI solution obtained with C2’ model; (e) ESI solution obtained with C3’ model; (f) ESI solution obtained with A1’ model.

Table 5. LED of ESI solutions as a function of head geometry Model LED

C1 10.5 mm

C2’ 16.5 mm

C3’ 15.6 mm

A1’ 32.7 mm

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As shown in Table 5, the LED is minimal when a head model matches the model that generated the scalp potential data. When a subject specific head models are not available, the warped older pediatric group models (C2’ and C3’) are still reasonable for EEG source localization (LEDs are increasing in this case up to 16 mm). The warped adult model, A1’ resulted in the large localization error of ~33 mm.

Effect of Head Model Resolution on Source Estimation Accuracy The motivation of this study is the fact that an infant head is about twice as small as an adult head and the skull is thinner. Therefore, it is reasonable to expect that a higher resolution model would be required for an infant head to match the same finite difference node density per skull voxel in adults captured by 1 mm resolution images. Another reason is that a current dipole is approximated in FDM as two monopoles at adjacent finite difference grid nodes with the amplitude I (Eq. 1) divided by the voxel volume. Therefore, the overall forward projection will be more accurate for the higher FDM resolution. Resampled subject C1 head volumes were created from the original 1 mm resolution C1 head model. In order to manipulate image resolution of the original head model (.88 mm × .88 mm × .9 mm), each voxel of the post-processed data is either merged with its 6 neighboring voxels or subdivided into 8 separate voxels, thus decreasing and increasing image resolution respectively (Figure 5).

Figure 5. Head models of a 6-month-old infant (C1) at 2 mm (left), 1 mm (center) and 0.5 mm (right) resolutions. Sagittal slices (top), sensors on scalp (bottom).

When decreasing resolution, sets of merged voxels were given a uniform tissue type based on the tissue type that was most common amongst the group before the merge. Due to aliasing, dipoles that were located in WM as a result of voxel merging were automatically deleted and not used for analysis. When increasing resolution, the subdivided voxels were assigned a single tissue type that matches the tissue of the voxel from which they were derived.


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Figure 5 shows the effect of the mesh resolution variations for the reference infant model, C1. Sagittal slices show the different FDM grid voxel size of 2 mm3, 1 mm3, and 0.5 mm3. It can be seen in Figure 5 that reduction of resolution to 2 mm leads to visible bumps on the scalp surface (bottom left corner) and disruption in skull morphology (upper left corner sagittal view), as the actual anatomical resolution was decreased in this case along with FDM resolution, while transition from the original 1 mm resolution to the interpolated 0.5 mm resolution simply made FDM grid denser but actually did not improve the original image resolution. In this evaluation, the same 128-sensor positions were registered to all three C1 resolution models. A forward projection for one dipole (Figure 6a) using the 0.5 mm resolution model served as the ground-truth location. The forward projections (lead fields) of this dipole in three resolution cases were calculated and plotted versus sensor number (Figure 6b).

Figure 6. Resolution variation effects on source localization: (a) ground truth dipole location near the occipital fontanel on the cortex; (b) forward projection of potentials to EEG sensors (128 channels) as a function of model resolution; (c-e) 3D views of forward projections to scalp; (f-h) ESI solutions (sLORETA) as a function of model resolution.

One can see that the dipole projection to the scalp is tighter (the full width at half maximum (FWHM) is smaller) for the 0.5 mm resolution, while projections of the same dipole forward fields at 1 mm and 2 mm are more diffused as expected. The ESI solutions (Table 6) using the sLORETA technique derived from the 0.5 mm resolution model correctly localized the dipole (LED is 0 mm, no

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resolution mismatch). The source distributions for the lower resolutions are more diffuse, as expected (the error is of 12 mm for this dipole in both mismatched resolutions). Table 6. LED of ESI solutions as a function of model resolution Model Resolution LED

0.5 mm 0 mm

1 mm 12.15 mm

2 mm 11.91 mm

Effect of Tissue Conductivities on Source Estimation Accuracy To evaluate how inaccurate assumptions of tissue conductivities will impact ESI solutions, LFMs were generated for three different models (C1, A0s, and A1’) while varying the skull conductivity (which is the most resistive tissue) across six values (0.004 S/m, 0.018 S/m, 0.1 S/m, 0.2 S/m, 0.35 S/m and 0.45 S/m). This resulted in 18 LFMs. The model with skull conductivity set to 0.1 S/m in each model (assuming that infant bones are more conductive on average than in adults) served as the ground truth. From the ground-truth model, forward projections were generated for each dipole and ESI solutions were derived using MN and sLORETA. The LEDs presented in Table 7 represent the mean LED (i.e., averaged ESI solutions for all dipoles) for each condition. Table 7. Errors of ESI depending from conductivity and/or model mismatch. The mean LEDs are given in mm. The ground truth LFMs for skull conductivity of 0.1 S/m results in the minimal LED in all three geometries with both MN and sLORETA. Method MN

sLORETA

Head Geometry C1 A0s A1’ C1 A0s A1’

0.004 17.25 18.42 19.75 3.72 7.63 10.56

Skull Conductivity (S/m) 0.018 0.1* 0.2 0.35 15.49 15.06 15.12 15.19 16.22 15.18 15.34 15.39 18.26 13.97 14.98 16.27 0.27 0 0 0 1.14 0 0 0.017 4.60 0 0.08 0.54

0.45 15.19 15.46 16.63 0.003 0.066 1.045

As can be seen, LED is minimal for both MN and sLORETA solutions when the conductivity values used in the head model matches with those used to generate the synthetic EEG data. Use of the head models with the correct skull conductivity values results in the minimal LEDs. When skull conductivity is set to be low (skull is more resistive), the LEDs are larger. On the other hand, when skull is effectively replaced bypio soft tissues (conductivity values approaching conductivity of surrounding tissues), the effect is small. The steepest change in LED was observed in the range of conductivities between 0.004 S/m and 0.1 S/m and more pronounced for the rescaled adult head models, A1’. We believe this is due to the fact that the relative skull thickness of adult model A1, even after rescaling, is larger than in the reference infant model C1, therefore the thicker skull conductivity misspecifications have more impact on the forward solution.


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Model Mismatch in SEP experiment This experimental EEG study was motivated by the need to verify our simulation studies. The expected brain activation regions in SEP experiments are generally well known from human brain anatomy and can be further confirmed by an independent fMRI study (ROI in Figure 7). The dEEG data was processed using Net Station Version 4.5.5 software (Electrical Geodesics, Inc, Eugene, United States). Each subject’s data was filtered using a 60 Hz high-pass FIR filter prior to visual bad channel replacement. Manually marked bad channels were replaced using spherical spline interpolation. Data was segmented into 300 ms stimulus-locked epochs from 100 ms prestimulus to 200 ms poststimulus. The ERPs were then averaged and corrected to a 100 ms baseline. Channels contaminated with eye or movement artifacts were identified by a computerized algorithm and were eliminated. Following computerized bad channel replacement, data were mean corrected and referenced to vertex (Cz). ESI using the sLORETA technique was performed on the ~10 ms time window just before the peak of P50 SEP component. Figure 7 shows the ESI solutions for subject A1 and A2 (sLORETA regularization constant of 0.1). In both subject specific models, clear congruency can be seen in source localization relevance to their predefined anatomical ROI. For subject A2 specifically, the S1 thumb region appears to be functionally defined along the posterior and anterior banks of the postcentral gyrus. In order to demonstrate the importance of head geometry on ESI solutions, we generated a new head model, A2’. This model was applied to the SEP data used for the A2 solution. Figure 7, top right corner shows the results. Notice that the bulk of electrical activity has shifted from the posterior and anterior banks of the postcentral gyrus (S1) to the center of the postcentral gyrus and posterior bank of the precentral gyrus (M1) even though the physical contours of the brain have been unchanged.

Figure 7. Effects of model mismatch on SEP localization. Top row left to right: subject A2 highlighted anatomical ROI, A2 model specific ESI solution, A2’ ESI solution for A2 SEP data (mismatch). Bottom row left to right: A1 highlighted anatomical ROI, A1 model specific ESI solution, A1 ESI solution for A2 SEP data (mismatch). Finally, we aimed to show what would happen when EEG data is localized to another subject’s head model. As can be seen in Figure 7, bottom right corner, EEG data from subject A2 was localized in the individual head model of A1, using the same time point and activity as above. As in the previous mismatch, the bulk of electrical activity has shifted away from the ROI defined for A2, only this time the activity has shifted ventrally (more toward the functional location of subject A1’s thumb).

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DISCUSSION AND CONCLUSION The present study demonstrates the importance of accurate physical measurement of head geometry and conductivity for accurate electrical source localization of dense array EEG. Particularly for infants and young children, using rescaled adult electrical head models produces inaccurate results. On the other hand, if the geometry of the child’s head is approximated, such as through warping an older child’s model to the child’s head shape (Figure 4), the source results are a reasonable approximation to what can be gained from using the individual’s MRI and CT. Anatomical data for constructing electrical head models, based on MRI and CT images for a range of age, gender, and ethnicity groups are becoming more readily available [24- 26]. Using these data to create head model atlases with appropriate conductivity specifications is an important near term goal. Given appropriate conductivities, electrical head atlases can be constructed for a look-up repository across the developmental range (from infancy to old age) and across gender and racial groups. To adjust these atlases to a specific subject, a warping procedure to the subject’s own head shape (measured noninvasively such as with photogrammetry [36]) can be used and give reasonably accurate results, as suggested by the analyses above. One approach for gaining accurate head conductivity for each age, sex, and racial group is to use electrical impedance tomography (EIT) for head impedance scanning (impedance is the reciprocal of conductivity). In this approach, harmless currents are injected into the head, and the potential field (“impressed EEG”) created by volume conduction of this current through head tissues is measured [1, 14, 27, 28, 34, 35]. From the impressed EEG and the known position of the injected current on the scalp, properties of the head tissue can be inferred through Ohm’s law. Ideally, subject specific electrical models based on native MRIs and CTs structural information and informed with tissue conductivity specifications are the best choice for the most accurate ESI. However, MRIs and CTs are not usually available for many adult subjects and the majority of infants and young children. In such cases, as we have shown on example of pediatric models, one can use a reasonably close by age atlas model and warp it to the subject specific EEG sensor positions cloud (obtained noninvasively with photogrammetry). Adult models rescaled to the infant size are not a good choice due to the far distant morphology (which makes conductivity uncertainties’ impact amplified as well), producing as a result localization errors up to 3 cm. We have shown previously [28] that conductivity fitting to experimental impressed EEG is feasible. The actual conductivity values for infant skull are not well known presently, but unlikely to be in the adult range of low values. Therefore further studies are needed for practical noninvasive estimation of head impedance for regional tissue conductivity estimates in infants. In addition to EEG, there are several other applications for which accurate (preferably subject specific) models of head-shape, tissue boundaries and tissue properties are required. These range from biomechanical models of cranial injury to imaging techniques such as MEG and EIT [1,8,16,28]. With the addition of optical diffusion equations and tissue parameters to the FDM framework, the child head model database can be extended to diffuse optical tomography (DOT) and Near Infrared Spectroscopy (NIRS) [39]. Finally, accurate electrical head models are needed for more accurate interventions, such as with Transcranial Electrical Stimulation (TES) and Transcranial Magnetic Stimulation (TMS) in neurorehabilitation for stroke and TBI patients, treatment of depression and other neurological disorders [17]. Although the specific issues vary in each of these applications, an accurate database of electrical head models could allow neuroimaging and neurointerventional technologies to be extended more accurately to work with children.


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ACKNOWLEDGMENTS This project was supported by the National Institute of Neurological Disorders and Stroke (Grants 5R43NS067726-02 and 5R44NS056758-04).

REFERENCES [1]

[2] [3] [4] [5]

[6] [7]

[8]

[9]

[10]

[11]

[12]

[13] [14]

[15]

Salman A, Turovets S, Malony A., Poolman P, Davey C, Eriksen J, Tucker D. Noninvasive conductivity extraction for high-resolution EEG source localization. Adv. Clin. Neurosci Rehabil. 2006;6(1):27-28. Michel CM, Murray MM, Lantz G, Gonzalez S, Spinelli L, Grave de Peralta R. EEG source imaging. Clin. Neurophysiol. 2004;115(10): 2195-2222. Holmes MD. Dense array EEG: Methodology and new hypothesis on epilepsy syndromes. Epilepsia. 2008;49(s3):3-14. Srinivasan R, Tucker D, Murias M. Estimating the spatial Nyquist of the human EEG. Behav. Res Methods Instrum Comput. 1998;30:8–19. Lantz G, Grave de Peralta R, Spinelli L, Seeck M, Michel CM. Epileptic source localization with high density EEG: how many electrodes are needed? Clin. Neurophysiol. 2003;114(1):6369. Plummer C, Harvey AS, Cook M. EEG source localization in focal epilepsy: Where are we now? Epilepsia 2008;49(2):201-218. Hallez H, Vanrumste B, Grech R, Muscat J, De Clercq W, Vergult A, D'Asseler Y, Camilleri KP, Fabri SG, Van Huffel S, Lemahieu I. Review on solving the forward problem in EEG source analysis. J. Neuroeng Rehabil. 2007;4:46. Grech R, Cassar T, Muscat J, Camilleri KP, Fabri SG, Zervakis M, Xanthopoulos P, Sakkalis V, Vanrumste B. Review on solving the inverse problem in EEG source analysis. J. Neuroeng Rehabil. 2008;5:25. doi:10.1186/1743-0003-5-25. Knickmeyer RC, Gouttard S, Kang C, Evans D, Wilber K, Smith JK, Hamer RM, Lin W, Gerig G, Gilmore JH. A Structural MRI Study of Human Brain Development from Birth to 2 Years. J. Neurosci. 2008;28(47):12176-12182. Marsh R, Gerber AJ, Peterson BS. Neuroimaging Studies of Normal Brain Development and Their Relevance for Understanding Childhood Neuropsychiatric Disorders. J. Am. Acad Child Adolesc Psychiatry. 2008;47(11):1233-1251. doi:10.1097/CHI.0b013e318185e703. Hammock MK, Mihorat TH. Cranial computed tomography in infancy and childhood. Other Information: From review in Radiology. 145(1) (Oct 1982). 1981. Medium: X; Size: Pages: 350. Neumann K, Moegelin A, Temminghoff M, Radlanski RJ, Langford A, Unger M, Langer R, Bier J. 3D-computed tomography: a new method for the evaluation of fetal cranial morphology. J. Craniofac Genet Dev Biol. 1997;17(1):9-22. Margulies SS, Thibault KL. Infant Skull and Suture Properties: Measurements and Implications for Mechanisms of Pediatric Brain Injury. J. Biomech Eng. 2000;122(4):364-371. Lai Y, van Drongelen W, Ding L, Hecox KE, Towle VL, Frim DM, He B. Estimation of in vivo human brain-to-skull conductivity ratio from simultaneous extra- and intra-cranial electrical potential recordings. Clin. Neurophysiol. 2005;116(2):456-465. Lebel C, Walker L, Leemans A, Phillips L, Beaulieu C. Microstructural maturation of the human brain from childhood to adulthood. Neuroimage. 2008;40(3):1044-1055.

292


[16] van Uitert R, Weinstein D, Johnson C. Volume Currents in Forward and Inverse Magnetoencephalographic Simulations Using Realistic Head Models. Ann. Biomed Eng. 2003;31(1):21-31. [17] Wagner T, Valero-Cabre A, Pascual-Leone A. Noninvasive Human Brain Stimulation. Annu Rev Biomed Eng. 2007;9:19.1–19.39. doi: 10.1146/annurev.bioeng.9.061206.133100. [18] Awada KA, Jackson DR, Baumann SB, Williams JT, Wilton DR, Fink PW, Prasky BR. Effect of conductivity uncertainties and modeling errors on EEG source localization using a 2-D model. IEEE Trans Biomed Eng. 1998;45(9):1135-1145. [19] Vanrumste B, Van Hoey G, Van de Walle R, D'Havé M, Lemahieu I, Boon P. Dipole location errors in electroencephalogram source analysis due to volume conductor model errors. Med. Biol Eng Comput. 2000;38(5):528-534. [20] Pohlmeier R, Buchner H, Knoll G, Rienäcker A, Beckmann R, Pesch J. The influence of skullconductivity misspecification on inverse source localization in realistically shaped finite element head models. Brain Topogr. 1997;9(3):157-162. [21] Huiskamp G, Vroeijenstijn M, van Dijk R, Wieneke G, van Huffelen AC. The need for correct realistic geometry in the inverse EEG problem. IEEE Trans Biomed Eng. 1999;46(11):12811287. [22] Acar ZA, Makeig S. Effects of forward model errors on EEG source localization. Brain Topogr. 2013;26(3):378-396. [23] Roche-Labarbe N, Aarabi A, Kongolo G, Gondry-Jouet C, Dümpelmann M, Grebe R, Wallois F. High-resolution Electroencephalography and source localization in Neonates. Hum. Brain Mapp. 2008;29:167-176. [24] MNI pediatric and adult template head models. Available from: http://www.bic.mni.mcgill.ca/ ServicesAtlases/ [25] Fonov V, Evans AC, Botteron K, Almli CR, McKinstry RC, Collins DL; Brain Development Cooperative Group. Unbiased average age-appropriate atlases for pediatric studies. Neuroimage. 2011;54:313-327. [26] Shi F, Yap PT, Wu G, Jia H, Gilmore JH, Lin W, Shen D. Infant brain atlases from neonates to 1- and 2-year-olds. PLoS ONE. 2011;6(4);e18746. doi: 10.1371/journal.pone.0018746. [27] Salman A, Turovets S, Malony A, Volkov V. Multi-cluster, mix-mode computational modeling of human head conductivity. IWOMP 2005/2006. LNCS. 2008;4315:119-130. [28] Turovets S, Poolman P, Salman A, Malony A, Tucker D. Conductivity analysis for highresolution EEG. In: Proceedings of 2008 International Conference on Biomedical Engineering and Informatics. IEEE Computer Society. 2008;386-393. [29] Durston S, Casey BJ. What have we learned about cognitive development from neuroimaging? Neuropsychologia. 2006;44:2149-2157. [30] Luna B, Garver KE, Urban TA, Lazar NA, Sweeney JA. Maturation of cognitive processes from late childhood to adulthood. Child Dev. 2004;75(5):1357-1372. [31] Murias M, Swanson JM, Srinivasan R. Functional connectivity of frontal cortex in healthy and ADHD children reflected in EEG coherence. Cerebral Cortex. 2007;17:1788-1799. [32] Li K, Malony A, Tucker DM. Automatic brain MR image segmentation by relative thresholding and morphological image analysis in The First International Conference on Computer Vision Theory and Applications-VISAPP; 2006; Setubal, Portugal. [33] Li K. BrainK: Structural Image Processing for Electrical Models of the Human Head. Neuroinformatics. Forthcoming 2013. [34] Oostendorp TF, Delbeke J, Stegeman DF. The conductivity of the human skull: Results of in vivo and in vitro measurements. IEEE Trans Biomed Eng. 2000;47:1487–1493.


293

[35] Goncalves SI, de Munck JC, Verbunt JP, Bijma F, Heethaar RM, Lopes da Silva F. In vivo measurement of the brain and skull resistivities using an EIT-based method and realistic models for the head. IEEE Trans Biomed Eng. 2003;50(6):754-767. [36] Russell GS, Eriksen KJ, Poolman P, Luu P, Tucker DM. Geodesic photogrammetry for localizing sensor positions in dense-array EEG. Clin. Neurophysiol. 2005;116:1130–1140. [37] Smith K, Politte D, Reiker G, Nolan TS, Hildebolt C, Mattson C, Tucker D, Prior F, Turovets S, Larson-Prior LJ. Automated measurement of pediatric cranial bone thickness and density from clinical computed tomography. Conf Proc IEEE Eng Med Biol Soc. 2012;2012:4462-5. doi: 10.1109/EMBC.2012.6346957. [38] Walters C. Influence of tissue conductivity and anisotropy on EEG/MEG based source localization in the human brain. PhD Thesis, University of Leipzig, Germany; 2003. [39] Gibson AP, Hebden JC, Arridge SR. Recent advances in diffuse optical imaging. Phys Med Biol. 2005;50(4):R1-R43. [40] Malony AD, Salman A, Turovets S, Tucker D, Volkov V, Li K, Song JE, Biersdorff S, Davey C, Hoge C, Hammond D. Computational modeling of human head electromagnetics for source localization of milliscale brain dynamics. Stud. Health Technol Inform. 2011;163:329-35.

