Attention and Working Memory-Related EEG Markers of ... - IOS Press

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Journal of Alzheimer’s Disease 47 (2015) 335–349 DOI 10.3233/JAD-150111 IOS Press

Attention and Working Memory-Related EEG Markers of Subtle Cognitive Deterioration in Healthy Elderly Individuals Marie-Pierre Deibera,b,∗ , Hadj Boumediene Mezianeb , Roland Haslerb , Cristelle Rodriguezc , Simona Tomac , Marine Ackermannc , François Herrmannd and Panteleimon Giannakopoulosc a INSERM

U1039, Faculty of Medicine, La Tronche, France of Vulnerability Unit, Department of Mental Health and Psychiatry, University Hospitals of Geneva, Geneva, Switzerland c Division of General Psychiatry, Department of Mental Health and Psychiatry, University Hospitals of Geneva, Geneva, Switzerland d Division of Geriatrics, Department of Internal Medicine, Rehabilitation and Geriatrics, University Hospitals of Geneva, Geneva, Switzerland b Biomarkers

Accepted 16 April 2015

Abstract. Future treatments of Alzheimer’s disease need the identification of cases at high risk at the preclinical stage of the disease before the development of irreversible structural damage. We investigated here whether subtle cognitive deterioration in a population of healthy elderly individuals could be predicted by EEG signals at baseline under cognitive activation. Continuous EEG was recorded in 97 elderly control subjects and 45 age-matched mild cognitive impairment (MCI) cases during a simple attentional and a 2-back working memory task. Upon 18-month neuropsychological follow-up, the final sample included 55 stable (sCON) and 42 deteriorated (dCON) controls. We examined the P1, N1, P3, and PNwm event-related components as well as the oscillatory activities in the theta (4–7 Hz), alpha (8–13 Hz), and beta (14–25 Hz) frequency ranges (ERD/ERS: event-related desynchronization/synchronization, and ITC: inter-trial coherence). Behavioral performance, P1, and N1 components were comparable in all groups. The P3, PNwm, and all oscillatory activity indices were altered in MCI cases compared to controls. Only three EEG indices distinguished the two control groups: alpha and beta ERD (dCON > sCON) and beta ITC (dCON < sCON). These findings show that subtle cognitive deterioration has no impact on EEG indices associated with perception, discrimination, and working memory processes but mostly affects attention, resulting in an enhanced recruitment of attentional resources. In addition, cognitive decline alters neural firing synchronization at high frequencies (14–25 Hz) at early stages, and possibly affects lower frequencies (4–13 Hz) only at more severe stages. Keywords: Alzheimer’s disease, attention, brain waves, cognitive decline, EEG, EEG phase synchronization, working memory

INTRODUCTION Curative interventions in Alzheimer’s disease (AD) could gain in success if applied at the preclinical phase, to either counterbalance the deleterious effects of ∗ Correspondence

to: Marie-Pierre Deiber, Biomarkers of Vulnerability Unit, Department of Mental Health and Psychiatry, Belle-Idée, Chemin du Petit-Bel-Air 2, 1225 Chêne-Bourg, Geneva, Switzerland. Tel.: +41 22 305 53 80; Fax: +41 22 305 53 50; E-mail: [email protected].

amyloid deposition and neurodegeneration preceding the clinically overt cognitive decline, or promote functional compensation ([1] for review). Preclinical AD is a recent concept designing cases with progressive installation of pathological processes in the absence of overt clinical signs of dementia ([2] for review). These cognitively intact elderly individuals who usually display increased amyloid burden in positron emission tomography (PET) scans and decreased amyloidbeta 42 (A␤42 ) concentration in cerebrospinal fluid

ISSN 1387-2877/15/$35.00 © 2015 – IOS Press and the authors. All rights reserved

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M.-P. Deiber et al. / EEG Markers of Early Cognitive Deterioration

(CSF) remain cognitively stable for variable time periods but ultimately present significantly increased risk for AD [3]. Pointing to the difficulty to identify cases at high risk of AD among this heterogeneous group, a 5-year follow-up of healthy elderly showed that more than 60% have a stable memory trajectory, 31% display subtle memory decline, and only 4% progress to mild cognitive impairment (MCI) [4]. Both markers of A␤ accumulation (decreased levels of CSF A␤42 , positive PET amyloid imaging) and neurodegeneration (increased CSF t-tau and p-tau, increased hippocampal atrophy or cortical thinning) have been shown to be associated with elevated rates of cognitive decline in preclinical AD [5, 6]. However, the identification of progressors among preclinical AD cases implies invasive investigations hard to perform in routine clinical settings. Unlike PET and lumbar puncture, EEG is a non-invasive and low-cost approach increasingly used in the characterization of MCI and AD since it can examine with maximal temporal resolution multistage cerebral functions potentially affected in neurodegenerative processes [7–9]. The EEG activity recorded during cognitive tasks may provide information on early phases of AD processes with better reliability than resting state patterns, which are more susceptible to intra- and inter-individual variability [10–12]. Significant differences in event-related potentials (ERPs) and oscillatory responses during working memory performance between MCI and healthy controls have been repeatedly documented ([9] for review). Using working memory n-back tasks, our group described a PNwm event-related component sensitive to memory load which absence at baseline in MCI patients predicted cognitive deterioration at 1 year [13]. In addition, frontal induced theta response was significantly reduced at baseline in progressive MCI as compared to both stable MCI and controls [14], suggesting altered top-down attentional control [15]. Alpha and beta frequency ranges have also been reported to be sensitive to early functional impairment in working memory tasks [10, 11, 16–18]. The co-existence of regional increases and decreases of frequency-specific activities recently reported during a continuous recognition task suggests a compensation/dysfunction duality of oscillatory brain responses in MCI [19]. It also points out the importance of analyzing complementary parameters that may improve the characterization of pathological processes. Beside amplitude, a fundamental feature of oscillatory activities is their temporal dynamics, or how they synchronize to enable the emergence of pertinent behavior and cognition [20, 21]. The phase synchro-

