conceptual spaces and consciousness: integrating ...

International Journal of Machine Consciousness Vol. 3, No. 1 (2011) 127143 # .c World Scienti¯c Publishing Company DOI: 10.1142/S1793843011000649

Int. J. Mach. Conscious. 2011.03:127-143. Downloaded from www.worldscientific.com by 179.231.44.238 on 01/11/13. For personal use only.

CONCEPTUAL SPACES AND CONSCIOUSNESS: INTEGRATING COGNITIVE AND AFFECTIVE PROCESSES

ALFREDO PEREIRA JÚNIOR UNESP, State University of S a~o Paulo, Institute of Biosciences, 18618-000, Botucatu, SP, Brazil [email protected] LEONARDO FERREIRA ALMADA UFG, Federal University of Goias/UNESP, State University of S a~o Paulo, 18618-000, Botucatu, SP, Brazil [email protected]

In the book \Conceptual Spaces: the Geometry of Thought" [2000] Peter Gärdenfors proposes a new framework for cognitive science. Complementary to symbolic and subsymbolic [connectionist] descriptions, conceptual spaces are semantic structures constructed from empirical data representing the universe of mental states. We argue that Gärdenfors' modeling can be used in consciousness research to describe the phenomenal conscious world, its elements and their intrinsic relations. The conceptual space approach a®ords the construction of a universal state space of human consciousness, where all possible kinds of human conscious states could be mapped. Starting from this approach, we discuss the inclusion of feelings and emotions in conceptual spaces, and their relation to perceptual and cognitive states. Current debate on integration of a®ect/emotion and perception/cognition allows three possible descriptive alternatives: emotion resulting from basic cognition; cognition resulting from basic emotion, and both as relatively independent functions integrated by brain mechanisms. Finding a solution for this issue is an important step in any attempt of successful modeling of natural or arti¯cial consciousness. After making a brief review of proposals in this area, we summarize the essentials of a new model of consciousness based on neuro-astroglial interactions. Keywords: Consciousness; conceptual spaces; correlations; methodology; homeomorphism.

1. Introduction The scienti¯c study of subjectivity displays important lines of development in the last 50 years. In the human sciences, the qualitative methods of empirical research, using a diversity of tools to collect and analyze data and developing its own validation procedures, was progressively accepted by the scienti¯c community. Scienti¯c methods derived from philosophy, as the phenomenological and dialectical ones, have 127


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been incorporated into the methodology of these sciences. At the same time, several e®orts have been made to correlate subjectivity with objective processes studied by neurobiology and biophysics. Neural bases of psychological processes as learning, memory formation, attention and emotion have been identi¯ed for several biological species. The search for correlates of conscious experience has brought important results, as the oscillatory synchrony in the thalamo-cortical system correlating with conscious perceptual processes [see, e.g., Rodriguez et al., 1999]. However, while there is remarkable progress in the identi¯cation of specialized brain regions involved in several kinds of conscious processing, few advances have occurred in the understanding of how the informational content of brain states emerge as conscious lived experiences. A neurobiological explanation of the processing of conscious content would begin by identifying what is there to be explained, or the explanandum, in the terminology used by Hempel and Oppenheim [1948], Hempel [1965] and Popper [1963]. Such an explanandum refers to all possible kinds of human conscious subjective experiences, which can be mapped as the state space of human consciousness (for the use of the notion of \state space" in this context, see Stanley [1999] and Fell [2004]). This task depends on the analysis and categorization of empirical data, composed of reports of individual human conscious experiences, implicitly assuming that subjectivity has a universal structure. In this paper, we acknowledge Peter Gärdenfors' proposal of constructing conceptual spaces as a descriptive tool for a science of consciousness, corresponding to the ¯rst step of de¯ning the explanandum of this science. We also pose the question of how to integrate perceptual/cognitive with a®ective/emotional states in a conceptual space that aims to describe the actual structure of human (and possibly human-based arti¯cial) consciousness. We claim that a®ect/emotion and perception/cognition are processed as relatively independent functions and integrated by a supplementary mechanism. A second step in the scienti¯c methodology for the study of human consciousness is to de¯ne the explanans, the kind of biophysical process in the brain (and its interactions with the body and environment) able to account for the processing of conscious content. A coarse-grained mapping of brain regions involved in each kind of conscious processing is not su±cient for this task; it is also necessary to identify how information is encoded and processed by neuronal and glial cellular populations. According to Gärdenfors [2000], one central property of conceptual spaces is the existence of correlations between dimensions, a feature that would correspond to the existence of large coherent patterns of activity in the brain. A positive matching of such structures (the state space that describes the contents of human consciousness, and the state space of biophysical information processing in the brain), displaying isomorphic or homeomorphic inter-relations, would validate this methodology. In this regard, we make a review of the literature on cognitive and emotional functions, discussing how their integration can be described in conceptual spaces without