Received: June 17 2013 Revised: June 24 2013 Accepted: June 28 2013



A NOVEL ERP PATTERN ANALYSIS METHOD FOR REVEALING INVARIANT REFERENCE BRAIN NETWORK MODELS Amit Reches1, Dan Kerem1, Noga Gal1, Ilan Laufer1, Revital Shani-Hershkovitch1, Dalia Dickman1, and Amir B. Geva1,2 1

2

ElMindA Ltd., Herzliya, Israel Electrical and Computer Engineering, Ben Gurion University of the Negev, Beersheba, Israel

ABSTRACT Background: Objective and reliable neuro-electrophysiological methods for the longitudinal monitoring of a patient’s cognitive state are scarce. Since baseline neuro-electrophysiological measurements are generally not performed as standard practice, this type of longitudinal monitoring requires an invariant normal reference to which the individual brain activity may be scored, with sufficiently high within-subject repeatability. Methods: Group-common functionally connected Reference Brain Network Models (RBNMs) were extracted with the Brain Network Activation (BNA) Technology from multichannel ERPs of 120 young healthy subjects (Reference Group) who underwent the three-stimulus Auditory Oddball Task. The test-retest repeatability of an age-matched group of 116 subjects (Database Group), whose individual brain activity on the oddball task was scored on the RBNMs, was determined and the Standard Error of Measurement (SEM) computed as a measure of Minimal Important Clinical Difference. The general applicability was cross-validated on 36 healthy patients of a wider and marginally overlapping age-range (Validation Group). Results: Intraclass correlation values of scores on repeated tests in the Database Group ranged between 0.58-0.81. SEM values ranged from 14.1-17.9, on a score scale of 0-100. Scoring, repeatability and SEM applicability were all successfully validated on subjects from the Validation Group, yielding values that were similar to or higher than those of the Database Group. Conclusions: The BNA generated brain network models are largely invariant and repeatable and as such may be useful for diagnosis and follow-up of disease progression and treatment management. To further test the algorithm’s utility, additional research should be conducted on diseased populations.

Keywords: Functional networks; Brain Network Activation (BNA); ERP; Auditory oddball Task; Normative database; Repeatability; Personalized medicine



Correspondence: Dr. Amit Reches, ElMindA Haminhara 16 st., Herzliya, Israel 46586 Email: [email protected].

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Amit Reches, Dan Kerem, Noga Gal et al.

1. INTRODUCTION Following neurophysiological changes over time relative to a baseline or to a normal reference is important in individual patient management, for the monitoring of both disease progression and response to treatment. Today, managing of CNS pathology is mostly achieved through questionnaires and neuro-psychological tests, which often are subjective and qualitative. It has been proposed that quantitative analysis of EEG (qEEG) as well as components of evoked response potentials (ERPs) may be more informative, objective and appropriate clinical tools for longitudinal monitoring of neuro-cognitive diseases [1-3]. They also hold an advantage over other imaging methods in providing dynamical (at a millisecond timescale) parameters of brain function. In order to assess deviation from the norm, qEEG uses metrics such as frequency band spectral power ratios, coherence and other ERP features that are evaluated by statistical comparisons to normative databases. To capture the full representation of network dynamics, essential for the description of normal and pathological brain function [4], emphasis has been put on spatio-temporal relations reflecting functional connectivity between neuronal assemblages and networks, which underlie continuous EEG as well as ERPs. Such relationships, obtained through various imaging methods, are being promoted as additional potential candidates for detecting various CNS pathologies [5,6]. In this study, in accordance with the network dysfunction perspective, rather than the use of discrete parameters of brain activation, we propose using global parameters that describe network dynamics by utilizing a novel EEG network analysis method, reliant on the Brain Network Activation (BNA) algorithm. BNA is a newly developed ERP-based, network-oriented analysis that produces a spectro-spatiotemporal activity template of scalp potentials in subjects performing a neuro-cognitive task [7]. Unlike other EEG/ERP-based analytical methods, BNA does not evaluate the individual in terms of discrete values such as latency, amplitude, frequency power content, coherence or complexity. Rather, it quantifies/scores the overall resemblance of the individual’s electrical activity in response to a cognitive task to an invariant model response that serves as a reference characterizing the majority of the normal population: the Reference Brain Network Model (RBNM). To do so, BNA utilizes a graph as the formal representation of a group-common network in which the nodes represent time, location, frequency-band and amplitude of an electrical event and the edges representing the level of coordinated activity among nodes. Therefore, the individual neurophysiological measure (the BNA Score) is not based on a discrete observed value of EEG activity such as relative or absolute power, but is derived at the level of entire network dynamics. In addition to the isolation of task-based RBNMs, the BNA algorithm is also used to establish a normative database of individual quantitative scores that could aid in diagnosis as well as in patient treatment management. There are two main goals for using a normative EEG/ERP database: a) quantifying individual differences and between-subject variability in normative brain function and b) establishing a robust normative framework for clinical diagnosis. Such a diagnosis is obtained by comparing the individual participant’s EEG patterns to the patterns of a reference population of healthy individuals. This is done to identify atypical features and to evaluate the magnitudes of deviations [8]. In essence, there are three standards that a normative database must follow in order to be clinically utilized towards these goals. First and foremost, the database must be reliable [1]. Reliability may be approximated from the test-retest repeatability of a large enough group of healthy subjects, all attending two identical sessions of an ERP-generating task. From such a dataset one may also derive the Standard Error of Measurement (SEM) which could be used to construct confidence intervals for mean scores and to determine the Minimal Clinically Important Difference that is surpassed when a non-random change in the response has occurred. The second requirement a database must adhere to is the ability to account for between subject variability. This variance is often considered a problem in normative

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databases due to group heterogeneity [9]. Finally, the third standard requirement that a normative database has to meet is cross-validation [2]. Due to cost considerations, most cross-validations were computed using the leave-one-out, a statistically weaker form of cross validation. The current study introduces several innovations relative to previous studies that constructed normative databases based on EEG data. First, individuals comprising the normative database were compared and scored against RBNMs identified by the BNA algorithm. As described above, this approach permits a more holistic presentation of the network dynamics of both the normative database and the individual subject. Second, although the BNA Score could be used as a single measure and viewed as the dependent variable, in this study, the difference between BNA Scores from two repeated visits (ΔBNA Scores) was not merely used to quantify repeatability but was also used to generate a normative database. Using difference scores greatly reduces the between-subject variance discussed above. Obtaining data through repeated scoring of the same person against the RBNM over time could enable monitoring of disease progression and treatment efficacy. Third, as opposed to previous attempts to construct an EEG based normative database, in the current study we employed a completely independent population of healthy subjects to cross-validate the normative database. In line with the three innovations presented above, the general structure of the manuscript comprises the following three-tiered stages: A. RBNM Construction Stage: The extraction of task-specific RBNMs from a large group of young healthy subjects (Reference Group). The task chosen for this purpose is the auditory oddball task, a classic EEG paradigm that has been extensively used in neuro-cognitive studies and in many neurologically compromised patient populations [10]. B. RBNM Evaluation and Normative Database Assemblage Stage: For this stage another independent large group of healthy participants (Database Group), age-matched to the Reference Group was recruited. All participants underwent two sessions of the oddball task and were scored twice against the RBNMs. The resulting scores were used to construct both the BNA Score and the 2-visit ΔBNA Scores distributions of the normative database. They also served to evaluate the reliability (within-subject repeatability) of the BNA Scores. In addition, the SEM was determined from the ΔBNA scores and was used as a measure of the likelihood of a given test-retest score difference being due to natural daily variation. C. Validation Stage: validating the general applicability of the RBNMs and normative database, BNA score repeatability and SEM.

2. METHODS 2.1. Subjects Reference Group: 120 healthy female (N=38) and male high school and college students, with an age range of 14 to 25 years (mean=18.6, median=18.3, SD=2.7) from York University (York) and University of Pittsburg Medical Center (UPMC). Database Group: 116 healthy female (N=67) and male high school and college students with an age range of 14 to 24 years (mean=19.3, median=19.2, SD=2.7), from Clinilabs Clinical Research Organization, New York (Clinilabs), University of Michigan (UMICH) and Vince & Associates Clinical Research, Kansas, USA (V&A). Validation Group: 36 healthy male (N=18) and female volunteers, with an age range of 23 to 64 years (mean=36.6, median=33, SD=12.2), tested at the Lowenstein Hospital Ra’anana, Israel.

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All subjects were right-handed and reported to have normal hearing, normal or corrected-tonormal vision, no history of special education, of neurological or psychiatric disease or of severe head injuries and not to consume any CNS-affecting medications. The study protocols for the three groups were approved by the Ethics Committee Boards for experiments involving human subjects of the respective research centers. All participants signed an informed consent before joining the study.

2.2. Task and Procedure We utilized a sensory-gating version of the three-stimulus auditory oddball task in which three different types of auditory stimuli were pseudo-randomly presented, at an average rate of 1 each 1.5 sec, each lasting 120 ms, with a sound pressure level of 70 dB re 20 microPascals. A total of 80% of the stimuli ('standard'/'frequent') were pure tones of 2000 Hz. A total of 10% of the stimuli ('deviant/target') were pure tones of 1000 Hz. The remaining 10% of stimuli ('novel') were environmental sounds (e.g., telephone ring, dog bark), different for each stimulus presentation (Figure 1). Subjects heard the sounds binaurally, via earphones, and were instructed to press a button with their right index finger in response to 'target' stimuli only. The total number of stimuli in a session was 600, presented continuously in one ~16 min block. Only correct press/no press responses underwent ERPs analysis. Each session commenced with 10 practice trials (8 frequent and 2 target tones) in order to be familiarized with the experimental paradigm and the recording system. Reference Group subjects attended one visit, Database Group subjects attended two visits and the Validation Group attended three visits (henceforth: V1, V2 and V3), 7±3 days apart, at which time they performed the auditory oddball task. A subset (N=25) of the Database Group subjects repeated the task 6 weeks after attending V1.

Figure 1. Auditory Oddball Paradigm. Frequencies of occurrence for Frequent, Target and Novel stimuli were 80%, 10% and 10%, respectively.

2.3. Electrophysiological Data Acquisition EEG of members of all groups was recorded with 64 Ag-AgCl active electrodes positioned according to the 10-20 international system. In the Reference and Database groups, HydroCel Geodesic Sensor Net of 256-channels (UMICH) and 128-channels (all other centers) net amps 300 amplifier of EGI (Eugene, Oregon) were used. In the Validation Group, A Biosemi Active Two EEG system (BioSemi Inc., Amsterdam, Netherlands) was used. Four electrodes, above and below the right


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eye, and on the outer canthus of each eye served to record eye movements via the electrooculogram. Subjects were instructed to avoid eye movements, blinking and body movements as much as possible, and to fix their gaze on some point in front of them during task performance. Epochs with the time range from -200ms to 1200ms (zero being stimulus onset), sampled at a rate of 256 Hz, were bandpassed filtered (0.1-100 Hz) and stored for off-line analysis.

2.4. General Principles of the BNA Algorithm BNA is based on identifying patterns of phase-locked evoked activity and it relates network dynamics to several network parameters. Specifically, the BNA algorithm exploits the interparticipant sequential temporal co-occurrence of pairs of ERP peaks (event-pairs) extracted from signals that were band-pass filtered into different frequency ranges and that emerged in different spatial locations. Thus, BNA captures the dynamic integration of group-common event-pairs of specific temporal relations, spatial locations frequencies and amplitudes into a unified functional network. As mentioned above, the information regarding the temporal co-occurring event-pairs, which form into patterns, is extracted from the group. That is, only if a specific sequential activation pattern of co-occurring ERP peaks is common across participants included in the group, it will be considered as the characteristic group’s network. Therefore, the coordinated activity in time, location and frequency depicted in the BNA group’s network implies that the spatiotemporal functional dependencies of regional neuronal activities in different frequency bands represent functional links common to and characteristic of a specific population (e.g., healthy controls, Alzheimer disease patients). Individual brain activation patterns may then be compared against the group’s network to determine the degree of similarity between the two in terms of network dynamics. The degree of similarity is measured by the BNA Score as detailed in “Single participant level process and the BNA Score” below. The BNA method allows an encompassing description of brain activation using a graph as the formal representation of a network in which the nodes represent events defined in time, location and frequency-band and amplitude, and the edges represent consistent temporal association among nodes. This is a suitable and convenient formal representation of the sequence of time-dependent activations that occur in different frequency-bands and scalp-locations. This formal representation allows a comparison between entire networks representing different groups or conditions as well as the comparison of the single participant to a group by comparing between different multidimensional graphs. This approach is in accordance with the view that cognition results from dynamic interactions of distributed brain areas operating in large-scale networks [11].

2.5. Detailed Description of the BNA Algorithm: Two Main Processes The essence of BNA analysis is the extraction of spectro-spatio-temporal brain activation patterns common to a group of subjects, to which the brain activation of individual subjects may be compared (Figure 2A-H). Accordingly, the analysis involves two independent three-staged processes, a group level pattern recognition process (blue arrows in Figure 2) and a single subject level similarity evaluation process (red arrows in Figure2). At the group level, group-common activation patterns/templates are extracted from the ERP records of N members of a group of subjects, all of whom have undergone the same cognitive task. In the single subject level process, ERP data from a single subject external to the group, who underwent the same task, is evaluated against a reference database of extracted group templates. The subject is then assigned a set of ‘BNA Scores’, reflecting

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the degree of congruity between their pattern of activation and that of the group's. The two processes will now be described in more detail.

Figure 2. Outline of steps in the BNA functional network analysis. The BNA analysis involves two independent processes – group pattern analysis (blue arrows) and individual participant evaluation (red arrows). For the group analysis, the raw EEG of each participant undergoes three separate processing stages: (1) preprocessing (artifact removal, band-passing); (2) salient event extraction (discretization, normalization) and (3) network analysis (unitary events extraction, pair-pattern extraction) on all salient events gathered from all of the participants. The single participant level process involves three stages – the first two are identical to the first two stages of the group level process. In the third stage, the single participant activity is compared to the set of patterns collected during the group analysis stage. See text for further details. The multiple arrows stemming from the normalization stage represent the pooling of each participant’s salient events to form the database on which the pattern analysis stage was performed (Modified from Figure 1 in Shahaf et al., 2012).

2.5.1. Group Analysis Process The first stage in the group’s pattern recognition process involves data preprocessing (Fig. 2A-C). At this stage individual single trial epochs, beginning 200 ms before and ending 1200 ms after


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stimulus onset, are sorted according to stimulus type. Only epochs corresponding to correct motor responses and free of excessive electrical activity (>100µV) are included in the analysis. Chosen single trial records for each of the three stimuli (Frequent, Target, Novel) undergo band-pass filtering (0.5-30 Hz) and artifact rejection. Next, the data for each electrode undergoes band-passing to conventional frequency bands, with partial overlap to reduce loss of information: delta band (0.5-4 Hz), theta band (3-8 Hz), alpha band (7-13 Hz) and beta band (12-30 Hz). Single trial data at each location are then averaged within each separate frequency band. The end result of this stage are 64 (electrodes) x 4 (frequency bands) = 256 averaged traces per subject. In the second stage, salient event extraction is performed (Figure 2D, E). At this stage, each of the individual's averaged traces is reduced into a set of discrete events designating all maxima and minima of the signal. Due to the near-symmetry of the waveforms, each activity peak may be defined by a pair of numbers denoting its timing (latency) and its amplitude (Figure 2D). The major ERP components (e.g., N100, P200, N200 and P300) will be included among other peaks and troughs in their respective frequency bands. Following discretization, in order to allow for differing conductivities of different electrodes, the amplitudes of the positive and negative activity peaks in each trace are normalized (z-scored) (Figure 2E). For each participant, all peaks that surpassed a specific threshold are selected for further analysis as follows. Initially, the average frequency band is calculated based on the high and low boundaries of the given frequency band. Next, the percentage threshold, which is the inverse of the average frequency, is computed per frequency band. Finally, the number of peaks selected for analysis is determined by the percentage threshold of the highest normalized peaks (see Appendix A1, “Normalization procedure”). This procedure ensures that signals are adequately represented across frequency bands. The selected peaks are considered salient events, each with a defined latency, amplitude, frequency band and location on the scalp (Figure 2D, E). Following the salient-event extraction stage described above, in the third stage, network analysis is performed (Figure 2F, G). In this stage, all salient events of the entire group are projected as points in a four dimensional space of timing, frequency, scalp location (i.e., electrode) and amplitude. It becomes immediately apparent that the point cloud is not homogenous but rather contains collections of tightly spaced points, implying residence within narrow limits in one or more dimensions (Figure 2F, with amplitude omitted due to graphical limitations). The BNA algorithm then performs continuous group clustering in the temporal dimension at each discrete combination of frequencyband and scalp location, in quest of salient-events clusters. Salient-events clusters ensemble a group of salient-events with the same scalp location and frequency-band and within a constrained temporal window, as detailed in Appendix A2 – “The clustering procedure”. 2.5.2. Single Subject-Level Process The single subject level process also involves three stages of which the first two (preprocessing and salient event extraction) are identical to the first two stages of the group level process (Figure 2AE). In the third stage (Figure 2H) the electrode activity of the single subject is compared to that of the group and is scored according to the degree of similarity between the two (further details in Appendix A3 – “Single-subject BNA similarity score computation”). The BNA Score is a measure of the level of similarity of the single participant’s activation to that of the group’s in terms of the stimulusevoked consistent activity in location, time and frequency, in the context of goal directed behavior. More specifically, the BNA Score is the measure of the 'functional similarity' between the activation pattern of a single participant and the group’s network in terms of the sequence of the temporal cooccurrence of event-pairs. The timing parameters that define co-occurrence are associated with event pairs of specific spatial locations, frequencies and amplitudes. The BNA algorithm produces a similarity score of the individual to the reference brain network. This score reflects the percentage of similarity to a healthy reference brain activation using all four BNA score parameters: time, location, frequency and amplitude.

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The scoring process yields four BNA Score types per subject, ranging between 0-100 percent, which are generated separately for each of the three response-evoking stimuli in the three-stimulus auditory oddball task:    

Amplitude BNA Score – a measure of the similarity of the amplitudes of the events; Absolute Time BNA Score – a measure of the similarity of the latencies of the events; Relative Time BNA Score– a measure of the similarity of latency differences between the two events in the event pairs; Overall BNA Score – the global average of the former three scores.

For the exact calculation of the 4 BNA Scores see Appendix A3.