nization of brain signals can be studied over distinct electrodes, providing information about local and distant functional connections, or across trials at single electrodes, reflecting temporal coordination of neural activity related to stimulus processing [22–24]. A reduction of local and distant synchronization in MCI and AD patients as compared to controls has been described in different frequency bands at rest [25–30] and during working memory tasks [31, 32], supporting the hypothesis of functional disconnection between cortical regions [28, 29, 33]. In contrast to corticocortical synchronization, little is known about the inter-trial synchronization of activities in AD pathology that reflects the quality of neural firing associated with stimulus encoding and processing [23]. Inter-trial coherence (ITC) was examined in only one visual oddball paradigm study, showing a tendency for lower phase-locking in the beta frequency range in MCI cases compared to age-matched controls [34]. As far as preclinical AD is concerned, EEG studies are limited to a recent contribution reporting altered congruous word repetition ERP effect in this condition compared to controls who remained cognitively stable over time [35]. The current investigation tests the hypothesis that EEG signals associated with selective attention and working memory may detect very early and subtle alterations in cortical network function at baseline visit in cognitively intact elderly individuals, in order to identify initial phases of subsequent cognitive deterioration. Elderly participants were classified based on neuropsychological follow-up at 18 months into stable (sCON) and deteriorating (dCON) controls and additionally compared to a group of MCI patients. The EEG was recorded at baseline during performance of a simple detection task and a 2-back working memory task. Different aspects of the stimulus-locked EEG signal were examined, namely the visual ERPs and the derived PNwm component, the event-related spectral power (ERSP) and the ITC in the theta, alpha and beta frequency bands obtained using time-frequency analysis.

MATERIALS AND METHODS Participants Participants were contacted via advertisements in local media to guarantee a community-based sample. After detailed information about the research was provided, telephone screening was performed with the


following inclusion criteria: normal or corrected-tonormal visual acuity; no history of major medical disorders (neoplasm, cardiovascular disorders, infectious diseases), sustained head injury, or psychiatric or neurologic disorders; no alcohol or drug abuse; no regular use of neuroleptics, antidepressants, mood stabilizers, anticonvulsant drugs, or psychostimulants. To control for the confounding effect of cerebrovascular diseases, patients with subtle cardiovascular symptoms and a history of stroke or transient ischemic episodes were not included in the present study. The local ethics committee (University Hospitals of Geneva) approved this prospective study, and all participants gave written informed consent prior to inclusion. At baseline, all individuals underwent neuropsychological assessment. The control participants were evaluated with an extensive neuropsychological battery, including the Mini-Mental State Examination (MMSE) [36], the Hospital Anxiety and Depression Scale (HAD) [37], and the Lawton Instrumental Activities of Daily Living (IADL) [38]. Cognitive assessment included (a) attention (Code [39], Trail Making Test A [40]), (b) working memory (verbal: Digit Span Forward [39], visuospatial: Visual Memory Span (Corsi) [39]), (c) episodic memory (verbal: RI-48 Cued Recall Test [41]; visual: Shapes test [42]; (d) executive functions: Trail Making Test B [40], Wisconsin Card Sorting Test [43], and Phonemic Verbal Fluency test [44], (e) language (Boston Naming [45]), (f) visual gnosis (Ghent Overlapping Figures [46]), (g) praxis: ideomotor [47], reflexive [48], and constructional (Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) Figures copy [49]). Education level was defined according to the Swiss scholar system, as follows: level 1, less than 9 years (primary school); level 2, between 9 and 12 years (high school); and level 3, more than 12 years (university). All individuals were also evaluated with the Clinical Dementia Rating scale (CDR) [50], and only cases with a CDR score of 0 and scores within 1.5 standard deviations of the age-appropriate mean in all other tests were included in the control group. The MCI condition was confirmed with a shortened battery that included the MMSE, HAD, and IADL. The cognitive assessment included (a) attention (Trail Making Test A), (b) working memory (verbal, Digit Span Forward), (c) episodic memory (verbal, RI-48 Cued Recall Test and RL/RI-16 Free and Cued Recall Test [51]), (d) executive functions (Trail Making Test B and Phonemic Verbal Fluency test), (e) language (Boston Naming) and (f) constructional praxis (CERAD). All individuals were also evaluated with the