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disrupting the intended correspondence with brain physiology. The results are applied for the understanding of conditions to be satis¯ed by conscious arti¯cial systems.


2. From Intersubjective Validation to Universal Conceptual Spaces Frith et al. [1999] proposed a method to study the neural correlates of consciousness that is based on the temporal co-occurrence of registered/measured brain activity (using EEG, MEG, fMRI, PET-scanning, etc.) and conscious states reported by the subject who is having his/her brain activity monitored. In our analysis of this method, we make a distinction between conscious episodes instantiated by brain activity and lived experiences involving brain-body-environment dynamical interactions [Pereira Jr. and Ricke, 2009]. For instance, currently available \mind-reading" technology [e.g., Kay et al., 2008] can access coarse-grained brain functional con¯gurations but cannot measure lived experiences. Partial accessibility of the latter to the experimenter depends on verbal and/or non-verbal reports made by the human subject. Therefore, what this methodology actually gets is a correlation between measured brain activity and reports made by the subject about the content that he/ she experienced while the activity occurred. The above procedures are too weak to determine a causal or law-like relationship between brain states/processes and conscious states/processes, but su±ciently strong to be considered as scienti¯c. A part of the weakness derives from the limitation of isolated studies, where the correlations may be biased by cultural or individual peculiarities. Therefore a possibility of adding a further strength to this methodology is by crossing the results obtained by several subjects and several experimenters, in order to identify the common aspects of reported human experiences. The crossing of several experiments in the cognitive neuroscience of consciousness makes possible an inter-subjective validation of the method. The rationale is that it would be extremely unlikely that several human subjects, sharing the same class of biological (genetic and phenotypic) constraints, interacting with the same kind of experimental setting, and not being a®ected by any well-known psychopathology or under e®ect of psychotropic drugs, would have di®erent lived experiences. It is important to consider that one stance of inter-subjective validation always occurs in any cognitive neuroscienti¯c experiment, when the experimenter makes a confrontation of the subject's report and his/her own perception of a presented stimulus (e.g., when the experimenter presents an object that he/she perceives to be a blue circle, he/she expects the subject to report seeing a blue circle and not, for instance, a red triangle). The idea of crossing subjective experiences is implicit in Dennett's proposal of a hetero-phenomenological approach [Dennett, 1991], but his approach was conceived as a refutation of ¯rst-person approaches to consciousness, not as a procedure of inter-subjective validation as we are proposing here. The original hetero-phenomenological method also lacks an appropriate framework to plot the result of studies made by di®erent researchers analyzing di®erent subjects.


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This kind of framework is provided by Gärdenfors. It is composed of geometrical tools (quality domains, similarity judgments as measure of proximity) used for the construction of conceptual spaces. Therefore, an important advancement provided by this new approach is to allow the progressive build-up of results of individual hetero-phenomenological studies into what might be called the universal state space of human consciousness. The lived experience of an individual human subject, as long as it can be communicated to others, would correspond to a trajectory in this state space. Considering that ¯rst-person lived experiences are partially available to empirical (third-person) science by means of verbal or non-verbal reports, this framework can support the interpretation of \qualitative" data (i.e., reports of lived experiences) in the context of cognitive sciences. The state space model can be useful as a referential framework also for introspective and phenomenological approaches. More importantly, for this scienti¯c methodology the distinction of ¯rst- and third-person perspectives is secondary, while keeping centrality from a philosophical perspective. Perceptual concepts and \qualia" refer to the same entities, suggesting the possibility of partial inter-translation of third-person and ¯rstperson descriptions. If a set of common results is reported by di®erent subjects, e.g., if they agree on the perceptual content elicited by a stimulus, the di®erence between the perspectives disappears for practical purposes. As the term \qualia" has a long and disputed history in philosophy, when possible we prefer to avoid its usage and refer to the corresponding concepts. One of the problems is that a \quale" includes both the subjective feeling (e.g., \what it is like for Adam to be looking at a red apple") as well as apparently objective informational properties (e.g., \the redness of red"). The partial conclusion we draw here is that the conceptual space approach is a valuable tool for the science of human consciousness and practical applications, since it a®ords the construction of a universal model representing the properties of the \explanandum" of this science. 3. Conceptual Spaces and A®ective/Emotional States Gärdenfors' approach is supported by empirical evidence from psychophysics, cognitive psychology, linguistics and neuroscience. The use of data from cognitive experimentation for the construction of perceptual spaces is possible because he implicitly assumes a universal structure of human cognition. Then, the subjects' reports of lived experiences in several experiments can be constructively mapped into the theoretician's model. A problem that appears for an approach to conscious processing based on conceptual spaces is how to integrate a®ects and emotions with cognitive states. Since a®ects/emotions are fundamental to conscious processes, they should be accounted for by the conceptual space approach for this method being successful as a description of the \explanandum" of consciousness science.