2.6. Statistical Methods 2.6.1. Poolability of Datasets from Different Research Centers ANOVA was performed to assess poolability with ‘center’ as the independent variable (model: BNA Score/ΔBNA Score=center). 2.6.2. Test-Retest Repeatability For each subject at each session, the 4 BNA scores and the ΔBNA scores between the two sessions were computed. In order to assess the repeatability of two BNA scores obtained in two different task sessions, intra-class correlation (ICC) analysis was performed [12]. ICC was calculated using the two-way random intra-class model, for each of the three stimulus types (Frequent, Target, Novel) and for the four BNA Scores (Amplitude, Absolute Time, Relative Time, Overall) yielding 12 repeatability estimates. In the case of the Validation Group, three-score ICC testing (V1, V2 and V3) was performed. Bland-Altman Plots [13], in which the difference between each subject's two measurements is plotted against their average values, were constructed for each pair of repeated BNA scores. The plots point to outliers as regards repeatability, usually defined as values that lie outside the limits of agreement, being ±1.96 SD around of the mean difference line. Also, one may infer from the plot whether or not repeatability is dependent on the magnitude of the measurement value (BNA scores in this case) and whether or not there is a bias/trend of one measurement giving consistently higher results, e.g., in case of a possible training effect. 2.6.3. Estimating Normal within-Subject Variability of ΔBNA Scores Kolmogorov-Smirnov normality tests and QQ-plots were used to assess the normal distribution of the 12 test-retest ΔBNA Scores. Given a normal distribution, the Standard Error of Measurement (SEM) is employed to estimate the within-subject repeated measure variability. Specifically for the case in question, SEM was defined as the standard deviation of the BNA Score that would have been obtained from a single subject exposed to multiple identical task sessions with consecutive BNA analysis and scoring. The following model was fitted to estimate SEM from the data, for each of the 12 BNA Scores: BNA Score = Intercept + subject The Mean Square Error (MSE) of the above model estimates the pooled within-subject variance, with SEM estimated as the square root of the MSE. SEM may be interpreted in terms of the Minimal Important Clinical Difference (MICD) which refers to the smallest difference across two scores considered to be important in that it indicates a true


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change in subject performance; i.e., a change that is unlikely to occur due solely to random variation in subject scores over time. MICD is determined using a distribution-based approach following [14] and uses SEM. This approach assumes that when no change occurs, the distribution of relevant variable is normal with mean = 0 and standard deviation = SEM. Thus, for example, given the characteristics of the normal distribution, we expect about 67% of ΔBNA Scores to reside within ± 1SEM around 0. Alternatively, any ΔBNA Score >1SEM has a 67% likelihood of being the result of a true change rather than the expected, random variation. 2.6.4. Stability over Time of the SEM A subset of subjects (N=25) from the UMICH dataset underwent an additional task session, 6 weeks after V1. ANOVA with random subject effect was performed to assess whether differences between ΔBNA Scores from repeated visits, 1 and 6 weeks apart, were significant.

3. RESULTS 3.1. RBNM Construction Stage (Reference Group) 3.1.1. Group RBNMs As a first step, reference brain network models (RBNMs) were extracted for each of the threestimuli of the auditory oddball task. These patterns formed the basis for the BNA scores that will be addressed in all following sections.

Figure 3. Reference group RBNMs. Shade of the grey line that connects two nodes forming an event pair is proportional to the corresponding pair’s preponderance as quantified by the weight index (see Appendix A3).

Figure 3 depicts the chosen group activity patterns, namely, the RBNMs. These patterns are composed of interconnected individual nodes (colored circles), each representing a unitary event. Each unitary event in the pattern is connected (grey lines) to at least one other participating event, as part of an event pair, triplet, etc. All connected (co-occurring) nodes that were active throughout the

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entire epoch are superimposed in a single image. The shade of the connecting lines is proportional to the weight index of the corresponding event pairs (see Appendix A3). Observing Figure 3, it may be seen that the ‘Target’ RBNM has an alpha frequency (yellow coded) fronto-central presentation, mainly issuing from the early ERP components (from 100 ms to about 200 ms). The ‘Frequent’ RBNM shows theta frequency (green coded) central presentation, also related to the ~ 100-200 ms latency interval, while centrally presented delta frequency (red coded), mainly emanating from the P3 peak (~ 300 ms), dominates the Novel RBNM.

3.2. RBNM Evaluation and ND Assemblage Stage (Database Group) We now describe the next stage in which subjects age-matched to the Reference Group and forming the Database Group are scored to the above RBNMs on two different visits. Scores and score differences are assessed in order to evaluate the performance of the RBNMs in a normal population, in terms of between-subject variability and within-subject variability (repeatability). 3.2.1. BNA Scores on RBNMs The distributions of the 4 BNA Scores on a given visit for the Novel stimulus were rather even, with similar representation of low, moderate and high scores. For the Target stimulus, the distributions were quasi-normal, with the mean at 50 points (Figure 4A). For the Frequent stimulus, distributions were as variant but markedly skewed, with roughly 2/3 of the subjects scoring higher than 60 (Figure 4B).

Figure 4. Histograms of Database Group scores on the RBNMs – two visits pooled. A – Stimulus = Target; BNA Score = Overall; B – Stimulus = Frequent; BNA Score = Absolute Time.

Means of the 12 BNA Scores (averages of two visits) ranged between 45.8 and 69.0, with ‘Frequent’ scores being significantly higher than ‘Novel’ and ‘Target’ scores (Friedman’s two-way analysis of variance by ranks, adjusted p value of pair-wise comparisons = 0.001). 3.2.2. Intraclass Correlation (ICC) of BNA Scores Table I lists V1-V2 ICC values for the four BNA Scores, for each of the three stimuli.

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ERP Pattern Analysis Reveals Invariant Networks Table I. ICCs of BNA Scores obtained at two visits of the Database Group Stimulus Target

Novel

Frequent

Average

Parameter Amplitude Absolute Time Relative Time Overall Amplitude Absolute Time Relative Time Overall Amplitude Absolute Time Relative Time Overall

ICC value 0.66 0.70 0.58 0.69 0.81 0.74 0.72 0.80 0.67 0.71 0.75 0.73 0.713

P-Value 1000 IU/mL (reference < 35). The patient underwent a one-month course of oscillatory phase reset therapy consisting of syncopated, pulsed auditory signals delivered through headphones. Therapy sessions were of one-minute duration twice a day for 3 days, followed by five minutes twice daily for the rest of the month. Results: Daily headaches, tachycardia, pounding heart, and heavy breathing were completely resolved with three days, and patient was able to consistently sleep through the night for the first time in two years. At one month patient was able to organize and present professional talks for the first time in two years. Conclusion: Oscillatory phase reset therapy improved autonomic nervous system function and reduced hyperthyroid tachycardia. Positive outcomes in this case encourage further study of this strategy as rehabilitation of autonomic dysregulation. Disclosure: The oscillatory phase reset therapy used in this study is a patent-pending process developed and owned by the author.

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Poster Abstracts

NORMALIZED QUANTITATIVE EEG FOLLOWING OSCILLATORY PHASE RESET THERAPY James Otis1 1

Private Practice, Oakland, CA USA Email: [email protected] Received: June 3 2013, Revised: June 10 2013 Accepted: June15 2013 Background: A 62-year-old female experienced poor name recall and problems with spatial orientation, progressively worse over a five-year period. Methods: A Quantitative EEG brain map was performed immediately before and immediately after a single five-minute session of oscillatory phase reset therapy consisting of syncopated, pulsed auditory signals delivered through headphones. EEG was recorded from 20 locations around the skull, digitally converted, analyzed, and compared with normed references using New Mind software. The dimensions of analysis included magnitude, dominant frequency, inter-hemispheric connectivity, and inter-hemispheric asymmetry. Results: Patient reported feeling relaxed. New Mind QEEG analysis reported 29% aggregate improvement between before and after eyes-open analysis, and 17% improvement between before and after eyes-closed analysis. Conclusion: Oscillatory phase reset therapy elicits positive changes in neurological function demonstrated by electroencephalographic analysis. Positive results in this case encourage further study of this strategy as a method of functional neurological rehabilitation.

IMPROVEMENT OF CERVICAL DYSTONIA FOLLOWING FUNCTIONAL NEUROLOGICAL INTERVENTION

Thomas van den Hof1 1

Private Practice, Harderwijk, The Netherlands Email: [email protected] Received: June 11 Revised: June 15 2013 Accepted: June 19 2013 Background and aims: Standard care for cervical dystonia generally involves periodical botox injection with or without a physical conditioning program. Pathophysiology points to the basal ganglia, vestibular system and cerebellum. Cervical dystonia tends to be present unilaterally suggesting unilateral neurological dysfunction of these structures. Hemisphere specific treatment might prove to be of benefit when stimuli can be targeted to the correct areas. A 39-year-old Caucasian female suffering from right sided cervical dystonia since 2001 (12 years) presented to our clinic. To relieve her complaints she had a botox injection every 9 weeks. Methods: On initial consultation she reported cervical dystonia on the right side leading to pain in the suboccipital area and headaches. Second, she reported the sensation of her left eye moving. Functional neurological evaluation revealed cerebellar dysfunctions consisting of head titubations, impaired motor control, poor ocular motor control particularly to pursuit and saccadic stimuli. Treatment included: breathing exercises, nutritional advice, ocular motor exercises for the left hemisphere. Results: After 1 week of intense functional neurological care (5 times per day for 15-30 minutes each time) the dystonia was drastically reduced. Neck pain and headache decreased. On a follow up visit two months later she was still stable and skipped her botox treatment. Conclusion: A functional neurological approach in which the specific cerebral and cerebellar functional lesions are addressed can be successful in improving and resolving cervical dystonia in a very short period of time in particular patients.

Poster Abstracts

VERTIGO IMPROVED THROUGH APPLICATION OF A VESTIBULAR REHABILITATION PROGRAM IN CONJUNCTION WITH BRAIN-BASED THERAPIES Frederick R. Carrick,1 David J. Traster,2 Susan Esposito,2 Jerome D. Lubbe,2 and Matthew Antonucci2 1

Carrick Institute of Graduate Studies, Cape Canaveral, Florida 32920 USA 2 Life University, Marietta, GA USA E-mail: [email protected] Received: June 2 2013 Revised: June 10 2013 Accepted: June 15 2013

Background: We describe a male in his 60’s who presented to a functional neurology clinic with a 3 year history of vertigo. Episodes of three to eight hour durations would produce dizziness, disorientation, tinnitus, as well as memory and cognitive difficulties. Methods: A centrally maintained vertigo was confirmed through neurological examination. The patient was found to have a 10 Hz tremor on the right arm with decrease right arm swing during gait. Aberrant gaze holding, pursuits, saccades and optokinetic responses were observed and confirmed by videonystagmography. Bilateral, mydriatic pupils with arcus senilis were noted. The patient participated in a one week vestibular rehabilitation program that included multi-axis labyrinthine and otilithic stimulation, specific brain-based eye movement strategies, times-one viewing gaze stabilization exercises, extra-spinal manipulations and gait rehabilitation. Results: The combination of treatment protocols produced profound changes in the patient’s state of being. Patient reported that this intervention eliminated the dizziness and unsteadiness for the first time since its onset. Conclusion: This case of vertigo showed significant improvements after administration of a functional neurologic treatment regimen as described. The authors suggest further investigation into vestibular rehabilitation mechanisms and brain-based approaches to patient treatments with vertigo.

ATAXIA IMPROVED THROUGH APPLICATION OF OFF VERTICAL AXIS VESTIBULAR REHABILITATION AND BRAIN-BASED THERAPIES Frederick R. Carrick,1 David J. Traster,2 Susan Esposito,2 Jerome D. Lubbe,2 Diana Stephens2 1


Background: We describe a 20-year-old male who presented to a functional neurology clinic with a twelve year history of progressive ataxia. Symptoms include poor balance and coordination, poor gross and fine motor skills, stiffness, fatigue and inability to walk without assistance. Methods: Ataxia was confirmed by neurologic examination. Aberrant saccades, pursuits, and optokinetic responses were noted. Square wave jerks were present on left gaze fixation. A right beating nystagmus was present on right gaze fixation. Decreased joint position sense and sensation to pinwheel was present in the lower extremity bilaterally. Patellar myotatic stretch reflexes were plus three bilaterally. The patient participated in an in house functional neurological

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Poster Abstracts program that included off vertical axis vestibular rehabilitation, passive multi-planar movements of proximal joints, specific eye movement exercises, times-one viewing gaze stabilization exercises, cross-crawl exercises and gait rehabilitation. Results: The combination of treatment protocols produced profound changes in the patient’s state of being. Symptoms associated with the ataxia were dramatically reduced and the patient has been able to walk without assistance as a result of this intervention. Conclusion: This case showed significant improvements after administration of the functional neurologic treatment regimen described. The authors suggest further investigation into vestibular rehabilitation mechanisms and brain-based approaches to patient treatments with ataxic syndromes.

TEENAGE FEMALE WITH MILD TRAUMATIC BRAIN INJURY TREATED THROUGH APPLICATION OF A VESTIBULAR REHABILITATION PROGRAM IN CONJUNCTION WITH BRAIN-BASED THERAPIES Frederick R. Carrick,1 David J. Traster,2 Susan Esposito,2 Jerome D. Lubbe,2 and James L. Duffy2 1


Background: We describe a 17-year-old female who presented to a functional neurology clinic with a history of concussions. She complained of headaches, neck pain, sensitivity to light, blurring of vision, dizziness, fatigue, trouble concentrating, balance and spatial awareness problems, sleeping problems, enuresis, depression and anxiety. Methods: A diagnosis of a centrally maintained vestibulopathy secondary to a mild traumatic brain injury was confirmed by neurologic examination. Light stimulation produced akesthesia and created a dynamic right correctasia. Decreased myotatic stretch reflexes were observed on the left side of the body. Percussion myotonia was produced bilaterally upon striking of the thenar eminence. The patient participated in a functional neurological program that included off vertical axis vestibular rehabilitation, times-one viewing gaze stabilization exercises, passive multi-planar proximal extremity movements, specific eye movement exercises and gait rehabilitation. Results: The combination of treatment protocols produced a profound change in the patient’s state of being. All signs and symptoms significantly reduced over a short period of time and the patient was able to return to school. Conclusion: This case showed significant improvements as a result of the functional neurologic treatment regimen as described. The authors suggest further investigation into the mechanisms of the vestibular rehabilitation and these brain-based approaches to patient treatments with mild traumatic brain injuries.

Poster Abstracts

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TEENAGE MALE WITH MILD TRAUMATIC BRAIN INJURY IMPROVED THROUGH APPLICATION OF OFF VERTICAL AXIS VESTIBULAR REHABILITATION WITH BRAIN-BASED THERAPIES Frederick R. Carrick,1 David J. Traster,2 Susan Esposito,2 Jerome D. Lubbe,2 and Jacob Shores2 1


Background: We describe a 17-year-old male who presented to a functional neurology clinic with a five year history of concussions. Symptoms included headaches, light and sound sensitivity, fogginess, lightheadedness, trouble concentrating and reading, memory difficulties, fatigue, nausea and decreased appetite associated with weight loss. Methods: A centrally maintained vestibulopathy secondary to a mild traumatic brain injury was confirmed by examination. A downbeat nystagmus was observed when visual fixation was eliminated. Comprehensive Assessment of Postural Systems (CAPS) testing during perturbed surface, eyes closed, head in neutral parameters, revealed a 59.3% stability score. The patient participated in a vestibular rehabilitation program that included off vertical axis vestibular rehabilitation, specific eye movement exercises, times-one viewing gaze stabilization exercises, somatosensory evoked potential activation of the left brainstem, breathing exercises and passive, multi-planar movements of right proximal extremities. Results: The combination of treatment protocols produced profound changes to all signs and symptoms associated with the mild traumatic brain injury. Follow up CAPS results during perturbed surface, eyes closed, head in neutral parameters, revealed a 74.9% stability score and a return to exercise was achieved. Conclusion: This case showed significant improvements after administration of a functional neurologic treatment regimen as described. The authors suggest further investigation into vestibular rehabilitation mechanisms and brain-based approaches to patient treatments with mild traumatic brain injuries.

TEENAGE FEMALE WITH MILD TRAUMATIC BRAIN INJURY IMPROVED THROUGH APPLICATION OF FUNCTIONAL NEUROLOGICAL THERAPIES Frederick R. Carrick,1 David J. Traster,2 Susan Esposito,2 Jerome D. Lubbe,2 and Jacob Shores2 1


Background: We describe a 17-year-old female who presented to a functional neurology clinic with a history of concussions. Symptoms include dizziness, lightheadedness, poor balance, headaches, light sensitivity, memory problems, fatigue and nausea. Methods: A centrally maintained vestibulopathy secondary to a mild traumatic brain injury was confirmed by examination. Upbeat nystagmus was present when visual fixation was removed. Aberrant saccades and optokinetic responses were observed and confirmed by

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Poster Abstracts videonystagmography. During convergence, an accommodation spasm with retropulsion was noted. A scissor gait was observed with decreased left arm swing which was further degraded during dual tasking. The patient participated in a vestibular rehabilitation program that included off vertical axis vestibular rehabilitation, specific brain-based eye movement strategies, times-one viewing gaze stabilization exercises, and gait rehabilitation. Results: The combination of treatment protocols produced profound changes in the patient’s state of being. All signs and symptoms associated with the mild traumatic brain injury were dramatically reduced and she was able to return to her normal daily activities as a result of this treatment. Conclusion: This case of a mild traumatic brain injury showed significant improvements after administration of a functional neurologic treatment regimen as described. The authors suggest further investigation into vestibular rehabilitation mechanisms and brain-based approaches to patient treatment with mild traumatic brain injuries.

MULTIPLE TRAUMATIC BRAIN INJURIES TREATED THROUGH FUNCTIONAL NEUROLOGICAL APPLICATIONS Frederick R. Carrick,1 David J. Traster,2 Susan Esposito,2 Jerome D. Lubbe,2 and Matthew Antonucci2 1


Background: We describe a 27-year-old female who presented to a functional neurology clinic with a seven year history of concussions. She complained of headaches, fatigue, memory and concentration problems, nausea, depression and speech difficulties. Methods: A diagnosis of a centrally maintained vestibulopathy secondary to a mild traumatic brain injury was confirmed by examination. Aberrant gaze fixation, saccades and pursuits were observed and confirmed by videonystagmography. A negative center of pressure with a rightward bias was recorded upon a Comprehensive Assessment of Postural Systems (CAPS) unit. The patient participated in a vestibular rehabilitation program that included off vertical axis vestibular rehabilitation, somatosensory evoked potential stimulation of the right brainstem, times-one viewing gaze stabilization exercises, specific brain-based eye movement therapies and application of low-level laser over the suboccipital musculature. Results: The combination of treatment applications produced a profound reduction in all signs and symptoms. Conclusion: This case of a mild traumatic brain injury showed significant improvements as a result of the functional neurologic treatment regimen as described. The authors suggest further investigation into the mechanisms of the vestibular rehabilitation and these brainbased approaches to patient treatment with mild traumatic brain injuries.

Poster Abstracts

379

IMPROVEMENTS ATTAINED IN MILD TRAUMATIC BRAIN INJURY THROUGH VESTIBULAR REHABILITATION AND BRAIN-BASED THERAPIES Frederick R. Carrick,1 David J. Traster,2 Susan Esposito,2 Jerome D. Lubbe,2 and Derek A. Barton2 1


Background: We describe a male in his 20’s who presented to a functional neurology clinic with a history of multiple concussions resulting in bilateral headaches, visual disturbances, dizziness and fatigue. Methods: A diagnosis of a centrally maintained vestibulopathy secondary to a mild traumatic brain injury was confirmed by examination. Saccadic intrusions were observed within all pursuits. Horizontal saccades were slow with glissades. Optokinetic responses were aberrant and there was an asymmetrical accommodation response. A left beating nystagmus was revealed when fixation was eliminated. Comprehensive Assessment of Postural Systems (CAPS) testing during perturbed surface, eyes closed, head in extension parameters, revealed a 15.5% stability score. The patient participated in a one week, in house, vestibular rehabilitation program that included off vertical axis vestibular rehabilitation, times-one viewing gaze stabilization exercises, somatosensory evoked potential stimulation of the left brainstem, brain-based eye movement strategies and spinal manipulations. Results: The combination of treatment protocols allowed the patient to return to his work place symptom free. Follow up CAPS results during perturbed surface, eyes closed, head in extension parameters, revealed a 53.6 stability score. Conclusion: This case showed significant improvements as a result of the functional neurologic treatment regimen described. The authors suggest further investigation into vestibular rehabilitation and brain-based therapies to patient treatments with mild traumatic brain injuries.