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CDR scale [50]. In agreement with the criteria of [52], participants with a CDR score of 0.5 but no dementia and a score more than 1.5 standard deviations below the age-appropriate mean in any of the previously mentioned tests were confirmed to have MCI. Eighteen months after the baseline evaluation, only control subjects underwent cognitive reassessment with the same neuropsychological battery. Participants were placed in the dCON group at follow-up if they had a performance 0.5 standard deviation lower than that at inclusion for two or more neuropsychological tests. All individuals were clinically assessed independently by two neuropsychologists (ST, MA: 4 and 2 years of experience, respectively). The final classification of dCON was made blindly by a trained neuropsychologist (CR: 10 years of experience) who took into account both the neuropsychological test results and clinical assessment. Within the dCON group, only the more severe cases corresponding to multiple-domain amnestic MCI subtype [52] were retained for further EEG analysis. The final sample included 55 individuals in the sCON group (mean age, 73.7 years ± 4.2, 33 female), 42 in the dCON group (73.7 years ± 3.5, 30 female), and 45 in the MCI group (75.3 years ± 4.7, 15 female) (Table 1). Procedure The participants, comfortably seated, watched a computer-controlled display screen at a distance of 57 cm. They viewed pseudo-random sequences of consonant and vowels common to the French alphabet, and pressed a computer-controlled button with their right index finger as soon as a target appeared (response trials). For non-target stimuli, no motor response was required (no-response trials). Stimuli consisted of white letters, Arial font (2◦ × 2.5◦ visual angle), with 10% grey noise, embedded in a 50% random noise grey rectangular background patch (6◦ × 6.7◦ visual angle). They were presented in the center of the screen for 0.5 s, separated by 4 s intervals (onset to onset) during which a dot helped subjects maintain fixation. Two cognitive tasks were tested, in which one third of the stimuli were targets. In the detection task, sequential letters (non-target) or background patches without letters (target) were presented. In the working memory 2-back task, the target was any letter that was identical to the one presented two trials back. Each task was tested in three blocks composed of 30 sequential stimuli each, adding up to 90 trials per task (21 response trials, 69 no-response trials). Reaction

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M.-P. Deiber et al. / EEG Markers of Early Cognitive Deterioration Table 1 Demographic, clinical, and neuropsychological data at inclusion

n Age Gender (F/M) Education∗ MMSE IADL HAD Total HAD Anxiety HAD Depression Digit Span Forward RI-48 (Buschke) Total immediate cued recall Total cued recall Intrusions Boston Naming Constructional praxies (CERAD) Verbal Fluency Trail A Time (s) Trail A Error Trail B Time (s) Trail B Error Trail B/A Code WCST Completed categories WCST Error Shapes test Praxies Ideomotor transitive Ideomotor intransitive Reflexive Visual gnosis (Ghent) Visual Memory Span Forward (Corsi)

sCON

Mean ± SD dCON

MCI

55 73.7 ± 4.2 33/22 2.4 ± 0.6 29 ± 1.11 8.5 ± 1.05 5.9 ± 3.5 4.4 ± 2.66 1.5 ± 1.55 6.5 ± 1.99

42 73.7 ± 3.44 30/12 2.0 ± 0.58 28.5 ± 1.04 8.1 ± 0.32 6.8 ± 4.22 4.9 ± 3.06 1.8 ± 1.97 6.5 ± 1.40

45 75.3 ± 4.72 15/30 2.2 ± 0.68 27.3 ± 2.15 9.2 ± 1.82 6.9 ± 4.34 4.3 ± 3.07 2.6 ± 2.12 6.4 ± 1.78

40.3 ± 4.68 27.4 ± 5.16 2.2 ± 2.23 19.5 ± 0.83 10.9 ± 0.57 24.0 ± 6.0 44.2 ± 19.81 0.04 ± 0.19 95.2 ± 31.39 0.47 ± 0.60 2.32 ± 0.69 55.1 ± 11.94 5.3 ± 1.43 0.31 ± 0.73 11.5 ± 0.96

39.0 ± 4.35 36.5 ± 5.52 28.0 ± 4.49 15.9 ± 3.36 2.2 ± 3.01 4.1 ± 5.59 19.4 ± 0.76 13.5 ± 1.20 10.7 ± 0.75 10.7 ± 0.63 21.8 ± 5.74 18.7 ± 6.73 42.8 ± 10.71 43.2 ± 14.05 0.0 ± 0.0 0.13 ± 0.40 98.2 ± 28.19 126.6 ± 74.01 0.36 ± 0.58 0.47 ± 0.92 2.37 ± 0.74 3.07 ± 1.66 52.7 ± 9.72 5.3 ± 1.58 0.35 ± 0.77 11.4 ± 1.36

0.004 0.001 0.016 0.001 0.277 0.001 0.878 0.654 0.023 0.436 0.052 0.302 0.847 0.786 0.708

9.4 ± 0.89 19.7 ± 1.02 7.0 ± 0.84 5.0 ± 0.1 4.8 ± 1.38

9.0 ± 1.31 19.7 ± 0.68 7.1 ± 1.18 5.0 ± 0.0 5.05 ± 1.31

0.202 0.438 0.395 0.382 0.203

KruskalAdjusted Pairwise Contrasts Wallis sCON sCON dCON p-value versus dCON versus MCI versus MCI 0.127 0.001† 0.021 0.001 0.001 0.534 0.570 0.033 0.945