MILD TRAUMATIC BRAIN INJURY IMPROVED THROUGH A FUNCTIONAL NEUROLOGIC APPROACH OF OFF VERTICAL AXIS VESTIBULAR REHABILITATION AND BRAIN-BASED APPLICATIONS Frederick R. Carrick,1 David J. Traster,2 Susan Esposito,2 Jerome D. Lubbe,2 and James L. Duffy2 1


Background: We describe a female in her 20’s who presented to a functional neurology clinic with a history multiple concussions resulting in headaches, fatigue, brain fog, nausea, dizziness, and disorientation. Methods: A diagnosis of a centrally maintained vestibulopathy secondary to a mild traumatic brain injury was confirmed by examination. Examination revealed a tremor of the right hand and left hemi-facial spasm. Saccadic velocity was decreased in all directions. While performing ten rapid movements of the index finger to thumb, the left hand’s velocity was slow. The patient

380

Poster Abstracts participated in a one week vestibular rehabilitation program that included off vertical axis vestibular rehabilitation, times-one viewing gaze stabilization exercises, somatosensory evoked potential stimulation of the left brainstem and specific eye movement strategies. Results: The combination of treatment protocols drastically reduced all signs and symptoms over a short period of time and the patient was able to re-enter her workplace as a result of this intervention. Conclusion: Significant improvements as a result of a functional neurologic treatment regimen were produced. The authors suggest further investigation into vestibular rehabilitation and brain-based approaches to patient treatments with mild traumatic brain injuries.

MILD TRAUMATIC BRAIN INJURY TREATED THROUGH APPLICATION OF A VESTIBULAR REHABILITATION PROGRAM IN CONJUNCTION WITH BRAINBASED THERAPIES Frederick R. Carrick,1 David J. Traster,2 Susan Esposito,2 Jerome D. Lubbe,2 and Jacob Shores2 1


Background: We describe the case of a male in his mid 20’s who presented to a functional neurology clinic with a history of multiple concussions resulting in headaches, loss of consciousness and speech difficulties. Methods: A diagnosis of a centrally maintained vestibulopathy secondary to a mild traumatic brain injury was confirmed by examination. Oculomotor examination revealed mitotic pupils bilaterally, hypometric saccades, saccadic pursuits, and absent optokinetic responses. Bilateral complexus myospasm and left sided hypotonia was noted. Three hesitations were present when performing ten rapid movements of the right index finger to thumb. The patient participated in a one week, in house, vestibular rehabilitation program that included off-vertical-axis vestibular rehabilitation paired with specific eye movement strategies. Results: The combination of treatment protocols produced a significant reduction of all signs and symptoms over a short period of time. Previously absent optokinetic responses were completely restored, and the patient was able to return to work, symptom free, as a result of this intervention. Conclusion: This case showed significant improvements as a result of a functional neurologic treatment regimen as described. The authors suggest further investigation into the mechanisms of the vestibular rehabilitation and brain-based approaches to patient treatments with mild traumatic brain injuries.

Poster Abstracts

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ANISMUS TREATED THROUGH APPLICATION OF A VESTIBULAR REHABILITATION PROGRAM IN CONJUNCTION WITH BRAIN-BASED THERAPIES Frederick R. Carrick,1 David J. Traster,2 Susan Esposito,2 Jerome D. Lubbe,2 and Jacob Shores2 1


Background: We describe a male in his 60’s who presented to a functional neurology clinic with a 4 year history of severe, progressing anal pain with associated pain in the left ear and jaw. The patient reported a year before the anal pain there was bilateral numbness on the bottom of both feet which never improved. Patient also reports regular bouts of constipation which last four to five days. Hemorrhoidectomy, disimpaction, ganglion impar block, lidocaine trigger point injection, pudendal block and superior hypogastric block has been performed with no impact on anal pain. All imaging was unremarkable. Methods: A diagnosis of anismus was confirmed by neurologic examination. Aberrant pursuits, saccades and optokinetic responses were observed along and confirmed by videonystagmography. Blepheroclonus was present during gaze stabilization. The patient participated in a functional neurological program that included somatosensory evoked potential stimulation of the right brainstem, specific brain-based eye movement strategies, along with application of low-level laser over the anus. Results: The combination of treatment protocols produced up to 40% decrease of symptoms, as reported by the patient, which was beyond any previous treatment application. Conclusion: This case of anismus showed improvements beyond traditional applications after administration of a functional neurologic treatment regimen as described. The authors suggest further investigation into the mechanisms of these brain-based approaches to patient treatment with anismus.

YOUNG BOY WITH COMPLEX REGIONAL PAIN SYNDROME TREATED THROUGH APPLICATION OF A FUNCTIONAL NEUROLOGICAL PROGRAM Frederick R. Carrick,1 David J. Traster,2 Susan Esposito,2 Jerome D. Lubbe,2 and Jacob Shores2 1


Background: We describe a 12-year-old male who presented to a functional neurology clinic with severe pain and an inability to tolerate light touch. A three year history of severe, progressing headaches, and head pain which had progressed down his back and shoulders was reported. The patient also presented with fatigue, light sensitivity and decreased appetite. Methods: A diagnosis of complex regional pain syndrome with associated dysautonomia was confirmed by neurologic examination. Aberrant vertical eye movements were observed and a right beating nystagmus was present during eccentric gaze fixation and confirmed on

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Poster Abstracts videonystagmography. This nystagmus matched the frequency of the patient’s midline stereotypies in his hands. Rib excursion measured 0.5 inches and a posterior suboccipital hemangioma was noted. The patient participated in an in house vestibular rehabilitation program that included off vertical axis stimulation and specific brain-based eye movement therapies. Results: The combination of treatment protocols produced a profound change in the patient’s state of being. Pain and ability to tolerate touch significantly reduced over a short period of time and the patient was able to return to school and athletics. Conclusion: This case of complex regional pain syndrome showed significant improvements beyond traditional applications after administration of a functional neurologic treatment regimen as described. The authors suggest further investigation into the mechanisms of the vestibular rehabilitation and these brain-based approaches to patient treatments with complex regional pain syndrome.

RESOLUTION OF HEAD FOGGINESS, DECREASE OF ESSENTIAL TREMORS, INCREASE OF READING COMPREHENSION AND MENTAL FOCUS FOLLOWING A COURSE OF FUNCTIONAL NEUROLOGICAL TREATMENT Susan Esposito,1 David Koentop,1 and Frederick R. Carrick2 1

Life University, Marietta, GA USA Carrick Institute for Graduate Studies, Cape Canaveral FL, USA Email: [email protected] Date Received: June 15 2013 Revised: June 19 2013 Accepted: June 19 2013 2

Background: A 26-year-old male presented to the functional neurology clinic for assessment of tremors, head fogginess, impaired reading comprehension, and inability to focus. Examination revealed a right hypertropia and 6 Hz tremor of his hands bilaterally. The patient showed decreased ability of gaze stabilization in all visual planes with aberrant saccades and pursuits. The patient’s history included numerous concussions and cranial impacts over years of playing hockey. Methods: A thorough neurological exam including Computerized Dynamic Posturography (CDP) and videonystagmography (VNG) testing confirmed a central vestibular lesion, cortical desynchronization, and inability to gaze fixate. He underwent a two month long program of functional neurological treatment that included complex passive movements of upper and lower extremities, brain-based therapeutic eye exercises, somatosensory evoked potential stimulations, and whole-body multi-axis vestibular rehabilitation. Results: The tremors in his hands completely disappeared immediately after treatment, but subsequently re-emerged with reduced amplitude and frequency. Head fogginess, inability of reading comprehension, decreased mental focus, and aberrant eye motions have reduced substantially. CDP scores improved drastically with eyes closed, head in extension on a perturbed surface from 0 to 46.5% stability. Square wave jerks and other eye movement aberrations were markedly diminished on VNG testing. Conclusion: Functional neurological treatments including vestibular rehabilitation strategies were used with positive outcomes in this case of tremors, head fogginess, impaired reading comprehension and mental focus. Further study in of the use of these strategies is suggested.

Poster Abstracts

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RESOLUTION OF POST-CHEMOTHERAPY SHORT-TERM MEMORY LOSS, MIGRAINES, DECREASED SENSATION, AND EXPRESSIVE APHASIA FOLLOWING TWO MONTHS OF FUNCTIONAL NEUROLOGY TREATMENT Susan Esposito,1 David Koentop,1 and Frederick R. Carrick2 1

Life University, Marietta, GA USA Carrick Institute for Graduate Studies, Cape Canaveral FL, USA Email: [email protected] Date Received: June 15 2013 Revised: June 19 2013 Accepted: June 19 2013 2

Background: A 50-year-old female presented to a functional neurology clinic for assessment of short term memory loss, constant migraines rated 10/10, anomia, expressive aphasia, fatigue, and leg pain following a 6 month treatment for ovarian cancer. On examination she presented with lid lag, ptosis, decreased left-sided facial tone, posture abnormalities, inability to distinguish smells, and hyperacusis in her left ear. Methods: A thorough neurological exam including Computerized Dynamic Posturography (CDP) and videonystagmography (VNG) testing confirmed a central vestibular lesion, as well as diminished sensation bilaterally. She underwent a two month long program of functional neurological treatment that included complex passive movements of upper and lower extremities, brain-based therapeutic eye exercises, somatosensory evoked potential stimulations, and wholebody multi-axis vestibular rehabilitation. Results: Patient’s memory improved within a week. Her migraines and sensitivity to loud sounds have resolved. Gaze holding has substantially improved, her expressive aphasia has resolved and her anomia had dramatically improved. She also reported no longer feeling “dazed and confused” and no longer had “brain fog”. Conclusion: Functional neurological treatments including vestibular rehabilitation strategies were used with positive outcomes in this case of post-chemotherapy neurological dysfunction. Further study in of the use of these strategies in cases of neurological aberrancies following a course of chemotherapy is warranted.

REDUCTION OF ABERRANT REFLEXOGENIC MUSCLE FIRING PATTERNS AFTER CORRECTION OF EYE MOVEMENTS IN A WORLD-CLASS PROFESSIONAL TENNIS PLAYER WITH LOW BACK PAIN Frederick R. Carrick,1 Susan Esposito,2 and Benjamin R. Behrendt3 1

Carrick Institute for Graduate Studies, Cape Canaveral, FL USA 2 Life University, Marietta, GA USA 3 Private Practice E-mail: [email protected] Received: June 15 2013 Revised: June 18 2013 Accepted: June 19 2013 Background: A sixteen-year-old world-class professional tennis player was referred to our functional neurology clinic secondary to a significant reduction in ability to play tennis and moderate low back pain (LBP). Methods: MRI, CT, and X-RAY findings of his low back were inconclusive except for mild posterior disc bulging at L3/4, L4/5 and L5/S1. Examination revealed both aberrant cerebellar and functional eye movement findings. He had right hyperopia (extinguished with VOR movements), left corectasia, and accommodation spasm. Saccadic evaluation revealed slower rightward saccades, hypermetric leftward saccades, and irregular phase profile with normal re-fixation. The

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Poster Abstracts patient exhibited a slower response on the left to fine motor tasking, which were slower on left. He had sluggish left brachioradialis reflexes, sluggish left achilles reflexes and pendular right patellar reflexes. When playing tennis and during initial eye movements a retrocolic cervical response was observed when looking down. He underwent a two-week therapy program consisting of specific vestibular rehabilitation including multi-axial labyrinthine stimulation, ocular-motor therapy, laser therapy and manipulation. Results: The patient’s aberrant eye movements improved. He no longer had failure of gaze holding. Pursuits at 0.1 Hz improved. Saccades and optokinetic responses improved significantly. Accommodation spasms and spontaneous facial movement became negligible. Retrocolic-cervical responses resolved. His V:A ratio and reflexes returned normal. He no longer had LBP. Conclusion: Unique and specific brain-based exercises, vestibular rehabilitation, correction of aberrant eye movements and manipulation allowed this patient to return to professional tennis. Authors suggest further investigation into treatment of vestibular, ocular-motor therapy to correct performance.

REDUCTION OF DIZZINESS AND ALLODYNIA IN A TEENAGE MALE AFTER FUNCTIONAL NEUROLOGIC TREATMENT Frederick R. Carrick ,1 Paula Rhodes,2 and Susan Esposito2 1

Carrick Institute of Graduate Studies, Cape Canaveral, FL USA 2 Life University, Marietta, GA 30060 USA E-mail: [email protected] Received: June 15 2013 Revised: June 19 2013 Accepted: June 20 2013 Background: A young teenage male returned to a Functional Neurology clinic after an exacerbation of dizziness and nausea, and a recent streptococcal infection. The patient had previously been treated successfully at this clinic for symptoms related to a central vestibulopathy, experiencing a reduction in allodynia from pain rated at 6-8/10 to a 4/10 (10 being the worst pain). Methods: Central vestibulopathy was confirmed by videonystagmography (VNG) findings, which revealed aberrancies in gaze holding, pursuits, saccades, and optokinetic responses. Computerized dynamic posturography (CDP) measured instability. The patient received treatment involving gaze holding and eye movement exercises, cerebellar stimulation, and multi-axis vestibular stimulation. Results: After two consecutive days of treatment, this patient experienced a significant reduction in dizziness and increased stability. VNG confirmed improvement in all eye movements. Allodynia was further reduced to a level of 1.5-3/10. Conclusion: Vestibular rehabilitation therapies utilizing frontal eye movement exercises, cerebellar stimulation, multi-axis labyrinthine and otolithic stimulation produced significant improvement in this patient’s dizziness and allodynia. This case suggests the need for further study of Functional Neurologic treatment for cases of central vestibulopathy.

Poster Abstracts

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IMPROVEMENTS IN HEADACHES, DIZZINESS, BRAIN FOG AND AKATHISIA THROUGH FUNCTIONAL NEUROLOGICAL APPLICATIONS AND VESTIBULAR REHABILITATION Frederick R. Carrick,1 Susan E. Esposito,2 David Traster2, and Jerome D. Lubbe2 1

Carrick Institute for Graduate Studies, Cape Canaveral, FL USA 2 Life University, Marietta, GA 30060 USA E-mail:[email protected]

Background: We describe a 39-year-old female who presented to a functional neurology clinic with a previous history of autonomic and vestibular complaints. The patient presented with a constellation of symptoms including severe headaches, dizziness, nausea, akathisia, decreased motivation, brain fog, concentration difficulty, anxiety and memory loss. Methods: During initial examination the patient reported severe headaches rated 8 out of 10 with 10 being the worst pain she has ever experienced. Eye movements were aberrant with an inability to maintain gaze stabilization in all vectors, saccadic intrusions of visual pursuits, square wave jerks with inability to hold gaze, and hypometric saccades with slowing of optokinetic nystagmus. All aberrant eye movements were confirmed by videonystagmography. The patient participated in a one-week vestibular rehabilitation program that included multi-axis labyrinthine and otolithic stimulation paired with specific eye movement exercises. Results: The patient reported a decrease in headache duration and frequency to 2 out of 10 with 0 being no pain. There was a near complete resolution of dizziness, nausea, brain fog and akathisia. There were also improvements noted in ability to concentrate, decreased anxiety and brain fog symptoms. During repeat oculomotor examination the patient exhibited normal and adequate pursuit strategies with improved speed of optokinetic nystagmus as well as complete resolution of square wave jerks while holding gaze. Conclusion: The results of this case suggest the necessity of further research into the functional neurologic model of diagnosis and treatment and the use of multimodal vestibular rehabilitation strategies.

TREATMENT OF SEVERE POST ORTHOSTATIC TACHYCARDIA SYNDROME WITH ASSOCIATED SEIZURE ACTIVITY THROUGH FUNCTIONAL NEUROLOGICAL APPLICATIONS AND BRAIN-BASED APPLICATIONS Frederick R. Carrick,1 Susan E. Esposito,2 Jerome D. Lubbe,2 David Traster,2 Jacob Shores,2 and Michael Drzewiecki2 1

Carrick Institute for Graduate Studies, Cape Canaveral, FL USA 2 Life University, Marietta, GA USA E-mail:[email protected] Received: June 15 2013 Revised: June 18 2013 Accepted: June 19 2013 Background: We describe a 16-year-old female who presented to a functional neurology clinic with a previous history of severe post orthostatic tachycardia syndrome with concomitant symptoms of seizures, headaches, fatigue, and severe anxiety. Methods: During examination the patient was unable to stand for any period of time due to orthostatic induced tachycardia and hypoxia. Patient exhibited severe seizure activities and marked tachycardia with movements of three degrees or more while assessing positional changes

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Poster Abstracts in symptomatology. The patient exhibited decreased circulation, sensation and warmth in lower extremities bilaterally. The patient was treated using supine positional changes of two degrees elevation per session on a motorized tilt table. Somatosensory evoked potential therapy was applied to the tibial, peroneal and medial nerves bilaterally. Results: The patient experienced a marked reduction in the frequency, intensity and duration of hypoxic and seizure related events related to her post orthostatic tachycardia syndrome, and withstood positional changes of up to 85 degrees without eliciting any seizure episodes or marked increase in heart rate. Following treatment the patient’s experienced marked improvements in complaints related to headaches, anxiety, fatigue, as well as lower extremity circulation, sensation and temperature. Subsequent to all therapies the patient was able to stand in a weight bearing position without elicitation of seizure or orthostatic symptomatology. Conclusion: The results of this case suggest the necessity of further research into the functional neurologic model of diagnosis and treatment and the use of multimodal vestibular rehabilitation strategies in regards to patients with post orthostatic tachycardia syndrome.

IMPROVEMENTS IN PAIN LEVELS, DIZZINESS AND COGNITIVE FUNCTION SUBSEQUENT TO FUNCTIONAL NEUROLOGY TREATMENT Beatrice D. Tapia1 and Susan E. Esposito1 1

Life University, Marietta, GA USA E-mail: [email protected] Received: June 16 2013 Revised: June 18 2013 Accepted: June 18 2013 Background: A 33-year-old male student presented to a chiropractic university clinic with back pain and concussion symptoms. He experienced approximately six episodes of defecation syncope. During one of these episodes he fell and woke up on his right side with neck and back pain. Since the injury he stuttered, had difficulty retaining and connecting information and had intermittent nominal and expressive aphasia. He felt apathetic and irritable. The patient experienced dizziness when reading more than five minutes at a time. Methods: Compromised left cortical function was confirmed through neurological examination. Decreased amplitude of finger tap test bilaterally, worse on right and decreased right arm swing were noted. Aberrancies in gaze holding and saccadic activity were also present. The patient underwent a four-day treatment program at once per week intervals. Treatment consisted of cortical rehabilitation involving gaze holding strategies, eye exercises, complex movement of the extremities and chiropractic spinal adjustments. Results: The patient is able to study for two hours with no dizziness, neck or back pain. Revised Oswestry Disability Index improved from 26% to 2% and Neck Disability Index decreased from 12% to 0% He is feeling more motivated and communication is significantly improved. He retains information more easily. The patient feels “more connected to people”. The patient has not lost consciousness for two weeks. Conclusion: Strategies utilizing complex movements, spinal manipulation and eye exercises demonstrated positive outcomes, which promote the need for further studies.

Poster Abstracts

INTUITIVE PROCESSES IN MATHEMATICS INSTRUCTION IN NEUROEDUCATION Ola Mualem1 1

The Baptist School, Nazareth Israel E-mail: [email protected] Received: June 15 2013 Revised: June 19 2013 Accepted: June 19 2013 Background: Evidence exists that the inferior parietal cortex is involved in in symbolic numerical abilities. Cases of epilepsia arithmetices that have been observed when performing mental calculations have all demonstrated EEG abnormalities in the inferior parietal cortex. Cohen and Dehaene have also reported on a case of an individual with a lesion of the inferior parietal cortex who could not determine which number came between 3 and 5 yet could determine which day came between Tuesday and Thursday with number sequencing having been singularly impaired but sequencing spared. Stavy and Tirosh defined three intuitive rules which learners apply predicting errors. These rules include: "More A-More B"; "Same A-Same B"; "You can always continue dividing." In addition this work adds, "if (A)  (B) then (B)  (A)?" as well as "If (A)  (B) then (¬A)  (¬B)?" Methods: Students were provided with a questionnaire that consisted of two parts: in the first part, students were asked to answer four questions using "right/wrong" format and if the answer turned out to be "wrong" they were asked to provide an explanation. Two questions relate to claims dealing with the relation between congruent rectangles and their perimeters and the two additional questions relate to claims dealing with rectangles' congruence and their perimeters. Participants included 100 students from the 6th and 7th grades (ages 12-13), half of them (50 students) were 6th graders in elementary school students and the remaining 50 were 7th graders studying in heterogeneous classes in junior high school, in the same socio-economic environment. Results: Approximately one-third of the overall number of students made use of the rule of inversion at least once. A significant negative correlation was found between the use of the rule of inversion and the inclination to solve correctly. Approximately one-half of students applied the rule of negation at least once and a significant negative correlation was found in the use of the rule of negation and the inclination to solve problems correctly. Significant positive correlation was found between the use of the intuitive rules of inversion and the use of the intuitive rule of negation. Conclusions: The results will be discussed in the context of neurological organization of mathematical problem solving capacity with implications for classroom interventions based on solid understanding of nervous system organization.

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IAFNR NEWS AND EVENTS Tricia Merlin Assistant Editor, News and Events

Neurology Conferences 2013-14 *F. R. Carrick Research Institute/National Institute for Brain & Rehabilitation Sciences Sponsored Event March 2013 16-23: 65th AAN Annual Meeting 2013 (American Academy of Neurology), San Diego, USA April 2013 11-14: The 7th World Congress on Controversies in Neurology (CONY), Istanbul, Turkey 18-21: 9th International Congress on Mental Disorders & Other Non-Motor features in Parkinson's Disease and Related Disorders, Seoul, South Korea 26-27: CSNS Spring Meeting 2013 (Council of State Neurosurgical Societies), New Orleans, USA 27-01: 80th AANS Annual Scientific Meeting (American Association of Neurological Surgeons), New Orleans, USA May 2013 22-24: Society of British Neurological Surgeon Spring Meeting 2013, Sheffield, UK 31-03: 17th Congress of the European Federation of Neurological Societies (EFNS), Istanbul, Turkey June 2013

*The Jerusalem International Conference on Neuroplasticity and Cognitive Modifiability 2-5 June 2013 – Jerusalem, Israel http://www.brainconference.com/en/

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IAFNR News and Events 16-20: 17th International Congress of Parkinson's Disease and Movement Disorders, Sydney, Australia 17-20: 9th International Symposium on Pediatric Pain (ISPP 2013), Stockholm, Sweden September 2013 08-13: 15th WFNS World Congress of Neurosurgery, Seoul, South Korea 08-13: EANS Annual Meeting 2013 (European Association of Neurosurgical Societies), Prague, Czech Republic 11-14: FENS Featured Regional Meeting (The Federation of European Neuroscience Societies), Prague, Czech Republic 21-26: XXI World Congress of Neurology, Vienna, Austria 22-27: World Congress of Neurology, Vienna, Austria October 2013 01-04: 3rd World Parkinson Congress 2013, Montreal, Canada 02-04: Eurospine 2013, Liverpook, UK

*IAFNR 2013 4th Annual Conference On Functional Neurology and Rehabilitation 10 -13 October 2013 – Phoenix, AZ USA 19-24: 63rd Annual Meeting of the Congress of Neurological Surgeons, San Francisco, USA November 2013 09-13: Neuroscience 2013, San Diego, USA December 2013 08-11: XX WFN World Congress on Parkinson's Disease and Related Disorders (World Federation of Neurology), Geneva, Switzerland

*International Conference on Disorders of Human Consciousness C. Machado, Conference Organizer Havana, Cuba, 3 - 8 December, 2013 Contact J. Groschel at IAFNR for more details. [email protected]


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FUNCTIONAL NEUROLOGY PRESS http://www.hockeywilderness.com/2012/4/23/2961399/guillaume-latendresse-interview-rdslantichambre http://prohockeytalk.nbcsports.com/2012/04/23/the-latest-gizmo-in-concussion-treatment-wholebody-gyroscopes/ http://www.thedoctorstv.com/videolib/init/5707 http://thestar.blogs.com/olympics/ http://www.nesn.com/.m/2012/03/alexandre-pato-ac-milan-star-will-jet-to-atlanta-to-treatchronic-thigh-problem.html http://www.cbc.ca/sports/hockeynightincanada/insidehockey/video/#id=2171100044 http://watch.discoverychannel.ca/#clip573633 http://www.cbc.ca/day6/blog/2011/11/25/crosbys-doctor-and-rebuilding-the-brain/ http://communities.washingtontimes.com/neighborhood/stress-and-health-drlind/2012/jul/23/olympic-atheletes-chiropractic/ https://rcpt.yousendit.com/1667112355/33acbc4df65ce2b7419c0fa4f7208600

LIFE UNIVERSITY ESTABLISHES FUNCTIONAL NEUROLOGY CLINIC Patients are streaming to Life University’s Functional Neurology Center in Marietta, Georgia. The University Based Center house state of art Neurological diagnostic instrumentation and is staffed by clinicians who are both Board Certified in Neurology and who are Fellowship trained and Certified in Functional Neurology. Life University has more Board Certified Chiropractic Neurologists on its faculty than any other University with a College of Chiropractic. The Life U Functional Neurology Center is associated with the Carrick Research Institute at Life and is active, not only in clinical care but ongoing neurological research. There are over 100 active clinical studies in progress as well as collaborations with other Institutions that involve both clinical and animal studies. Life U faculty had more poster and platform presentations accepted at the recent IAFNR congress in Orlando than any other Institution. They have submitted more papers to the scientific jury for consideration at the IAFNR Phoenix Scientific Congress this October. The Functional Neurology Center at Life was created in response to a global demand for an Institutional Center specializing in Functional Neurology. It serves the referral needs of physicians and has attended patients from around the globe. In fact, 95% of the patients referred to the center are not from the State of Georgia. The clinic has been highlighted in the press due to its popularity with Olympic Athletes and Professional Sports Personnel from hockey, football, soccer, and basketball. The clinical staff is headed by Prof. Frederick R. Carrick and includes the faculty of the Carrick Institute and Clinical Team Leaders, Susan Esposito, DC, DACNB, FACFN, FABEDS and James Duffy, DC, DACNB, FACFN. The Institutional Clinic is also a center for clinical education and Doctoral Students, Interns and Residents from Life University and other Institutions are scheduled to observe patient rounds and to assist in patient care under the direction of Clinic Staff.

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First trimester doctoral students are embracing a clinical reality, as they are able to observe the diagnosis and treatment of the most difficult neurological cases. Life University has a goal to establish and maintain the best clinical education available for its students and this world center is an important part of that training. Physicians from around the globe are able to attend rounds with their patients and observe patient care first hand. The ability to be present with a difficult patient has been very popular with field doctors who have travelled to Life U from all corners of the world. The experience has empowered them to greater clinical excellence. Patients with neurological compromise may be referred to the Life University Functional Neurology Center by calling (770) 426-2636. For More information, please log onto www.lifeneurologycenter.com

University of the Medical Sciences Havana, Cuba

National Institute for Brain & Rehabilitation Sciences Nazareth, Israel

International Association of Functional Neurology& Rehabilitation

2013 Pre-admission Seminars Offered by Prof. Gerry Leisman 23-24 February 2013 Ronkonkoma, New York ____________ 18-20 May 2013 Rockwall, Texas ____________ 17-18 August 2013 Venue TBA ____________ 8-9 October Phoenix, AZ (Prior to IAFNR Conference) ____________ 3-8 December 2013 Havana Cuba + (Presentations to Doctoral Faculty)

Universidad de Ciencias Médicas de la Habana Facultad Manuel Fajardo


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2012 ACCOMPLISHMENTS 1. Journal Development a. Development of the new journal, Functional Neurology, Rehabilitation, and Ergonomics, published by Nova Science Publishers, now finished volumes 1 and 2 with four issues each. (https://www.novapublishers.com/catalog/product_info.php?products_id=16707)

2. External Academic Linkages a. Finalized contractual relationship for doctoral students working in our laboratories from the University of Medical Sciences of Havana.

b. Contractual relationship completed and now accepted research fellows into laboratories. i. Articulation agreement with the Mind Sciences Institute at the Massachusetts Institute of Technology (MIT) and Dr. Newton Howard finalized (http://www.brainsciences.org/Research-Team/bsffellows.html). ii. Development of articulation agreement with numerous investment groups to fund R&D and patent development. iii. Development of an articulation agreement for BS level engineering students AND MSc. students of Biomedical Engineering at ORTBraude College in Carmiel to work with The Institute for Brain and Rehabilitation Sciences in Nazareth on joint projects through the Department of Mechanical Engineering’s programme in Biomedical Engineering. iv. Development of articulation agreement with Cornell University on joint R&D projects through Prof David Robertshaw supported by a US Department of State Fullbright grant through Dr. Raed Mualem, IAFNR-Israel. v. Developed affiliation agreement shared faculty and research partnership with the Centro di Intagrativi Rehabilitation Neurologica and the Instututo di Neurologia e Neurochirugia through Prof. Calixto Machado in Havana Cuba.

3. Conference Sponsorships and Organization a. Conference sponsor and participation of Nazareth Academic Institute, ORTBraude College of Engineering, Carmiel, the Institute for Brain and Rehabilitation Sciences-Nazareth, and M.A.T.I.- Nazareth at the International Association of Functional Neurology and Rehabilitation in October in Phoenix, Arizona, supported, in part, through the Israel Ministry of Trade and Industry. (http://www.frcarrickresearchinstitute.org/userfiles/IAFNRSPEAKERS.pdf). b. Planning of conference with ORT-Braude College of Engineering, The Institute for Brain and Rehabilitation Sciences, NAI, The F. R. Carrick Research Institute and the Department of Industrial Engineering of Ben-Gurion University of the Negev of a conference in 2013 on Applications of Optimization and Functional Connectivities in Havana, Cuba. c. Sponsor through The Institute for Brain and Rehabilitation Sciences, ORTBraude College of Engineering, and NAI of the 3rd Annual Conference on Chronic Diseases of Childhood, and Child Health and Human Development, Jerusalem 5-8 December 2012 with Harvard University, the University of Kentucky, Hadassah School of Medicine, Department of Paediatrics, and the

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IAFNR News and Events National Institute for Child Health and Human Development. (http://www.isas.co.il/chhd/advisory_committees.php) d. Sponsor and participant of and in conference on Neuroplasticity and Cognitive Modifiability 2-5 June 2013 Jerusalem (http://www.brainconference.com /en/index.php?page_id=8).

4. Grant and External Funding Applications: a. European Union-Neuron 7: Leisman G, Howard N. “Measurement of

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Optimization of Neuro-Electrophysiological and Cognitive Performance in Autism.” European Research Projects on Novel Methods and Approaches towards the Understanding of Brain Diseases.” Submission of grant application to European Union for Neuron-7 contest collectively with NAI, Institute for Brain and Rehabilitation Sciences-Israel, La Sorbonne Institute for Mathematics and Computational Sciences, and Sigmund Freud University, Vienna, approved by Chief Scientist office Misrad Habriut. 120.000 € (unsuccessful) (unsuccessful for technical reasons and a resubmission is planned). Autism Speaks: Leisman G, Melillo R. “The nature of functional connectivities on neurocognitive performance in autistic spectrum disorder: hemispheric balancing as a potential remediative tool.” $80,000 (Trailblazer Award – unsuccessful) Q-Bank Greenwich CT US: Leisman G. “Establishing a Rehabilitation Research Laboratory Emphasizing Exploitation of Dual-Use Technologies, Located in the Galilee. $200,000 (pending). DARPA US. Howard N, Leisman G. (with MIT & Cntr. For Adv. Defense Studies) “Discovering and Modeling Narrative Influence on Neurobiology” DARPA-BAA-12-03 NARRATIVE NETWORK. DARPA (USA) $10,318,136 (Unsuccessful) Eugene Kahane Foundation: Leisman G, Mualem R. “Rehabilitation Research Laboratory.” Submission to the Eugene Kahana Foundation for laboratory funding $197,430 – successful pending final determination of the award. Mcknight Endowment Fund for Neuroscience Memory and Cognitive Disorder Award 2013 McKnight Neuroscience. Leisman G, Rosner A. “The Development of Functional Connectivities in Pre/Post-Natal Development of Consciousness: When Does the Human Become Conscious?” $386,000 (pending) The International College of Applied Kinesiology. Leisman G. “The Effects of Therapy Localization on IEMG” successful $29,650 Brain and Behaviour Research Foundation: Leisman G. “Measurement of Optimization of Neuro-Electrophysiological and Cognitive Performance in Autism”, 2012 NARSAD Distinguished Investigator Grant $97,610 (pending) Simmons Foundation: Optimization of Cognitive Performance in Autism, $250,000 (pending).

5. Recent Conference Presentations a. Leisman G. The Development of Functional Connectivities in the Pre- and PostNatal Development of Consciousness. [Invited Speaker, International Symposium of Disorders of consciousness, Havana, Cuba 6-8, December 2011] (http://www.engraciacal.com/scientificprogram/abstracts/tabid/64/Default.aspx) b. Leisman G. The Development of Functional Connectivities in the Pre- and PostNatal Development of Consciousness. [Invited Opening Lecture International Symposium of Disorders of Consciousness, Havana, Cuba, December 6 – 8, 2011].


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(http://www.engraciacal.com/ScientificProgram/SubmittedAbstracts/tabid/72/De fault.aspx) Leisman G, Melillo R, Machado C. Functional Disconnectivities in Autistic Spectrum Individuals. [Paper presented at the International Symposium of Disorders of Consciousness, Havana, Cuba, December 6–8, 2011]. (http://www.engraciacal.com/ScientificProgram/SubmittedAbstracts/tabid/72/De fault.aspx) Pérez-Nellar J, Machado C, Rodríguez-Rojas R, Estévez M., Chinchilla M, Carrick, FR, Melillo R, Leisman G. Structural Neuroimaging Assessment of PVS Patients [Paper presented at the International Symposium of Disorders of Consciousness, Havana, Cuba, December 6 – 8, 2011]. (http://www.engraciacal.com/ScientificProgram/SubmittedAbstracts/tabid/72/De fault.aspx) Batista-García-Ramó K, Rodríguez-Rojas R, Carballo-Barreda M, Machado C, Melillo R, Leisman G. Tractography Assessment in Autism Spectrum Disorders. [Paper presented at the International Symposium of Disorders of Consciousness, Havana, Cuba, December 6 – 8, 2011]. (http://www.engraciacal.com/ ScientificProgram/SubmittedAbstracts/tabid/72/Default.aspx) Pérez-Nellar J, Machado C, Rodríguez-Rojas R, Estévez M, Chinchilla M, Carrick FR, Melillo R, Leisman G. Neuroimaging in Non-Fatal Central Transtentorial Herniation. [Paper presented at the International Symposium of Disorders of Consciousness, Havana, Cuba, December 6 – 8, 2011]. (http://www.engraciacal.com/ScientificProgram/SubmittedAbstracts/tabid/72/De fault.aspx) Leisman G. Children’s Language Production: How Cognitive Neuroscience & Industrial Engineering Can Inform Public Education Policy and Practice [Invited Paper Presented at the Oxford University Roundtable on Public Policy, 11-15 March, 2012] (http://www.oxfordroundtable.com/index.php/view/SessionsItem/id/141) Rosner AF, Leisman G, Gilchriest J. Reliability and validity of therapy localization in applied kinesiology. [Paper to be presented at the Society for Neuroscience, New Orleans, October 16-18, 2012] (http://www.sfn.org/am2012/) Leisman G. The Brain on Art: Auditory, Visual, Spatial Aesthetic, and Artistic Training Facilitates Brain Plasticity [Invited presentation, International Association of Functional Neurology and Rehabilitation, Phoneix, AZ USA 2428 October, 2012] (http://www.frcarrickresearchinstitute.org/conference) Jubran F, Leisman G. Intersensory Integration in Functional Neurology: An Engineer's Perspective of Music as an Interventionary Medium. [Paper presented, International Association of Functional Neurology and Rehabilitation, Phoenix, AZ USA 24-28 October, 2012] (http://www.frcarrick researchinstitute.org/conference) Leisman G, Melillo R, Machado C, Rodriguez-Rojas R, Batista K, Carballo M, Mualem R. Functional Disconnectivities in Autistic Spectrum Individuals [Paper to be presented at the International Conference of Child Health and Human Development, Jerusalem, Israel December, 2012] Leisman G. Functional Connectivities in the Post-Natal Development of Consciousness. [Paper to be presented at the International Conference of Child Health and Human Development, Jerusalem, Israel December, 2012] (www.isas.co.il/chhd/Child_Development_Brochure.pdf) Estévez M, Machado C, Leisman G, Melillo R, Machado A, Hernández-Cruz A, Arias A, Rodríguez-Rojas R, Carballo M. Eegconn: A Software Tool for Offline

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IAFNR News and Events Qeeg Analysis, Including Spectral Univariate and Bivariate Processes and Linear and Non-Linear Indices of Brain Connectivity in Autistic Spectrum Disorder. [Paper to be presented at the International Conference of Child Health and Human Development, Jerusalem, Israel December, 2012] (www.isas.co.il/chhd/Child_Development_Brochure.pdf) n. Rodriguez-Rojas R, Batista K, Carballo, M, Machado C, Leisman G, Estévez M, Melillo R. Anatomical And Topological Connectivity Reveal Different Attributes of Disrupted Small-World Networks in Autistic Children. [Paper to be presented at the International Conference of Child Health and Human Development, Jerusalem, Israel December, 2012] (www.isas.co.il/chhd/Child_ Development_Brochure.pdf) o. Jammalieh J, Mualem R, Leisman G. Clinical effects of the development of physiological rhythms in premature infants. [Paper presented at the International Conference of Child Health and Human Development, Jerusalem, Israel December, 2012] (http://www.isas.co.il/chhd/)

6. Recent Books and Chapters a. Melillo RM, Leisman G. Neurobehavioral Disorders of Childhood Beijing, China: People's Medical Publishing House (PMPH) 2010 [Chinese Translation].

b. Leisman G,Melillo R. The Development of the Frontal Lobes in Infancy and Childhood: Asymmetry and the Nature of Temperament and Adjustment. In: Cavanna, A.E. (Ed.) Frontal Lobe: Anatomy, Functions and Injuries. Hauppauge, NY: Nova Scientific Publishers, 2012. (https://www.novapublishers.com /catalog/product_info.php?products_id=33647) c. Leisman. G, Melillo R. The Basal Ganglia: Motor and Cognitive Relationships in a Clinical Neurobehavioral Context In: E. Franz (Ed) Leisman G, Melillo R. The Basal Ganglia: Motor and Cognitive Relationships in a Clinical Neurobehavioral Context. In: Franz E, editor. Basal Ganglia. Rijeka, Croatia: InTech; 2012. [ISBN 980-953307-193-5] d. Leisman G, Melillo R, Mualem R, Machado C. The effect of music training and production on functional brain organization and cerebral asymmetry. In: Kravchuk T, Groysman A, Soddu C, Colabella E, Leisman G, editors. Art, Science and Technology. Mialno, Italy: Domus Argenia Publisher; 2012. pp. 133-139. [ISBN: 978-88-96610-24-4] (www.artscience-ebookshop.com/1stAST_proceedings.pdf) e. Leisman G. Behavioral Disorders: New Research. Hauppauge, NY: Nova Scientific Publishers; 2013 [In Press].