0.01

0.01

0.001 0.001

0.01 0.001

0.007

0.007

0.001 0.001 0.001

0.001 0.003 0.001

0.001

0.004

Data are means ± SD. Statistics: Kruskal-Wallis non-parametric test. † Chi square test. Adjusted pairwise contrasts carried out when main effect of group is significant. ∗ Education: level 1: ≤9 years; level 2: 9 to 12 years; level 3: >12 years. MCI, mild cognitive impairment; sCON, stable controls; dCON, deteriorated controls; F, female; M, male; MMSE, Mini-Mental State examination; IADL, Lawton’s Instrumental Activities of Daily Living; HAD, Hospital Anxiety and Depression scale (cut off is 8 for both anxiety and depression); CERAD, Consortium to Establish a Registry for Alzheimer’s Disease; WCST, Wisconsin Card Sorting Test.

time and performance were systematically recorded, but no feedback on performance was provided. The experimental procedure has been described in detail elsewhere [11, 14]. Electrophysiological recordings Continuous EEG was recorded using 30 surface electrodes mounted on a cap (NeuroScan Quick Cap) and referenced to the linked earlobes. Electrode impedances were kept below 5 k. Electrophysiological signals were sampled at 1000 Hz with lower cutoff at 0.05 Hz and upper cutoff at 200 Hz (DC amplifiers and software by NeuroScan, Texas, USA). The electrooculogram was recorded using two pairs of bipolar electrodes in both vertical and horizontal

directions. Stimulus delivery and response recording, monitored using E-Prime (Psychology Software Tools, Pittsburgh, Pa., USA), were automatically documented with markers in the continuous EEG file, which were used off-line to segment the continuous EEG data into epochs time-locked to stimulus onset.

Data processing Behavioral data Reaction time (RT) was measured as the time interval between target onset and response button press. Accuracy was defined as the percentage of correct responses.


EEG data EEG analysis was conducted with Brain Vision Analyzer 2 software (Brain Products GmbH). Independent component analysis was used to identify vertical and horizontal ocular artifacts and to remove them from the signal [53]. Surface Laplacian estimation was performed on continuous EEG, reducing head volume conduction and canceling out the reference electrode influence [54]. The Laplacian-transformed EEG signal was segmented into epochs of 5500 ms, starting 1500 ms before stimulus onset. Epochs with voltage step above 50 ␮V or peak-to-peak signal deflection exceeding 200 ␮V within 300 ms intervals were automatically rejected. Only data corresponding to correct answers without motor response were analyzed. Event-related potentials: ERPs were obtained by stimulus-locked averaging of the signal with a 200 ms pre-stimulus baseline correction. Data were filtered between 0.05 Hz and 30 Hz (−48 dB/octave). The peak latency and amplitude of the P1, N1, and P3 ERP components were measured on the culmination electrodes identified in the grand-average waveforms (Oz for P1, P3 for N1, Pz for P3). The PNwm component was obtained by subtracting the stimulus-locked signal in the detection task from the 2-back task, and measured at its maximal amplitude over 3 mesial electrodes (Fz, Cz, Pz) [13]. Event-related spectral power (ERSP): To detect and characterize the event-related EEG oscillations whose latency and frequency ranges are not known a priori, a time-frequency (TF) analysis based on a continuous wavelet transformation of the signal was applied (complex Morlet’s wavelets) [55]. This analysis was performed between 4 to 30 Hz in 1-Hz steps. The resulting dataset consisted in a TF representation of the energy of the signal, from which frequency specific ERSP can be extracted. A baseline level of TF energy was calculated as the mean energy between 1000 and 150 ms before stimulus onset and subtracted from the TF energy of the entire 5500 ms epoch. Analysis was performed in the theta (4–7 Hz), alpha (8–13 Hz), and beta (14–25 Hz) frequency bands. Active cerebral processing of the stimulus is reflected in the theta range by an early increase of ERSP relative to the baseline level, or event-related synchronization (ERS), and in the alpha and beta ranges by a subsequent decrease of ERSP relative to baseline, or event-related desynchronization (ERD) [56]. Inter-trial coherence: ITC is a time-frequency domain measure of event-related phase locking across trials, also referred to as phase-locking factor. ITC values

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range from 0 to 1, with higher values indicating higher coherence of the phase of oscillations across trials [20, 57]. The ITC, closely time-locked to the stimulus and independent of power amplitude changes, was calculated using EEGLAB at single electrodes as follows ([58], newtimef.m function): For i = 1 to N trials, N 1 ITC(t, f ) = (1) ejφi (t,f ) N i=1

where φi (t, f ) is the phase of the wavelet at time t and frequency f. ITC analysis was performed in the theta (4–7 Hz), alpha (8–13 Hz) and beta (14–25 Hz) frequency bands. Statistical analysis All statistical analyses were performed using Stata software (StataCorp., 2013). Demographic, clinical, and neuropsychological data They were compared at baseline across the three cognitive groups using the Kruskal-Wallis nonparametric test. Post-hoc pairwise comparisons for sCON versus dCON, sCON versus MCI, and dCON versus MCI were performed using Dunnett’s multiple comparison tests. Gender differences were assessed using Chi-square test. Behavioral and ERP data RT and accuracy (% of correct responses), as well as latency and amplitude of ERP components were compared across cognitive groups and tasks using a repeated-measures ANCOVA with 2-level TASK (detection, 2-back) as within-subject and 3-level GROUP (sCON, dCON, MCI) as between-subject factors, while controlling for gender, education level, and HAD depression scores (see Results). The PNwm amplitude was compared across the three cognitive groups using a repeated-measures ANCOVA with 3-level ELECTRODE (Fz, Cz, Pz) as within-subject and 3-level GROUP (sCON, dCON, MCI) as betweensubject factors, with adjustment for gender, education level and HAD depression scores. ERSP and ITC ERSP and ITC were separately analyzed within the theta (4–7 Hz), alpha (8–13 Hz), and beta (14–25 Hz) frequency bands over the 9 most posterior electrode sites where their amplitude was maximal: CP3, CPz,

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Fig. 1. Mean and standard deviation values of reaction time (ms) and accuracy (percentage of correct responses) in each group for each task. ∗∗∗ p < 0.001 (task effect).