7. Published Papers in Indexed Peer-reviewed Journals a. Leisman G, Melillo R. Functional Disconnectivities in Autistic Spectrum Disorder as a Potent Model for Explaining Disorders of Consciousness and Cognition in the Brain and Nervous System. Funct Neurol Rehabil Ergon. 2011;1(1):101-145. (https://www.novapublishers.com/catalog/product_info.php?products_id=21547) b. Leisman G, Machado C. Considering Consciousness Clinically. Funct Neurol Rehabil Ergon. 2011;1(1):17-23. (https://www.novapublishers.com/catalog /product_info.php?products_id=21537) c. Carrick FR, Pagnacco G, Oggero E, Sullivan S, Barton D, Esposito S, Leisman G, Melillo R. The Effects of Whole Body Rotations in the Pitch and Yaw Planes on Postural Stability. Funct Neurol Rehabil Ergon. 2011;1(2):167-179. (https://www.novapublishers.com/catalog/product_info.php?products_id=23933) d. Leisman G. Brain Networks, Plasticity, and Functional Connectivities Inform Current Directions. Funct Neurol Rehabil Ergon. 2011;1(2):315-356. (https://www.novapublishers.com/catalog/product_info.php?products_id=23945)


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e. Machado C, Estévez M, Rodríguez R, Carballo M, Pérez-Nellar J, Gutiérrez J, Fleitas

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M, Leisman G. Are Persistent Vegetative State Patients Isolated from the Outside World? Funct Neurol Rehabil Ergon. 2011;1(2):357-377. (https://www.novapublishers.com/catalog/product_info.php?products_id=23947). Machado C, Estévez M, Carrick F, Melillo R, Leisman G. qEEG may increase the reliability of diagnostic and prognostic procedures in cerebral arterial gas embolism. Clinical Neurophysiology. 2012;123(2):225-226. (http://www.ncbi.nlm.nih.gov /pubmed/21784702) (http://www.sciencedirect.com/science/article/pii/S1388245711004615) Machado C, Estevez M, Rodriguez R, Carrick FR, Melillo R, Leisman G. Bilateral N20 Absence in Post-Anoxic Coma: Do You Pay Attention? Clinical Neurophysiology. 2012;123(1). (http://dx.doi.org/10.1016/j.clinph.2011.11.008) Leisman G, Melillo R. The Development of the Frontal Lobes in Infancy and Childhood: Asymmetry and the Nature of Temperament and Adjustment. In: Cavanna AE, editor. Frontal Lobe: Anatomy, Functions and Injuries. Hauppauge, NY: Nova Scientific Publishers; 2012. Leisman G, Melillo R. The Basal Ganglia: Motor and Cognitive Relationships in a Clinical Neurobehavioral Context. In: E. Franz E, editor. Basal Ganglia. Rijeka, Croatia: InTech; 2012. [ISBN 980-953-307-193-5] Leisman, G and Melillo, R. EEG Coherence Measures Functional Disconnectivities in Autism. Journal of Pediatric Research, 2013 [in Press]. Machado C, Estevez M, Rodriguez R, Carrick FR, Melillo R, Leisman G. Bilateral N20 Absence in Post-Anoxic Coma: Do You Pay Attention? Clinical Neurophysiology. 2012;123(1):1264-1266. (http://dx.doi.org/10.1016/j.clinph. 2011.11.008). Leisman G, Machado C, Melillo R, Mualem R. Intentionality and “Free- Will” From a Neurodevelopmental Perspective. Frontiers of Integrative Neuroscience. 2012;6:36. doi: 10.3389/ fnint.2012.00036 (http://www.frontiersin.org/Integrative _Neuroscience/10.3389/fnint.2012.00036/ful Leisman G. Children’s Language Production: How Cognitive Neuroscience & Industrial Engineering Can Inform Public Education Policy and Practice Forum on Public Policy. A Journal of the Oxford Roundtable. 2012;2012(1):1-14. (http://forumonpublicpolicy.com/vol2012.no1/archive/leisman.pdf)(http://forumonpu blicpolicy.com/vol2012.no1/earlychild2012.html) Leisman G. Auditory, Visual and Spatial Aesthetic and Artistic Training Facilitates Brain Plasticity: The Arts as a Vehicle for Rehabilitation. Funct Neurol Rehabil Ergon. 2012;2(3):251-266. (https://www.novapublishers.com/catalog/product_ info.php?products_id=36803) Jubran F, Leisman G. Intersensory Integration in Functional Neurology: An Engineer's Perspective of Music as an Interventionary. Funct Neurol Rehabil Ergon. 2012;2(3):215-222. (https://www.novapublishers.com/catalog/product_info.php?products_id=36803) Machado-Ferrer Y, Estevez M, Machado C, Hernández-Cruz, Leisman G, Carrick FR, Melillo R, Beltrán C. Heart Rate Variability for Assessing Comatose Patients with Different Glasgow Coma Scale Scores. Clinical Neurophysiology. 2012;123(3):572-581.

8. Papers in Indexed Peer-Reviewed Journals Currently In Press. a. Leisman G. Cognitive Science Applied to Medical Expertise. Journal of the Royal Society of Medicine. 2012 (in Press).

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b. Leisman G, Melillo R. Functional Disconnectivities in Autism. International Journal of Adolescent Medicine and Health. 2012 [in Press]

c. Machado C, Estevez M, Rodriguez R, Perez-Nellar J, Chinchilla M, Carrick FR, Leisman, G, Melillo R, Gutierrez J, Carballo M, Machado A, Olivares A, Perez-Cruz N, Belttran C. Zolpidem Arousing Effect in Persistent Vegetative State Patients: Autonomic, EEG and Behavioral Assessment. Clinical Neurophysiology. 2012. [InPress].



LITERATURE CALLING A REVIEW OF RECENT PUBLICATIONS OF INTEREST TO FUNCTIONAL NEUROLOGY An fMRI-Based Neurologic Signature of Physical Pain Wager TD, Atlas LY, Lindquist MA, Roy M, Woo C-W, Kross E. New Eng J Med. 2013;368:1388-1397. BACKGROUND: Persistent pain is measured by means of self-report, the sole reliance on which hampers diagnosis and treatment. Functional magnetic resonance imaging (fMRI) holds promise for identifying objective measures of pain, but brain measures that are sensitive and specific to physical pain have not yet been identified. METHODS: In four studies involving a total of 114 participants, we developed an fMRI-based measure that predicts pain intensity at the level of the individual person. In study 1, we used machine-learning analyses to identify a pattern of fMRI activity across brain regions — a neurologic signature — that was associated with heatinduced pain. The pattern included the thalamus, the posterior and anterior insulae, the secondary somatosensory cortex, the anterior cingulate cortex, the periaqueductal gray matter, and other regions. In study 2, we tested the sensitivity and specificity of the signature to pain versus warmth in a new sample. In study 3, we assessed specificity relative to social pain, which activates many of the same brain regions as physical pain. In study 4, we assessed the responsiveness of the measure to the analgesic agent remifentanil. RESULTS: In study 1, the neurologic signature showed sensitivity and specificity of 94% or more (95% confidence interval [CI], 89 to 98) in discriminating painful heat from nonpainful warmth, pain anticipation, and pain recall. In study 2, the signature discriminated between painful heat and nonpainful warmth with 93% sensitivity and specificity (95% CI, 84 to 100). In study 3, it discriminated between physical pain and social pain with 85% sensitivity (95% CI, 76 to 94) and 73% specificity (95% CI, 61 to 84) and with 95% sensitivity and specificity in a forced-choice test of which of two conditions was more painful. In study 4, the strength of the signature response was substantially reduced when remifentanil was administered. CONCLUSIONS: It is possible to use fMRI to assess pain elicited by noxious heat in healthy persons. Future studies are needed to assess whether the signature predicts clinical pain. (Funded by the National Institute on Drug Abuse and others.)

Mom’s Obesity May Affect Unborn Child’s Brain Feb. 11, 2013 Courtesy of the Society for Maternal-Fetal Medicine and World Science staff Obesity in a pregnant mother may lead to abnormal brain development in the fetus, scientists are warning, based on a finding of abnormal patterns of genetic activity in such fetuses. Although the implications are unclear, scientists called the findings a potentially major concern, given that an estimated one in three U.S. women are obese at conception. Researchers from Tufts Medical Center in Boston plan to present the findings on Feb. 15 at the Society for Maternal-Fetal Medicine’s annual meeting in San Francisco.

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Literature Calling “Women won’t be surprised to hear being obese while pregnant can lead to obesity in the child,” said Andrea Edlow, lead author of the study. “But what might surprise them is the potential effect it has on the brain development of their unborn child.” The study examined the fetal development of 16 pregnant women, eight obese and eight lean. As early as the second trimester, obese women’s fetuses were found to have different patterns of gene activity, suggestive of abnormal brain development. During gestation, fetuses go through apoptosis—a normal process of programmed “suicide” by certain brain cells. This constitutes a sort of pruning, a clearing out space for new growth, said Diana Bianchi, senior author of the study and executive director of the Mother Infant Research Institute at Tufts. Fetuses of obese women had genetic activity indicating decreased apoptosis, an important part of normal fetal brain development, she explained. It’s unclear what effect this will ultimately have on the developed brain, she added, but she said maternal obesity is a rapidly growing problem in the United States and has been associated with increased rates of autism and altered appetite regulation. Bianchi and Edlow say their next step will be to use laboratory mice to further study the observed genetic differences.

How Do You Learn to Walk? Thousands of Steps and Dozens of Falls per Day Adolph KE, Cole WG, Komati M, Garciaguirre JS, Badaly D, Lingeman JM, Chan G, Sotsky RB. Psychological Science. 2012; 23(11):1387-1394. A century of research on the development of walking has examined periodic gait over a straight, uniform path. The current study provides the first corpus of natural infant locomotion derived from spontaneous activity during free play. Locomotor experience was immense: Twelveto 19-month-olds averaged 2,368 steps and 17 falls per hour. Novice walkers traveled farther faster than expert crawlers, but had comparable fall rates, which suggests that increased efficiency without increased cost motivates expert crawlers to transition to walking. After walking onset, natural locomotion improved dramatically: Infants took more steps, traveled farther distances, and fell less. Walking was distributed in short bouts with variable paths—frequently too short or irregular to qualify as periodic gait. Nonetheless, measures of periodic gait and of natural locomotion were correlated, which indicates that better walkers spontaneously walk more and fall less. Immense amounts of time-distributed, variable practice constitute the natural practice regimen for learning to walk.

Distinct Attention Networks for Feature Enhancement and Suppression in Vision Bridwell DA, Srinivasan R. Psychological Sciences. 2012 Oct 1;23(10):1151-1158. Attention biases sensory processing toward neurons containing information about behaviorally relevant events. These attentional biases apparently reflect the combined influence of feature enhancement and suppression. We examined the separate influence of enhancement and suppression in visual processing by determining whether responses to an unattended flicker were modulated when the flicker features matched target features at the attended location, competed with those features, or were neutral. We found that suppression primarily modulated parietal networks with a preferred frequency in the lower alpha band (f2 = 8 Hz), and enhancement primarily influenced parietal networks with a preferred frequency in the upper alpha band (f2 = 12 Hz). These responses were coupled with perception, with large responses to the unattended flicker leading to subsequently detected targets when the target features matched the flicker features (i.e., during enhancement). Our results suggest that enhancement and suppression are two distinct processes that work together to shape visual perception.

Literature Calling

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Growing Up with Asperger’s Syndrome: Developmental Trajectory of Autobiographical Memory Bon L, Baleyte J-M, Piolino P, Desgranges B, Eustache F and Guillery-Girard B. Front Psychol. 2013; 3:605. doi: 10.3389/fpsyg.2012.00605 Autobiographical memory (AM) and social cognition share common properties and both are affected in autism spectrum disorders (ASD). So far, most of the scant research in ASD has concerned adults, systematically reporting impairment of the episodic component. The only study to be conducted with children concluded that they have poorer personal semantic knowledge than typical developing children. The present study explores the development of both components of AM in an 8-year-old boy diagnosed with Asperger’s syndrome, based on three examinations in 2007, 2008, and 2010. On each occasion, he underwent a general neuropsychological assessment including theory of mind (ToM) tasks, and a specially designed AM task allowing us to test both the semantic and the episodic components for three lifetime periods (current year, previous year, and earlier years). We observed difficulties in strategic retrieval and ToM, with a significant improvement between the second and third examinations. Regarding AM, different patterns of performance were noted in all three examinations: (1) relative preservation of current year personal knowledge, but impairment for the previous and earlier years, and (2) impairment of episodic memory for the current and previous year, but performances similar to those of controls for the earlier years. The first pattern can be explained by abnormal forgetting and by the semanticization mechanism, which needs verbal communication and social interaction to be efficient. The second pattern suggests that the development of episodic memory only reached the stage of “event memory.” This term refers to memory for personal events lacking in details or spatiotemporal specificity, and is usually observed in children younger than five. We conclude that the abnormal functioning of social cognition in ASD, encompassing social, and personal points of view, has an impact on both components of AM.

Cognition-Emotion Dysinteraction In Schizophrenia Anticevic A, Corlett PR. Front Psychol. 2012;3:392. doi: 10.3389/fpsyg.2012.00392. This article was submitted to Frontiers in Emotion Science, a specialty of Frontiers in Psychology Evolving theories of schizophrenia emphasize a “disconnection” in distributed fronto-striatallimbic neural systems, which may give rise to breakdowns in cognition and emotional function. We discuss these diverse domains of function from the perspective of disrupted neural circuits involved in “cold” cognitive vs. “hot” affective operations and the interplay between these processes. We focus on three research areas that highlight cognition-emotion dysinteractions in schizophrenia: First, we discuss the role of cognitive deficits in the “maintenance” of emotional information. We review recent evidence suggesting that motivational abnormalities in schizophrenia may in part arise due to a disrupted ability to “maintain” affective information over time. Here, dysfunction in a prototypical “cold” cognitive operation may result in “affective” deficits in schizophrenia. Second, we discuss abnormalities in the detection and ascription of salience, manifest as excessive processing of non-emotional stimuli and inappropriate distractibility. We review emerging evidence suggesting deficits in some, but not other, specific emotional processes in schizophrenia – namely an intact ability to perceive emotion “in-themoment” but poor prospective valuation of stimuli and heightened reactivity to stimuli that ought to be filtered. Third, we discuss abnormalities in learning mechanisms that may give rise to delusions, the fixed, false, and often emotionally charged beliefs that accompany psychosis. We highlight the role of affect in aberrant belief formation, mostly ignored by current theoretical models. Together, we attempt to provide a consilient overview for how breakdowns in neural systems underlying affect and cognition in psychosis interact across symptom domains. We conclude with a brief treatment of the neurobiology of schizophrenia and the need to close our

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Literature Calling explanatory gap between cellular-level hypotheses and complex behavioral symptoms observed in this illness.

Toward A Neurobiology Of Unrealistic Optimism Shah P. Front Psychol. 2012;3:344. doi: 10.3389/ fpsyg.2012.00344 Research spanning three decades has found that human judgment is characterized by unrealistic optimism (or “optimism bias”), the tendency to underestimate the likelihood of negative events and overestimate the likelihood of positive events (Weinstein, 1980). This work has recently garnered much interest, some question its existence (Harris and Hahn, 2011), while others have found support for it by using novel experiments (Massey et al., 2011; Simmons and Massey, 2012). Most recently, attention has turned to investigating the neural underpinnings of this phenomenon (Sharot et al., 2007, 2011). A new study (Sharot et al., 2012) has now shown that optimism bias is increased by up-regulating dopaminergic function via dihydroxy-lphenylalanine (l-DOPA). Sharot et al. (2012) propose that this process occurs as l-DOPA attenuates belief updating in response to bad news about the future. In light of such evidence, the implications for future research on unrealistic optimism are discussed. Unrealistic optimism is recognized as one of the major human cognitive biases (Kahneman, 2011). It has been the focus of much research, particularly in social and clinical psychology; here it is argued that optimism bias is not just a pervasive feature of human judgment, but a crucial requirement to guard against depression (Taylor and Brown, 1988). Despite the wealth of research, this work has been scrutinized, as many question (e.g., Moore and Small, 2008) the methods used in the majority of studies where the “comparison approach” is used, i.e., where optimism bias is interpreted by optimistic comparisons of one’s personal risk, relative to the average person. A compelling demonstration of how optimism research may be riddled with statistical artifacts has recently emerged (Harris and Hahn, 2011). In contrast, Sharot et al. (2011) provided a promising, new approach to investigate optimism bias, via the concept of belief change. Sharot and colleagues reported that unrealistic optimism persists “in the face of reality” because good (versus bad) news is incorporated significantly more into one’s beliefs of personal risk. They reported that this asymmetric “updating” originates from a prediction error bias which correlates (determined by functional magnetic resonance imaging) with activity in various regions of the frontal cortex. Importantly, on first glance, this method does not appear to suffer from the problems inherent in the comparison approach of optimism research, and their findings have been interpreted as evidence of unrealistic optimism. This has naturally shifted attention towards the neurobiology underlying this phenomenon.

Music and Early Language Acquisition Brandt A, Gebrian M and Slevc LR. Front Psychol. 2012;3:327. doi: 10.3389/fpsyg.2012.00327 Language is typically viewed as fundamental to human intelligence. Music, while recognized as a human universal, is often treated as an ancillary ability – one dependent on or derivative of language. In contrast, we argue that it is more productive from a developmental perspective to describe spoken language as a special type of music. A review of existing studies presents a compelling case that musical hearing and ability is essential to language acquisition. In addition, we challenge the prevailing view that music cognition matures more slowly than language and is more difficult; instead, we argue that music learning matches the speed and effort of language acquisition. We conclude that music merits a central place in our understanding of human development.

Literature Calling

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Freezing of Gait in Parkinson’s Disease: Disturbances in Automaticity and Control Vandenbossche J, Deroost N, Soetens E, Coomans D, Spildooren J, Vercruysse S, Nieuwboer A, Kerckhofs E. Front Hum Neurosci. 2013;6:356. doi: 10.3389/fnhum.2012.00356 Recent studies emphasize a key role of controlled operations, such as set-shifting and inhibition, in the occurrence of freezing of gait (FOG) in Parkinson’s disease (PD). However, FOG can also be characterized as a de-automatization disorder, showing impairments in both the execution and acquisition of automaticity. The observed deficits in automaticity and executive functioning indicate that both processes are malfunctioning in freezers. Therefore, to explain FOG from a cognitive-based perspective, we present a model describing the pathways involved in automatic and controlled processes prior to a FOG episode. Crucially, we focus on disturbances in automaticity and control, regulated by the frontostriatal circuitry. In complex situations, nonfreezing PD patients may compensate for deficits in automaticity by switching to increased cognitive control. However, as both automatic and controlled processes are more severely impaired in freezers, this hampers cognitive compensation in FOG, resulting in a potential breakdown. Future directions for cognitive rehabilitation are proposed, based on the cognitive model we put forward.

“Doctor” Or “Darling”? Decoding the Communication Partner from Ecog of the Anterior Temporal Lobe During Non-Experimental, Real-Life Social Interaction Derix J, Iljina O, Schulze-Bonhage A, Aertsen A and Ball T. Front Hum Neurosci. 2012;6:251. doi: 10.3389/fnhum.2012.00251 Human brain processes underlying real-life social interaction in everyday situations have been difficult to study and have, until now, remained largely unknown. Here, we investigated whether electrocorticography (ECoG) recorded for pre-neurosurgical diagnostics during the daily hospital life of epilepsy patients could provide a way to elucidate the neural correlates of nonexperimental social interaction. We identified time periods in which patients were involved in conversations with either their respective life partners (Condition 1; C1) or attending physicians (Condition 2; C2). These two conditions can be expected to differentially involve subfunctions of social interaction which have been associated with activity in the anterior temporal lobe (ATL), including the temporal pole (TP). Therefore, we specifically focused on ECoG recordings from this brain region and investigated spectral power modulations in the alpha (8–12Hz) and theta (3– 5Hz) frequency ranges, which have been previously assumed to play an important role in the processing of social interaction. We hypothesized that brain activity in this region might be sensitive to differences in the two interaction situations and tested whether these differences can be detected by single-trial decoding. Condition-specific effects in both theta and alpha bands were observed: the left and right TP exclusively showed increased power in C1 compared to C2, whereas more posterior parts of the ATL exhibited similar (C1 > C2) and also contrary (C2 > C1) effects. Single-trial decoding accuracies for classification of these effects were highly above chance. Our findings demonstrate that it is possible to study the neural correlates of human social interaction in non-experimental conditions. Decoding the identity of the communication partner and adjusting the speech output accordingly may be useful in the emerging field of brain-machine interfacing for restoration of expressive speech.