CP4, P3, Pz, P4, O1, Oz, O2. As observed from the TF plots of grand averaged responses (Fig. 3), the ERSP time course showed an initial theta ERS of around 500 ms duration, followed after 100 ms by an alpha and a beta ERD of around 600 ms duration. Therefore, analysis of theta ERS was performed on the mean theta power between 0 and 500 ms, while analysis of alpha and beta ERD was performed on the mean power between 100 and 700 ms in the alpha and beta band, respectively. ERSP in the theta, alpha and beta frequency ranges were compared across cognitive groups and tasks using a repeated-measures ANCOVA with 2-level TASK (detection, 2-back) and 9-level ELECTRODE (CP3, CPz, CP4, P3, Pz, P4, O1, Oz, O2) as within-subject, and 3-level GROUP (sCON, dCON, MCI) as between-subject factors, while controlling for gender, education level, and HAD depression scores. For analysis of ITC, peak values were extracted for each frequency band within the first 300 ms following stimulus onset. As for ERSP, ITC was compared across groups and tasks using a repeated-measures ANCOVA with 2-level TASK and 9-level ELECTRODE as within-subject, and 3-level GROUP as between-subject factors, while controlling for gender, education level, and HAD depression scores. For all ANCOVA-tested variables, statistical threshold was set at p < 0.05 after Huynh-Feldt correction for nonsphericity when appropriate. Post-hoc analysis used t-tests with p < 0.05 as significance threshold after Bonferroni correction for multiple comparisons. RESULTS Neuropsychological data Demographic, clinical, and neuropsychological data are presented in Table 1. Since gender, education, and

HAD depression scores differed significantly between groups, behavioral and EEG measures were controlled for these variables in subsequent statistical analyses. No significant difference in clinical and neuropsychological scores was found between sCON and dCON at baseline. In contrast, consistent with the definition of MCI, the MCI cases differed significantly from the two control groups in the following tests: MMSE, IADL, RI-48, Boston Naming, Verbal fluency, and Trail Making Test B (time).

Behavioral results The mean RT and accuracy data are presented in Fig. 1. Only a main effect of task was observed (RT: F(1,140) = 160.1, p < 0.001; accuracy: F(1,140) = 130.0, p < 0.001), performance being faster and more accurate in the detection than 2-back task. No differences were found in RT and accuracy values between the three diagnostic groups.

ERPs (P1, N1, P3, PNwm) The grand average ERPs are displayed in Fig. 2. P1 and N1 components did not differ across group or task. There was a main group effect on P3 amplitude (F(2,280) = 3.9, p < 0.05), with smaller values in MCI compared to both control groups. A main task effect was also observed on P3 amplitude (F(1,140) = 28.1, p < 0.001), with larger values in the 2-back than detection task. A main group effect was observed on PNwm (F(2,280) = 3.7, p < 0.05), with no significant difference between sCON and dCON, but smaller amplitude in MCI than sCON (t = −3.8, p < 0.001) (Fig. 2).


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Fig. 2. Grand average event-related potentials (ERPs) on midline electrodes Fz, Cz, Pz, and Oz, superimposed for each group, stratified by condition (left column: 2-back, middle column: detection, right column: difference 2-back – detection). Significant amplitude reduction is observed for P3 and PNwm components in the MCI group (see text for details).

Event-Related Spectral Power (ERSP) The ERSP and ITC plots are displayed on representative O2 electrode in Fig. 3 for each task and group. In both tasks, stimulus presentation elicited a transient

increase of theta power (ERS) followed by a decrease of alpha and beta power (ERD). The ITC showed a transient increase in the three frequency bands following stimulus presentation. Figure 4 illustrates the ERSP topographic maps in each group, task and frequency

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Fig. 3. Time-frequency representation of relative activity at O2 electrode in each group and task. A) Event-related spectral power (ERSP, ␮V2 ), B) Inter-trial coherence (ITC, score between 0 and 1). Stimulus onset at t = 0.

band. Figure 6A shows the mean ERSP values pooled across tasks and electrodes in each frequency band, illustrating the group effects. Theta ERS (4–7 Hz) The repeated-measures ANCOVA revealed a main effect of group (F(2,280) = 13.0, p < 0.001) and electrode (F(8,1120) = 11.0, p < 0.001). Post hoc analysis showed that theta ERS was smaller in MCI than sCON (t = −3.03, p < 0.005), but there was no significant difference between the two control groups (Fig. 6A). Theta ERS was larger over lateral parietal electrodes (Comparison with P3: Pz: t = 3.5, p < 0.005; CP3: t = 6.0, p < 0.001; CPz: t = 5.6, p < 0.001; CP4: t = 6.1, p < 0.001; O2: t = 3.4, p < 0.01. Comparison with P4: Pz: t = 3.8, p < 0.001; CP3: t = 6.3, p < 0.001; CPz: t = 5.9, p < 0.001; CP4: t = 6.4, p < 0.001; O1: t = 2.9, p < 0.05; O2: t = 3.7, p < 0.005). Alpha ERD (8–13 Hz) The repeated-measures ANCOVA revealed a main effect of group (F(2,280) = 28.8, p < 0.001) and electrode