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Differential Vulnerability of Substantia Nigra and Corpus Striatum to Oxidative Insult Induced by Reduced Dietary Levels of Essential Fatty Acids Cardoso HD, Passos PP, Lagranha CJ, Ferraz AC, Santos Junior EF, Oliveira RS, Oliveira PEL, Santos RCF, Santana DF, Borba JMC, Rocha-de-Melo A, Guedes RCA, Navarro DMAF, Santos GKN, Borner R, Picanço- Diniz CW, Beltrão EI, Silva JF, Rodrigues MCA and Andrade da Costa BL. Front Hum Neurosci. 2012;6:249. doi: 10.3389/ fnhum. 2012.00249 Oxidative stress (OS) has been implicated in the etiology of certain neurodegenerative disorders. Some of these disorders have been associated with unbalanced levels of essential fatty acids (EFA). The response of certain brain regions to OS, however, is not uniform and a selective vulnerability or resilience can occur. In our previous study on rat brains, we observed that a twogeneration EFA dietary restriction reduced the number and size of dopaminergic neurons in the substantia nigra (SN) rostro-dorso-medial. To understand whether OS contributes to this effect, we assessed the status of lipid peroxidation (LP) and anti-oxidant markers in both SN and corpus striatum (CS) of rats submitted to this dietary treatment for one (F1) or two (F2) generations. Wistar rats were raised from conception on control or experimental diets containing adequate or reduced levels of linoleic and α-linolenic fatty acids, respectively. LP was measured using the thiobarbituric acid reaction method (TBARS) and the total superoxide dismutase (t-SOD) and catalase (CAT) enzymatic activities were assessed. The experimental diet significantly reduced the docosahexaenoic acid (DHA) levels of SN phospholipids in the F1 (∼28%) and F2 (∼50%) groups. In F1 adult animals of the experimental group there was no LP in both SN and CS. Consistently, there was a significant increase in the t-SOD activity (p < 0.01) in both regions. In EF2 young animals, degeneration in dopaminergic and non-dopaminergic neurons and a significant increase in LP (p < 0.01) and decrease in the CAT activity (p < 0.001) were detected in the SN, while no inter-group difference was found for these parameters in the CS. Conversely, a significant increase in t-SOD activity (p < 0.05) was detected in the CS of the experimental group compared to the control. The results show that unbalanced EFA dietary levels reduce the redox balance in the SN and reveal mechanisms of resilience in the CS under this stressful condition.

The Cinema- Cognition Dialogue: A Match Made In Brain Dudai Y. Front Hum Neurosci. 2012;6:248. doi: 10.3389/fnhum.2012.00248 That human evolution amalgamates biological and cultural change is taken as a given, and that the interaction of brain, body, and culture is more reciprocal then initially thought becomes apparent as the science of evolution evolves (Jablonka and Lamb, 2005). The contribution of science and technology to this evolutionary process is probably the first to come to mind. The biology of Homo sapiens permits and promotes the development of technologies and artefacts that enable us to sense and reach physical niches previously inaccessible. This extends our biological capabilities, but is also expected to create selective pressures on these capabilities. The jury is yet out on the pace at which critical biological changes take place in evolution. There is no question, however, that the kinetics of technological and cultural change is much faster, rendering the latter particularly important in the biography of the individual and the species alike. The capacity of art to enrich human capabilities is recurrently discussed by philosophers and critics (e.g., Arsitotle/Poetics, Richards, 1925; Smith and Parks, 1951; Gibbs, 1994). Yet less attention is commonly allotted to the role of the arts in the aforementioned ongoing evolutional tango. My position is that the art of cinema is particularly suited to explore the intriguing dialogue between art and the brain. Further, in the following set of brief notes, intended mainly to trigger further thinking on the subject, I posit that cinema provides an unparalleled and highly rewarding experimentation space for the mind of the individual consumer of that art. In parallel, it also provides a useful and promising device for investigating brain and cognition.

Literature Calling

Human Striatum Is Differentially Activated by Delayed, Omitted, and Immediate Registering Feedback Kohrs C, Angenstein N, Scheich H and Brechmann A. Front Hum Neurosci. 2012;6:243. doi: 10.3389/fnhum. 2012.00243 The temporal contingency of feedback during conversations is an essential requirement of a successful dialog. In the current study, we investigated the effects of delayed and omitted registering feedback on fMRI activation and compared both unexpected conditions to immediate feedback. In the majority of trials of an auditory task, participants received an immediate visual feedback which merely indicated that a button press was registered but not whether the response was correct or not. In a minority of trials, and thus unexpectedly, the feedback was omitted, or delayed by 500 ms. The results reveal a response hierarchy of activation strength in the dorsal striatum and the substantia nigra: the response to the delayed feedback was larger compared to immediate feedback and immediate feedback showed a larger activation compared to the omission of feedback. This suggests that brain regions typically involved in reward processing are also activated by non-rewarding, registering feedback. Furthermore, the comparison with immediate feedback revealed that both omitted and delayed feedback significantly modulated activity in a network of brain regions that reflects attentional demand and adjustments in cognitive and action control, i.e., the posterior medial frontal cortex (pMFC), right dorsolateral prefrontal cortex (dlPFC), bilateral anterior insula (aI), inferior frontal gyrus (Gfi), and inferior parietal lobe (Lpi). This finding emphasizes the importance of immediate feedback in human–computer interaction, as the effects of delayed feedback on brain activity in the described network seem to be similar to that of omitted feedback.

The Fuzzy Brain. Vagueness and Mapping Connec- Tivity of the Human Cerebral Cortex Haueis P. Front Neuroanat. 2012;6:37. doi: 10.3389/ fnana.2012.00037 While the past century of neuroscientific research has brought considerable progress in defining the boundaries of the human cerebral cortex, there are cases in which the demarcation of one area from another remains fuzzy. Despite the existence of clearly demarcated areas, examples of gradual transitions between areas are known since early cytoarchitectonic studies. Since multimodal anatomical approaches and functional connectivity studies brought renewed attention to the topic, a better understanding of the theoretical and methodological implications of fuzzy boundaries in brain science can be conceptually useful. This article provides a preliminary conceptual framework to understand this problem by applying philosophical theories of vagueness to three levels of neuroanatomical research. For the first two levels (cytoarchitectonics and fMRI studies), vagueness will be distinguished from other forms of uncertainty, such as imprecise measurement or ambiguous causal sources of activation. The article proceeds to discuss the implications of these levels for the anatomical study of connectivity between cortical areas. There, vagueness gets imported into connectivity studies since the network structure is dependent on the parcellation scheme and thresholds have to be used to delineate functional boundaries. Functional connectivity may introduce an additional form of vagueness, as it is an organizational principle of the brain. The article concludes by discussing what steps are appropriate to define areal boundaries more precisely.

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Functional Disconnection of Frontal Cortex and Visual Cortex in AttentionDeficit/Hyperactivity Disorder Mazaheri A, Coffey-Corina S, Mangun GR, Bekker EM, Berry AS, Corbett BA. Biol Psychiatry. 2010 Apr 1;67(7):617-23. BACKGROUND: Current pathophysiologic models of attention-deficit/hyperactivity disorder (ADHD) suggest that impaired functional connectivity within brain attention networks may contribute to the disorder. In this electroencephalographic (EEG) study, we analyzed crossfrequency amplitude correlations to investigate differences in cue-induced functional connectivity in typically developing children and children with ADHD. METHODS: Electroencephalographic activity was recorded in 25 children aged 8 to 12 years (14 with ADHD) while they performed a cross-modal attention task in which cues signaled the most likely (.75 probability) modality of an upcoming target. The power spectra of the EEG in the theta (3-5 Hz) and alpha (8-12 Hz) bands were calculated for the 1-sec interval after the cue and before the target while subjects prepared to discriminate the expected target. RESULTS: Both groups showed behavioral benefits of the predictive attentional cues, being faster and more accurate for validly cued targets (e.g., visual target preceded by a cue predicting a visual target) than to invalidly cued targets (e.g., visual target preceded by a cue predicting an auditory target); in addition, independent of cue-target validity, typical children were faster to respond overall. In the typically developing children, the alpha activity was differentially modulated by the two cues and anticorrelated with midfrontal theta activity; these EEG correlates of attentional control were not observed in the children with ADHD. CONCLUSIONS: Our findings provide neurophysiological evidence for a specific deficit in top-down attentional control in children with ADHD that is manifested as a functional disconnection between frontal and occipital cortex.

New Form of Brain Plasticity: How Social Isolation Disrupts Production ScienceDaily (Nov. 11, 2012) Animals that are socially isolated for prolonged periods make less myelin in the region of the brain responsible for complex emotional and cognitive behavior, researchers at the University at Buffalo and Mt. Sinai School of Medicine report in Nature Neuroscience online. The research sheds new light on brain plasticity, the brain's ability to adapt to environmental changes. It reveals that neurons aren't the only brain structures that undergo changes in response to an individual's environment and experience, according to one of the paper's lead authors, Karen Dietz, PhD, research scientist in the Department of Pharmacology and Toxicology in the UB School of Medicine and Biomedical Sciences. Dietz did the work while a postdoctoral researcher at Mt. Sinai School of Medicine; Jia Liu, PhD, a Mt. Sinai postdoctoral researcher, is the other lead author. The paper notes that changes in the brain's white matter, or myelin, have been seen before in psychiatric disorders, and demyelinating disorders have also had an association with depression. Recently, myelin changes were also seen in very young animals or adolescents responding to environmental changes. "This research reveals for the first time a role for myelin in adult psychiatric disorders," Dietz says. "It demonstrates that plasticity in the brain is not restricted to neurons, but actively occurs in glial cells, such as the oligodendrocytes, which produce myelin." Myelin is the crucial fatty material that wraps the axons of neurons and allows them to signal effectively. Normal nerve function is lost in demyelinating disorders, such as MS and the rare, fatal, childhood disease, Krabbe's disease. This paper reveals that the stress of social isolation disrupts the sequence in which the myelin-making cells, the oligodendrocytes, are formed. In the experiment, adult mice, normally social animals, were isolated for eight weeks to induce a depressive-like state. They were then

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introduced to a "novel" mouse, one they hadn't seen before; while mice are normally highly motivated to be social, those who had been socially isolated did not show any interest in interacting with the new mouse, a model of social avoidance and withdrawal. Brain tissue analysis of the socially isolated animals revealed significantly lower than normal levels of gene transcription for oligodendrocyte cells in the prefrontal cortex, a brain region responsible for emotional and cognitive behavior. "This research provides the first explanation of the mechanism behind how this brain plasticity occurs," says Dietz, "showing how this change in the level of social interaction of the adult animal resulted in changes in oligodendrocytes." The key change was that cellular nuclei in the prefrontal cortex contained less heterochromatin, a tightly packed form of DNA material, which is unavailable for gene expression. "This process of DNA compaction is what signifies that the oligodendrocytes have matured, allowing them to produce normal amounts of myelin," says Dietz. "We have observed in socially isolated animals that there isn't as much compaction, and the oligodendrocytes look more immature. As adults age, normally, you would see more compaction, but when social isolation interferes, there's less compaction and therefore, less myelin being made." She adds, however, that the research also showed that myelin production went back to normal after a period of social integration, suggesting that environmental intervention was sufficient to reverse the negative consequences of adult social isolation. The new paper, together with a report published earlier this year by another group showing myelin changes triggered by social isolation early in life will broaden investigations into brain plasticity, says David Dietz, PhD, one of the paper's co-authors, an assistant professor of pharmacology and toxicology at UB. In addition, adds Karen Dietz, the work has implications for future questions regarding MS and other myelin disorders. "This research suggests that maybe recovery from an MS episode might be enhanced by social interaction," she says. "This opens another avenue of investigation of how mood and myelin disorders may interact with one another." Major funding for the research came from the National Institutes of Health.

Music and Early Language Acquisition Brandt A, Gebrian M, Slevc LR. Front Psychol. 2012;3:327. doi: 10.3389/fpsyg.2012.00327 Language is typically viewed as fundamental to human intelligence. Music, while recognizedas a human universal, is often treated as an ancillary ability – one dependent on or derivative of language. In contrast, we argue that it is more productive from a developmental perspective to describe spoken language as a special type of music. A review of existing studies presents a compelling case that musical hearing and ability is essential to language acquisition. In addition, we challenge the prevailing view that music cognition matures more slowly than language and is more difficult; instead, we argue that music learning matches the speed and effort of language acquisition. We conclude that music merits a central place in our understanding of human development.

Playing "Duck Duck Goose" with Neurons: Change Detection through Connectivity Reduction Tian X, Huber DE. Psychol Sci. 2013 Jun 1;24(6):819-27. doi: 10.1177/0956797612459765. Epub 2013 Apr 9. Reduced connectivity between sending and receiving neurons (i.e., synaptic depression) may facilitate change detection by reducing responses for recently viewed objects so new objects can be highlighted. In the experiment reported here, we investigated high-level change detection following semantic satiation, which is the loss of meaning following repetition of a word. A

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Literature Calling computer simulation of a word-reading neural network with synaptic depression identified key predictions of connectivity reduction. A dynamic-causal-modeling analysis of magnetoencephalography (MEG) responses collected during a category-matching task identified connectivity reduction between a cortical region related to orthography and a cortical region related to semantics as the cause of the reduced MEG response to a repeated word. As predicted, prior repetitions of a category-matching word presented immediately after the repeated word enhanced semantic novelty, as measured with the M400 component. These results demonstrate that a combination of neural-network modeling and connectivity analyses can reveal the manner in which connectivity fluctuations underlie cognitive functions.

Small Quantities of Marijuana Protect Against Brain Damage Ephrati A. June 9th, 2013 in Health » Israel. Researchers from the Sackler Faculty of Medicine at Tel Aviv University found that a very low dose of the active ingredient in marijuana (THC) may protect brain cells before and after brain injury, and can also protect against the development of cardiac damage. The research was published in the journal Experimental Brain Research. In the last decade, numerous studies have been conducted on marijuana’s therapeutic properties. It is well known that medical cannabis is used to alleviate the suffering of people with serious diseases including cancer and post-traumatic stress disorder – helping them cope with pain, insomnia, lack of appetite and other symptoms. Professor Joseph Sarne, who is responsible for the research along with Professor Edith Hochhauser of the Felsenstein Medical Research Center, and the Rabin Medical Center, has found that a minimal dose of THC, marijuana’s psychoactive ingredient, protects the brain from longterm cognitive damage. This works to varying degrees, and protects against damage that may be caused by lack of oxygen, drug use or other complications. Triggering the brain’s natural protection In previous studies, researchers injected high doses of THC into subjects in a very short time: up to four hours before or after brain injury. Professor Sarne’s study however, shows that a small dose of THC, 1000 times smaller than the quantity found in a regular marijuana cigarette, injected into mice prevents the development of brain damage. According to him, the tiny dose activates the brain’s protective abilities, including increased neural growth that protects nerve cells in the brain, and preserves cognitive abilities over time. “This treatment is safe and effective in many cases of brain injury in humans,” he says. “Our treatment has several important benefits,” concludes Sarne. “First of all, we are considering a long-term period, which allows treating damage after it has occurred and prevents damage that could occur in the future. Additionally, due to the lower dosage, the method is also safe to use as a preventative treatment over time, and for different chronic conditions.”

Dynamics of Hippocampal Neurogenesis in Adult Humans Spalding KL, Bergmann O, Alkass K, Bernard S, Salehpour M, Huttner HB, Boström E, Westerlund I, Vial C, Buchholz B, Possnert G, Mash DC, Druid H, Frisén J. Cell. 2013;153(6);1219-27. Adult-born hippocampal neurons are important for cognitive plasticity in rodents. There is evidence for hippocampal neurogenesis in adult humans, although whether its extent is sufficient to have functional significance has been questioned. We have assessed the generation of hippocampal cells in humans by measuring the concentration of nuclear-bomb-test-derived 14C in genomic DNA, and we present an integrated model of the cell turnover dynamics. We found that a large subpopulation of hippocampal neurons constituting one-third of the neurons is subject to exchange. In adult humans, 700 new neurons are added in each hippocampus per day,

Literature Calling corresponding to an annual turnover of 1.75% of the neurons within the renewing fraction, with a modest decline during aging. We conclude that neurons are generated throughout adulthood and that the rates are comparable in middle-aged humans and mice, suggesting that adult hippocampal neurogenesis may contribute to human brain function.

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International Association of Functional Neurology and Rehabilitation and the F.R. Carrick Research Institute’s 4th Annual Conference and Awards Dinner October 10-13, 2013 Phoenix, Arizona Don’t miss out on fantastic registration specials for the 2013 event. Sign up today and take advantage of the option to put the entire conference on a payment plan!

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□ Please bill my credit card now for payment in full. Name: ________________________________________________________________________ Phone Number: _________________________________________________________________ Email Address: _________________________________________________________________ City/State/Country: ______________________________________________________________ Credit Card Number: ____________________________________ Exp Date: _______________ Billing Zip Code: ____________________ Signature: ______________________________________________________________________ Please email, fax or mail your registration IAFNR – 2487 S. Gilbert Rd #106-116, Gilbert, AZ 85296 Phone (480) 926-1115 * Fax (480) 813-1868 * Email: [email protected]

POSTER PRESENTATION REQUIREMENTS FOR 2013 ANNUAL CONFERENCE OCTOBER 10-13, 2013 PHOENIX, AZ

• Abstracts must be original and must not be or have been published or presented at any other meeting prior to the congress. • Abstracts must be submitted in English. • Abstracts must be received by the announced deadline. Abstracts received after the deadline will not be considered. • The presenting author is required to ensure that all co-authors are aware of the content of the abstract before submission. • Presenting author's contact details must be included. (Email address, postal address, daytime and evening phone number, author and co-authors' details, full first and family name(s)) Authors' names must be in upper and lower case. • Affiliation details (department, institution, hospital, city, state, country) must be included. • Abstract title must be limited to 20 words in upper case. • Abstract text must be limited to 250 words, including acknowledgements. • Abstracts should clearly state: background and aims, methods, results, conclusion. • Use only standard abbreviations. Place special or unusual abbreviations in parentheses after the full word appears the first time. Use generic names of supplements or drugs. Do not use product identifiers. Express numbers as numerals. • Case studies are of real cases and all identity to a patient must be kept confidential. Do not use names or identifying initials.

• Tables, graphs and images: • A maximum of 3 tables of up to 10 rows x 10 columns can be included per abstract. • Each image included in the abstract is worth 30 words. A maximum of 3 images can be included per abstract. • The maximum file size of each graph image is 500 kb. The maximum pixel size of the graph / image is 600(w) x 800 (h) pixel. Jpeg format only. • Full disclosure of financial relationships that the author(s) may have with the manufacturer / supplier of any commercial product or services related to the work, should be indicated on the abstract form. For example, if you use a certain product or diagnostic instrument in your case study, you must state that you have no conflict of interest or state whatever relationship you might have. • All accepted poster abstracts will be printed in the conference issue of the Journal of Functional Neurology, Rehabilitation and Ergonomics. • All abstracts must be physically AND digitally submitted to: Dr. Gerry Leisman F.R. Carrick Research Institute 2487 S. Gilbert Rd. #106-116 Gilbert, AZ 85295 Phone: (480) 926-1115 Email: [email protected] Web: www.frcarrickresearchinstitute.org

The International Association for Functional Neurology and Rehabilitation was founded in 2010 to promote, protect, and advance interdisciplinary scientific and clinical Functional Neurology and Rehabilitation Sciences at the national and international levels. We plan to be one of the fastestgrowing, most respected and diverse organizations in the field world-wide.

MEMBER BENEFITS 2013-2014 As a member of IAFNR, you will not only be voicing your commitment to the science and practice of Functional Neurology and Neurological Rehabilitation Sciences, but you will also receive the following benefits: IAFNR-Journal – Functional Neurology, Rehabilitation, and Ergonomics published by Nova Science Publishers, Inc. with Drs. Gerry Leisman and Robert Melillo as Editors-in-Chief. Stay up-to-date on the latest scientific research in Functional Neurology, as well as reports of trends in the field, special issues on pertinent topics, abstracts of the annual conference, and timely news of organizational activities. The journal will be published four times yearly. The aim and scope of this interdisciplinary journal is to provide a forum for the fields of Functional Neurology, Rehabilitation Sciences, Neuropsychology, Clinical Neurology, Human Factors and Ergonomics, and vocational assessment and training to present critical ideas, theories, proof-ofconcept for technology solutions, and data-based evaluative research to facilitate more effective functional development in children and adults. FNRE accepts review papers, articles of original research, data-based and controlled case studies pertaining to Functional Neurology, Man-Machine Interaction, Rehabilitation Sciences, brainbehavior relationships, and in applied cognitive neuroscience that relate to translational research. Engineering proof-of-concept applied to functional neurology as ergonomics are also welcome. FNRE also welcomes commentary on either the review papers or on original research as the journal intends to be an archival source of discussion of new advances in rehabilitation. IAFNR-Annual Convention – Our 4th Annual Convention in Phoenix, Arizona will take place October 10-13, 2013. Please contact us for more information and to register for the event! IAFNR-Library – APS will publish several book series, which will be available to Members at discounted prices. IAFNR-Online – The IAFNR and FNRE websites will offer a wealth of information for members, including in-press journal articles, searchable employment ads, the FNRE archive, an online membership directory available only to members, and much more.