(F(8,1120) = 15.9, p < 0.001). Post hoc analysis showed that alpha ERD was smaller in sCON than dCON (t = −5.6, p < 0.001) and MCI (t = −5.2, p < 0.001), with no significant difference between dCON and MCI groups (Fig. 6A). Alpha ERD was larger over the right parietal electrode (P4), the amplitude difference being significant as compared to all other electrodes (P3: t = 2.8, p < 0.05; Pz: t = 2.9, p < 0.05; CP3: t = 5.3, p < 0.001; CPz: t = 7.2, p < 0.001; CP4: t = 3.4, p < 0.005; O1: t = 8.6, p < 0.001; Oz: t = 7.5, p < 0.001; O2: t = 7.7, p < 0.001). Beta ERD (14–25 Hz) The repeated-measures ANCOVA revealed a main effect of group (F(2,280) = 10.6, p < 0.001) and electrode (F(8,1120) = 10.6, p < 0.001). Post hoc analysis showed that beta ERD was smaller in sCON and MCI than in dCON (sCON versus dCON: t = −2.3, p < 0.05; MCI versus dCON t = −3.4, p < 0.001) (Fig. 6A). Beta ERD was larger at lateral parietal (Comparison with P3: CPz: t = 3.7, p < 0.005; O1: t = 6.2, p < 0.001; Oz: t = 4.9,


Fig. 4. Spatial distribution of grand average ERSP (␮V2 ) in each group and task, for each frequency band. Theta (4–7 Hz; 0–500 ms), Alpha (8–13 Hz; 100–700 ms), and Beta (14–25 Hz; 100–700 ms).

p < 0.001; O2: t = 5.2, p < 0.001. Comparison with P4: CPz: t = 4.7, p < 0.001; O1: t = 7.2, p < 0.001; Oz: t = 5.9, p < 0.001; O2: t = 6.1, p < 0.001) and centroparietal electrodes (Comparison with CP3: CPz: t = 3.2, p < 0.01; O1: t = 5.7, p < 0.001; Oz: t = 4.5, p < 0.001; O2: t = 4.7, p < 0.001. Comparison with CP4: CPz: t = 2.9, p < 0.05; O1: t = 5.4, p < 0.001; Oz: t = 4.1, p < 0.001; O2: t = 4.3, p < 0.001). Inter-Trial Coherence (ITC) Figure 5 illustrates the topographic maps of ITC in each group, task and frequency band. Figure 6B shows the mean ITC values pooled across tasks and electrodes in each frequency band, illustrating the group effects. Theta ITC (4–7 Hz) The repeated-measures ANCOVA revealed a main effect of group (F(2,280) = 13.3, p < 0.001), task (F(1,140) = 6.3, p < 0.001), and electrode (F(8,1120) = 7.4, p < 0.001). Post hoc analysis showed that theta ITC

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Fig. 5. Spatial distribution of grand average ITC in each group and task, for each frequency band (score between 0 and 1). The maps represent the mean ITC around peak (80–190 ms).

was smaller in MCI than sCON (t = −5.3, p < 0.001) and dCON (t = −2.9, p < 0.01), but did not differ significantly between the two control groups (Fig. 6B). Theta ITC was larger in the 2-back than detection task (t = 2.5, p < 0.05), and larger over lateral parietal (Comparison with P3: CP4: t = 3.1, p < 0.05; CP3: t = 4.6, p < 0.001. Comparison with P4: CP3: t = 5.8, p < 0.001; CPz: t = 3.6, p < 0.005; CP4: t = 4.2, p < 0.001) and occipital electrodes (Comparison with O1: CP3: t = 5.0, p < 0.001; CPz: t = 2.8, p < 0.05; CP4: t = 3.4, p < 0.005. Comparison with Oz: CP3: t = 5.2, p < 0.001; CPz: t = 3.0, p < 0.05; CP4: t = 3.6, p < 0.005. Comparison with O2: CP3: t = 4.2, p < 0.001). Alpha ITC (8–13 Hz) The repeated-measures ANCOVA revealed a main effect of group (F(2,280) = 9.9, p < 0.001), task (F(1,140) = 13.9, p < 0.005), and electrode (F(8,1120) = 4.7, p < 0.001). Post hoc analysis showed that alpha ITC was smaller in MCI than sCON (t = −4.8, p < 0.001) and dCON (t = −2.8, p < 0.01), but did not

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Fig. 6. Mean and standard error values of ERSP (A) and ITC (B) pooled across the 9 posterior electrodes (CP3, CPz, CP4, P3, Pz, P4, O1, Oz, O2) and the 2 tasks (Detection, 2-back), in each group and frequency band. ERSP: relative power between 0–500 ms (theta), 100–700 ms (alpha and beta). ITC: peak values between 0–300 ms. The main effect of group is significant in each frequency band (see text for details). Post hoc t-tests: ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001. Significant differences between sCON and dCON in bold.

differ significantly between the two control groups (Fig. 6B). Alpha ITC was larger in the 2-back than detection task (t = 3.8, p < 0.001), and larger over right and mesial posterior than left centroparietal electrodes (Comparison with CP3: Oz: t = −3.6, p < 0.005; O2: t = −3.7, p < 0.001; Pz: t = −3.1, p < 0.05; P4: t = −4.7, p < 0.001; CP4: t = −4.0, p < 0.001).

(t = −4.6, p < 0.001) (Fig. 6B). There was also a strong tendency for smaller beta ITC in MCI than sCON (t = −2.2, p = 0.056). Beta ITC was larger over the right parietal electrode (Comparison with P4: P3: t = 3.4, p < 0.005; Pz: t = 2.8, p < 0.05; CP3: t = 5.1, p < 0.001; CPz: t = 2.9, p < 0.05; O1: t = 4.3, p < 0.001; O2: t = 3.0, p < 0.05).

Beta ITC (14–25 Hz) The repeated-measures ANCOVA revealed a main effect of group (F(2,280) = 6.5, p < 0.005) and electrode (F(8,1120) = 4.2, p < 0.001). Post hoc analysis showed that beta ITC was smaller in dCON than sCON

DISCUSSION Our data reveal that among the different EEG parameters studied, increased alpha and beta ERD as well as decreased beta ITC during the successful


performance of simple attention and working memory tasks are associated with the subsequent development of neuropsychological deficits in cognitively preserved elderly adults. Demographic, behavioral, and ERP data Among healthy controls, 43% developed subtle cognitive decline after 18 months. Although this high percentage of cognitively intact individuals who display decreased neuropsychological performances at a relatively short follow-up interval may be surprising, one should keep in mind that we applied a low threshold of decline in order to explore the very initial phases of cognitive deterioration in healthy control subjects (−0.5 standard deviation compared to baseline). All subjects performed similarly in the detection and 2-back tasks. In accordance with previous findings, early visuo-cortical P1 and N1 components were comparable in the three groups, indicating the preservation of primary visual processing. In contrast, the P3 amplitude was reduced in the MCI group, in line with the alteration of higher-level discrimination processes in this condition [59–62]. The PNwm component, obtained by subtracting the EEG response of the detection to the 2-back task, is thought to be sensitive to memory load and its amplitude has been shown to predict rapid cognitive decline in MCI patients [11, 13]. The present data confirmed the reduction of PNwm amplitude in MCI cases already described in our previous reports, but showed no significant difference between sCON and dCON, supporting the maintenance of working memory processing at the very early stage of cognitive decline. Early cognitive changes and oscillatory responses Theta band In the 4 to 7 Hz range, a significant group effect was evidenced on theta ERS, driven by the significantly smaller theta ERS amplitude in MCI compared to the sCON group. With intermediate theta ERS values, the dCON group did not differ from either sCON or MCI cases. Distinguishing between evoked and induced activities, we previously reported a reduction of frontal induced theta ERS in MCI cases that subsequently evolved to dementia, with preservation of posterior evoked theta ERS [14]. The present findings suggest that early posterior perceptual processes are altered in the MCI group as compared to sCON [15]. On the other hand, the preserved theta ERS in

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dCON cases indicates the robustness of these early perceptual processes in the context of subtle cognitive deterioration. Alpha and beta bands In the alpha and beta frequency bands, non-target stimuli initiated an event-related desynchronization that tended to be of higher amplitude and duration in the working memory 2-back than in the detection task. Such observation is consistent with previous reports describing a sensitivity of alpha and beta ERD to increasing memory load [63–65], and supports the idea that alpha as well as beta ERD are closely related to memory processing [66–68]. However, the lack of significant task effect together with the right posterior dominance of alpha ERD indicate that the primary influential factor on alpha and beta ERD might be the selective attention processes involved in both detection and working memory tasks, as previously described [15, 69–71]. In the alpha range, the posterior ERD was enlarged in dCON and MCI as compared to sCON, suggesting an increased mobilization of resources engaged for attention and working memory in these groups. The increase of memory-related cortical activity in MCI compared to controls was previously described using functional imaging [72–74]. In the same line, a 10–20 Hz ERD was identified in MCI cases contrasting with an ERS in control subjects during auditory working memory encoding [16]. Using magnetoencephalography, a discrete increase of alpha ERD in MCI cases compared to controls was also reported in the left frontal cortex during the retention period of a modified Sternberg memory task [17]. In similar experimental conditions, an increase of neuromagnetic activity was described in MCI cases compared to age-matched controls in a bilateral ventral pathway including ventral prefrontal, inferior parietal, medial temporal, and temporo-occipital regions [18]. In the presence of preserved task performances, such increases were usually interpreted as compensatory phenomena related to the necessity to enhance the activation of the memory networks in order to guarantee accurate task achievement. Alternatively, the increased activation could represent an early sign of loss in brain efficiency due to disease progression. Unlike MCI and AD, only a few studies have addressed the effect of discrete cognitive decline on memory networks. An increase of left prefrontal activity related to episodic memory encoding was reported with fMRI in individuals with subjective memory complaints but no objective cognitive deficits compared to controls [75]. With