Advocacy – Your voice will be heard through our tireless government relations work, which works with the United States Congress and federal research agencies to increase support for our research and practice interests and training. Public Affairs – IAFNR will engage the public in Functional Neurology research through social network technologies including Facebook and Twitter, our “Brain Matters” column and our “We’re Superhuman if we only tried…” weblog. These efforts will reach an unprecedented number of people around the world. We’ll let you know how many hits we get each day. Teaching – Expand your knowledge and skills through IAFNR teaching initiatives in concert with the Carrick Institute and international university programs. For more information on these and other IAFNR member benefits, please contact us via any of the following: Membership Department International Association for Functional Neurology, Rehabilitation, and Ergonomics 2487 S. Gilbert Road, Suite 106-116 Gilbert, AZ 85295 USA E-mail: [email protected] Phone: 1-480-926-1115 Fax: 1-480-813-1868

INTERNATIONAL ASSOCIATION OF FUNCTIONAL NEUROLOGY AND REHABILITATION APPLICATION FOR NEW MEMBERSHIP (Renewing & Reinstated Members: Please note any changes in contact information or education below.)

CONTACT INFORMATION Member Last Name: _________________________________________________________________ First Name: _____________________________________________________ MI: _______________ Organization/Institution/Affiliation: _____________________________________________________ Mailing Address: ___________________________________________________________________ City: _____________________________________ State: _________ Postal Code: _______________ Country: ____________________________ Email Address: _________________________________ Office Phone (Include extension): ______________________________________________________ Home Telephone: ____________________________________ Fax: __________________________ Personal Web Address: _______________________________________________________________

EDUCATION __________________________________________________________________________________ Highest Degree (in Primary Discipline) College or University Discipline Yr. of Degree __________________________________________________________________________________ Graduate Degrees College or University Discipline Yr. of Degree __________________________________________________________________________________ Other Graduate Degrees College or University Discipline Yr. of Degree __________________________________________________________________________________ Undergraduate Degrees College or University Discipline Yr. of Degree

__________________________________________________________________________________ Professional Licenses __________________________________________________________________________________ Field Jurisdiction Number Year MAJOR FIELD (Circle one) • Medicine • Chiropractic •Occupational Therapy • Law • Psychology • Physiotherapy • Engineering • Forensic Science • Basic Sciences • Optometry • Sports Science/Kinesiology • Other: ___________________________________________________ MINOR FIELD & INTERESTS (Circle all that apply) • Neurology • Neuropsychology • Physical Med. & Rehab • Mobility • Biomedical Engineering • Nutritional Sciences & Biochem. • Orthotics/Prosthetic • Other: ___________________________________________________________________________ PRACTICE/RESEARCH AREA DESCRIPTION __________________________________________________________________________________ __________________________________________________________________________________ __________________________________________________________________________________ EMPLOYMENT SECTOR (circle one) • University • Private-Practice • Hospital • 4 YR. College • Not-For-Profit • 2 Yr. College • Professional School • Research Institute • Government • Retired • Student: _________________________________________________________________________ (Where and when do you expect to graduate?) CLASS OF MEMBERSHIP FOR WHICH APPLYING [ ] Member [ ] Student Member [ ] Affiliate Member (non-professional) [ ] Fellow* [ ] Life Member+ [ ] Life Member AND Fellow+ [ ] Sustaining Member° [ ] Sustaining Member and Fellow° *Fellowship status is granted by the IAFNR in recognition of significant and sustained contribution to the field of Functional Neurology and Rehabilitation Sciences of greater than ten years. +

Life membership provides IAFNR membership at the appropriate grade of Member and/or Fellow status for life with the payment of a single membership fee indicated below and never having to pay dues, the journal subscription will be included for life. °Sustaining membership and/or fellowship is obtained by a multiyear dues payment as indicated below.

PAYMENT INFORMATION [ ] Check enclosed made payable to: International Association for Functional Neurology and Rehabilitation (IAFNR) Please Charge my: [ ] Visa [ ] MasterCard [ ] American Express Card Number: ______________________________________________________________________ Exp Date: _________________ CVV: ______________ Billing Zip Code: _____________________ Name on Card: _____________________________________________________________________ Signature: _________________________________________________________________________ OPTIONAL DONATION TO RESEARCH • Please charge my charge card $______________ in monthly installments (for donations to the F. R. Carrick Institute only-see below). MEMBERSHIP CATEGORIES [ ] 3 Year Member (through 12/31/15) $750 [ ] 2 Year Member (through 12/31/14) $500 [ ] 1 Year Member (including FNRE journal subscription) JOURNAL SUBSCRIPTION TYPE (PLEASE ONLY CHOOSE ONE) [ ] Hard Copy $295 [ ] Electronic Copy as .pdf $295 [ ] Student $175 (including Postdoc/intern/resident) [ ] Retired (Over 65) $195 [ ] Retired (No journals) $50 [ ] Spouse Member (No journals) $100 Spouse’s Name: _________________________________________________________________ [ ] Lifetime Member $5,000 [ ] Optional contribution to the F. R. Carrick Institute $ _____________________________________ (Optional contributions may be made in installments – see above) Please send your remittance to any of the following: Membership Department International Association of Functional Neurology and Rehabilitation 2487 S. Gilbert Road, Suite #106-116 Gilbert, AZ 85295, USA Fax: 1-480-813-1868 Email: [email protected]

AIM AND SCOPE OF THE JOURNAL The aim and scope of this interdisciplinary journal is to provide a forum for the fields of biomedical and rehabilitation engineering, neuropsychology, clinical neurology, human factors and ergonomics, and vocational assessment and training to present critical ideas, theories, proof-of-concept for technology solutions, and data-based evaluative research to facilitate return to work or more effective functional development in children and adults. FNRE accepts review papers, articles of original research, data-based and controlled case studies pertaining to functional neurology, man-machine interactions, rehabilitation sciences, brain-behavior relationships, and in applied cognitive neuroscience that relate to translational research. Engineering proof-of-concept applied to functional neurology as ergonomics are also welcome. FNRE also welcomes commentary on either the review papers or on original research as the journal intends to be an archival source of discussion of new advances in rehabilitation.

Description of the Fields Covered Assessment & Rehabilitation in Neurological Disorders       

Diseases and trauma of the brain Cognitive, language, motor, sensory (e.g. visual, auditory, pain, vestibular, etc) and behavioral disorders Developmental disabilities Autism in childhood and adults Diseases and trauma of the spinal cord Neuropathy, myopathy, and peripheral nerve lesions Diseases and trauma impacting on vestibular function

Assessment & Rehabilitation in Orthopedic and Musculoskeletal Disorders   

Limb disease, trauma, and amputation Rheumatic diseases; osteoporosis Back and neck pain

Assessment & Rehabilitation in Other Specific Populations   

Geriatric rehabilitation Pediatric rehabilitation Special medical conditions (e.g., heart disease; respiratory disorders; cancer; burns; vegetative state)

Topics of General Interest in P&RM Organization and management of rehabilitation services: rehabilitation in the framework of hospitalization and in the community; quality control in rehabilitation; vocational rehabilitation. Scope of the specialty: educational needs; ethical and medico-legal aspects; role for alternative/complementary medicine practices in P&RM. Functional assessment & outcome measurement at various levels: impairment; disability (activity); handicap (participation); quality-of-life (QOL); WHO-ICF system. Management of commonly encountered disabling conditions: pain; sexual disability; spasticity; postural instability & recurrent falls; wounds; sleep disorders; disability related emotional disorders. Other topics of general interest in P&RM: secondary and tertiary prevention in medical rehabilitation; nursing of disabled persons; sports medicine and sports for the disabled; rehabilitation of terror victims; electrodiagnosis; kinesiology; walking analysis; movement analysis; posturography; orthotic devices; advanced technologies in P&RM; augmentative devices; neuromuscular electrical stimulation; biofeedback; ergonomic considerations in the home and workplace of disabled persons.

Rationale for Why the Journal Is Needed The field of Rehabilitation does not presently exist as a cohesive discipline. Rehabilitation specialists define themselves as neurologists, practitioners of physical medicine and rehabilitation, vocational experts, engineers, psychologists, educators, social workers, physical therapists, occupational therapists and the like. The intrinsic cross-disciplinary nature of the rehabilitation process and the requirement for clinical-driven applied and basic science is not represented in any presently published journal, or for that matter, professional organization. The International Association of Functional Neurology and Rehabilitation and the F. R. Carrick Institute for Clinical Ergonomics, Rehabilitation, and Applied Neuroscience, the host organization and research institution for the journal FNRE, is addressing the foregoing by training interdisciplinary rehabilitation professionals whose dissertations also require patent and product development, the establishment of cross-disciplinary research laboratories and projects, the transfer of technology into community based services such as free medical equipment and services for those in need of getting to or back to work, regional clinical program integration systems, and international academic and research cooperative agreements. It is expected that the proposed journal will strongly reflect the structure and philosophy of science and practice.

Description of the Peer Review Process Papers will be solicited through the organs of fields impacting on rehabilitation science. Peer review will be performed on each paper but will be blind. Periodically, papers linking a particular cogent theme applied to rehabilitation will be compended within a single issue and published in book form. Papers will be ranked as accepted without revision, accepted but with minor revision, requiring major rework and an additional review, or rejected. We do desire to create dialogue within the rehabilitation community, and reviewer’s comments, when appropriate, will be included with the published paper.

INSTRUCTIONS FOR AUTHORS Manuscripts for the Journal of Functional Neurology, Rehabilitation, and Ergonomics (FNRE) may be submitted to the Editor-in-Chief at the F. R. Carrick Institute for Clinical Ergonomics, Rehabilitation, and Applied Neurosciences (CERAN), 647 Franklin Avenue, Garden City New York 11530 USA. Articles must also be submitted by email: to [email protected]. Type of Manuscripts Accepted FNRE accepts review papers, articles of original research, data-based and controlled case studies pertaining to Functional Neurology, Man-Machine Interaction, Rehabilitation Sciences, brainbehavior relationships, and in applied cognitive neuroscience that relate to translational research. Engineering proof-of-concept applied to functional neurology as ergonomics are also welcome. FNRE also welcomes commentary on either the review papers or on original research as the journal intends to be an archival source of discussion of new advances in rehabilitation. Manuscript Requirements [1] Manuscripts must be written in English and be typewritten with double spacing throughout the entire text and with margins of at least 2.5 cm. An original on 8½"  11" heavy duty white bond paper and two duplicate copies should be provided. An email copy as a file attachment in MS WORD for WINDOWS or a text file must also be submitted by email to the above indicated email address. [2] Each manuscript must have a title (first) page that includes the title, the authors’ full names, the laboratory or origin of the data, a running head, a list of 6-8 key words and the name, address and FAX number of the person to whom correspondence and proofs should be mailed. [3] Full length review articles should be divided into sections in the following order: Synopsis, Body (with relevant sub-headings), Acknowledgements, and References. Short notes should contain no sections. Number pages consecutively. [4] Abbreviations should be defined when first used by placing in parentheses after the full term; e.g., acetylcholin-esterase (AChE). [5] References will follow the "Uniform requirements for manuscripts submitted to biomedical journals" format (also called the Vancouver style, see http://www.icmje.org/index.html) determined by the International Committee of Medical Journal Editors and used for PubMed/Medline journals. Abbreviations of journal names should conform to the Index Medicus.

References in specific References (maximum of 25 for articles, 40 for review articles and 5 for case reports) should be cited consecutively (enclosing the number in parenthesis) in the text and listed in the same numerical order at the end of the paper. The Vancouver Style is required (http://www.icmje.org/).The first reference in the text should be (1) and the next (2) and so forth and then listed accordingly at the end of the paper after discussion or after acknowledgements. Examples: Journal article Damianopoulos EN, Carey RJ. Pavlovian conditioning of CNS drug effects: a critical review and new experimental design. Rev Neurosci 1992; 3: 65-77. Note: no comma in between name an initials, no italics or bold, no capitol letters in title except at the begining of sentence, no period between jorunal name and year, year;vol:page-page without space betwwen and last page number shortened. All authors must be cited. Journal name abbreviated according to the international standard found at PubMed Journal Database. (http://www.ncbi.nlm.nih.gov/sites/entrez?db=journals) Book Melillo R, Leisman G Neurobehavioral disorders of childhood: An evolutionary approach. New York: Kluwer, 2004. Book chapter Leisman G, Melillo R. Cortical asymmetry and learning efficiency: A direction for the rehabilitation process. In: Randall SV Learning disabilities: New research. Hauppauge, NY: Nova. 2006: 1-24. Research report Shek DTL. A positive youth development program in Hong Kong. Hong Kong: Soc Welfare Pract Res Centre, Univ Hong Kong, 2004. (Chinese) Unpublished thesis Kaplan SJ. Post-hospital home health care: The elderly’s access and utilization. Dissertation. St Louis: MO: Washington Univ, 1995. Internet materials / publication Internet journal: Morse SS. Factors in the emergence of infectious diseases. Emer Infect Dis 2006;5:1. Internet material Morse SS. Factors in the emergence of infectious diseases. Emer Infect Dis 2006. Accessed 2007 Jun 05. URL: http://www.cdc.gov/ncidod/EID/eid.htm [6] Case studies. FNRE will publish limited case-study material as long as the appropriate format is followed including the format for references, figures and tables. The conclusions must be supportable by laboratory-based evidence presented within the case study. The authors of case study material are strongly encouraged to study the following websites that may be useful in increasing the likelihood of the material being published (e.g. http://www.bgfl.org/bgfl/18.cfm?s=18&m=473&p=261,index or http://www.bmhlinguistics.org/joomla2/guidelines-for-writing-case-studies). [7] Copyright responsibility. This is the author’s own responsibility. If any figure(s), illustration(s), table(s) or extended quotation(s) etc. are to be taken from material(s) previously published, the author(s) must secure reproduction permission from the copyright owner. Only original papers will be accepted, and copyright of published papers will be retained by the publisher.

[8] Transfer of author copyright. Please include a signed release of copyright to Nova Publishers with your manuscript. Include the title of the article being sub-mitted, as well as the date. Include the signatures of co-authors. [9] Manuscript editing. All accepted manuscripts are subject to manuscript editing. [10] The original manuscript and diagrams will be discarded one month after publication unless there is a written request for the material to be returned to the author. Indexed and abstracted by: The journal will be indexed and abstracted by BIOSIS, EMBASE/Excerpta Medica, Index Medicus, Neuroscience Citation Index, Reference Update, Research Alert, IEEE/EMBS. Conflict-of-Interest Statement Public trust in the peer review process and the credibility of published articles depend in part on how well conflict of interest is handled during writing, peer review, and editorial decision making. Conflict of interest exists when an author (or the author's institution), reviewer, or editor has financial or personal relationships that inappropriately influence (bias) his or her actions (such relationships are also known as dual commitments, competing interests, or competing loyalties). These relationships vary from those with negligible potential to those with great potential to influence judgment, and not all relationships represent true conflict of interest. The potential for conflict of interest can exist whether or not an individual believes that the relationship affects his or her scientific judgment. Financial relationships (such as employment, consultancies, stock ownership, honoraria, paid expert testimony) are the most easily identifiable conflicts of interest and the most likely to undermine the credibility of the journal, the authors, and of science itself. However, conflicts can occur for other reasons, such as personal relationships, academic competition, and intellectual passion. - International Committee of Medical Journal Editors ("Uniform Requirements for Manuscripts Submitted to Biomedical Journals") - February 2006 Functional Neurology, Rehabilitation, and Ergonomics requires all authors and reviewers to declare any conflict of interest that may be inherent in their submissions. Statement of Informed Consent Patients have a right to privacy that should not be infringed without informed consent. Identifying information, including patients' names, initials, or hospital numbers, should not be published in written descriptions, photographs, and pedigrees unless the information is essential for scientific purposes and the patient (or parent or guardian) gives written informed consent for publication. Informed consent for this purpose requires that a patient who is identifiable be shown the manuscript to be published. Authors should identify Individuals who provide writing assistance and disclose the funding source for this assistance. Identifying details should be omitted if they are not essential. Complete anonymity is difficult to achieve, however, and informed consent should be obtained if there is any doubt. For example, masking the eye region in photographs of patients is inadequate protection of anonymity. If identifying characteristics are altered to protect anonymity, such as in genetic pedigrees, authors should provide assurance that alterations do not distort scientific meaning and editors should so note. - International Committee of Medical Journal Editors ("Uniform Requirements for Manuscripts Submitted to Biomedical Journals"_ - February 2006 Statement of Human and Animal Rights When reporting experiments on human subjects, authors should indicate whether the procedures followed were in accordance with the ethical standards of the responsible committee on human

experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000 (5). If doubt exists whether the research was conducted in accordance with the Helsinki Declaration, the authors must explain the rationale for their approach, and demonstrate that the institutional review body explicitly approved the doubtful aspects of the study. When reporting experiments on animals, authors should be asked to indicate whether the institutional and national guide for the care and use of laboratory animals was followed. - International Committee of Medical Journal Editors ("Uniform Requirements for Manuscripts Submitted to Biomedical Journals") - February 2006

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Back pain

Fitzsimmons RJ, et al. PEMF increases human chondrocyte proliferation through a transduction pathway involving NO signaling. J Orthop Res. 2008, Jun;26(6):854-9.

Marks RA. Spine fusion for discogenic low back pain: outcomes in patients treated with or without PEMF. Adv Ther. 2000 Mar-Apr;17(2):57-67.

Autoimmunity modulation

Jorgensen WA, et al. Electrochemical therapy of pelvic pain: effects of PEMF on tissue trauma. Eur J Surg Suppl. 1994;(574):83-6.

Nindl G, et al. Experiments showing that electromagnetic fields can be used to treat inflammatory diseases. Biomed Sci Instrum. 2000;36:7-13.

Migraines

Pain

Bone healing

Pelka RB, et al. PEMF for migraine and other headaches: a double-blind, placebo-controlled study. Adv Ther. 2001 May-Jun;18(3):101-9.

Chang K, et al. Effects of different intensities of extremely low frequency PEMFs on formation of osteoclast-like cells. Bioelectromagnetics. 2003 Sep;24(6):431-9.

Depression

Wound healing

Sandyk R. Suicidal behavior is attenuated in patients with multiple sclerosis by treatment with electromagnetic fields. Int J Neurosci. 1996 Oct;87(1-2):5-15.

Patiño O, et al. [Effect of magnetic fields on skin wound healing. Experimenta study]. Medicina (B Aires). 1996;56(1):41-4.

Balance

Lappin MS, et al. Effects of PEMF therapy on multiple sclerosis fatigue and quality of life: a double-blind, placebo controlled trial. Altern Ther Health Med. 2003 Jul-Aug;9(4):38-48.

Thomas AW, et al. Human subjects exposed to a specific (200 microT) PEMFs: effects on normal standing balance. Neurosci Lett. 2001 Jan 12;297(2):121-4.

Neurodegenerative disrorders Sandyk R. Reversal of an acute Parkinsonian syndrome associated with multiple sclerosis by application of weak electromagnetic fields. Int J Neurosci. 1996 Jul;86(1-2):33-45.

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Functional Neurology, Rehabilitation, and Ergonomics

Functional Neurology, Rehabilitation, and Ergonomics

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