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comparable memory performance, individuals with subjective memory complaints showed increased neuromagnetic activity in the ventral and dorsal pathways as compared to controls during memory retention, but did not differ from MCI cases, suggesting that both groups employed similar functional compensatory strategies [76]. Consistent with these observations, our data further indicate that alpha ERD linked to attentional and working memory processes is sensitive to subtle alterations of cognitive status at very early stage of cognitive decline. Modulations in the beta range were less obvious than in the alpha range. The beta ERD was of higher amplitude in dCON than sCON and MCI, but did not differ between sCON and MCI. In the perceptualcognitive domain, beta ERD (decrease of beta activity) is proposed to be determined by exogenous, bottom-up factors, whereas beta ERS (increase of beta activity) would be related to endogenous, top-down components [66]. As alpha, beta ERD can be observed following stimulus presentation in relation with capture of attentional set by exogenous event, mainly in elderly subjects [70, 77]. Consistent with this idea, the increase of beta ERD in dCON as compared to sCON can reflect an enhancement of attentional recruitment devoted to stimulus processing. The absence of change between sCON and MCI is surprising at first sight, and could indicate a ceiling effect in the capacity to recruit additional resources in the presence of more severe cognitive decline. Recent observations using magnetoencephalography during memory encoding corroborate our findings, failing to identify difference in beta ERD amplitude between control subjects and MCI [17]. Early cognitive changes and inter-trial coherence The synchronization of cerebral oscillations reflects the integration of neural network activities to build a meaningful whole [20, 21]. ITC is computed in the time-frequency domain to estimate the degree of synchronization of the stimulus-related oscillatory response across trials, providing an estimate of the quality of stimulus-locked neural firing synchrony. The present data revealed that the ITC was sensitive to the task in the theta and alpha bands, with higher values in the 2-back than the detection task, suggesting that the higher cognitive demands conveyed by the stimulus required low frequency efficiency of neural firing. The largest ITC in the occipital region in the theta band is likely to reflect synchronization across primary visual input responses, whereas larger ITC values in the

right over left posterior regions in the alpha and beta bands suggest the implication of early perceptual attentional processes [78]. More importantly, we observed a differential group effect on ITC according to the frequency band. While theta and alpha ITC were larger in both control groups as compared to MCI, beta ITC distinguished the two groups of control subjects, with decreased values in dCON and MCI as compared to sCON, although differences with MCI remained just below significance probably because of the elevated inter-individual variability in this group. Overall, these observations are in line with most connectivity studies in MCI/AD patients, generally reporting reduced 4–30 Hz coherence among cortical regions in MCI/AD compared to elderly controls at rest, compatible with the disconnection syndrome [25–30]. Moreover, some studies emphasize the greater sensitivity of the beta frequency band, describing reduced resting beta synchronization in MCI and AD that correlates with neuropsychological testing [27, 29]. The rare synchronization studies during working memory activation also confirm reduced alpha and beta global synchronization values with cognitive decline [31, 32]. As far as inter-trial synchronization is concerned, a tendency for reduced ITC values in MCI as compared to controls was shown in the beta range during a visual oddball paradigm [34]. Completing these findings, our results indicate that ITC is particularly sensitive to cognitive decline in the beta frequency range during working memory activation, since this index was able to differentiate two cognitive levels within the control group, in contrast to theta and alpha phase-locking indices. Whereas macroscopic synchronization may be preferentially indexed in theta and alpha low frequency ranges, fine-tuning regulation within higher beta frequency ranges, shown to relate to attentive behavior [79], would be earlier affected in the course of cognitive decline. In conclusion, the present study confirms the abnormalities of several EEG biomarkers during the successful performance of simple attention and working memory tasks in MCI cases as compared to age-matched controls, namely the P3 ERP component, the PNwm, the theta and alpha ERSP as well as ITC. Most importantly, we evidenced for the first time to our knowledge altered oscillatory responses in control subjects showing subtle cognitive deterioration after 18 months that mainly concern the alpha ERD and the beta ITC. As compared to sCON, the increased alpha ERD in both dCON and MCI may reflect the necessity for enhanced attentional resources for task realization at the initial stage of cognitive decline. The reduced


beta ITC in dCON indicates impaired inter-trial phase synchrony initiating at higher frequencies that possibly affects lower frequencies with more severe cognitive impairment, as reduced theta and alpha ITC in MCI would suggest. Strengths of the present study include the relatively large number of cases, detailed neuropsychological documentation of control subjects, and extensive EEG analysis combining ERP, ERSP, and ITC analyses. Some limitations should, however, be considered. First, the follow-up was limited to 18 months. We cannot thus exclude that some dCON remain stable or even improve over time. Second, cognitive activation was centered on simple detection and working memory components and did not include selective attention in a distracting experimental setting, potentially more sensitive to early cognitive deterioration. Third, gamma oscillatory activity, that participates in the synchronization of cortical networks involved in attention and short-term memory [80] was not considered, nor was delta activity, which role in focused attention and internal concentration is being debated [9, 81]. Future investigations including longer follow-up of elderly controls with very subtle cognitive changes and activation paradigms focusing on selective attention are needed to identify additional EEG parameters that may predict the cognitive fate of at-risk elderly controls.

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ACKNOWLEDGMENTS [12]

This project was funded by the Swiss National Foundation for Scientific Research, grant 320030 129690, grant 33CM30 140335, and grant 31ND30 141625 JPND-BIOMARKAPD. Authors’ disclosures available online (http://j-alz. com/manuscript-disclosures/15-0111r1). REFERENCES [1]

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