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First, it is necessary to clarify what we mean by \a®ect" and \emotions", and how they di®er from cognitive states. \A®ect" refers to a class of subjective feelings, such as those related to basic physiological functions (hunger, thirst, heat, pain, body pleasure, etc.) and psychological states (love and hate, happiness, sadness, etc.). \Emotion" refers to feelings related to the objects of action in a bio-psycho-social context, e.g., anger (of something), anxiety (for something), fear (of something), etc. The distinction is surely a fuzzy one. Conceptual spaces are de¯ned as \theoretical entities that can be used to explain and predict various empirical phenomena concerning concept formation" [Gärdenfors, 2000, p. 31]. They are made of quality dimensions, representing the qualities of objects, like weight, brightness and pitch. The proximity or distance between dimensions is established by judgments of similarity, which can be made in the context of scienti¯c experimentation. Such judgments establish intra- and interdimensional correlations. How could a®ects and emotions be included in conceptual spaces? To answer this question, three issues are brought into consideration: (i) A®ects and emotions are lived experiences, not concepts. One problem with the proposal of a mathematical \qualia space" by Stanley [1999] was the con°ation of concepts and experiences. Universal types of conscious experience can be represented by concepts (which are indicated by terms as \pain" and \pleasure", in the above examples). Conceptual spaces, of course, are not made by lived experiences themselves, but by their concepts. In order to achieve a realistic view of the human mind or any arti¯cial system that simulates or reproduces activities of the human mind, the relations between concepts should have a homeomorphism with actual relations. This correspondence is assured, in Gärdenfors' case, by the method of construction of the model; (ii) Conceptual spaces, as they were presented by Gärdenfors [2000], are heavily based on perceptual and cognitive processes. The symbol grounding problem is solved since perceptual domains \are tied to sensory input channels and hence what is represented in these domains has some correspondence with the external world" [Gärdenfors, 2000, p. 43, 44]. The learning problem of connectionist networks is also approachable, since it provides an understanding of concept formation by means of judgments of similarity. The frame problem is solved when information is not conceived as modality-free, but sorted into domains. The properties of objects are conceived as perceptual invariances located in conceptual spaces. While properties are based on one quality domain, perceptual concepts are based on several domains. Therefore, they are multimodal instead of amodal; e.g., the concept of \apple" involves the color, shape, texture, taste, fruit and nutrition domains, see Gärdenfors [2000, p. 103]. How to apply the same strategy of argumentation — based on the embodiment of processes — to a®ective and emotional phenomena? In order to answer this question, it is necessary to examine how scientists conceive the process by which the brain supports lived experiences and discuss the inclusion (or not) of other parts of the


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body and parts of the environment in the process that generates a®ects/ emotions; (iii) The location of a linguistic term in the conceptual space may vary, depending on the context of the utterance. Conceptual spaces can also be used as a basis for cognitive semantics, replacing realist approaches (both extensional and intensional). Gärdenfors proposes that \meanings of linguistic expressions are mental entities" [Gärdenfors, 2000, p. 154], at the same time holding that conceptual structures of di®erent individuals become attuned to each other: \via successful and less successful interactions with the world, the conceptual structure of an individual will adapt to the structure of reality" [Gärdenfors, 2000, p. 156]. He assumes a \socio-cognitive" position, accounting for social power in°uences on conceptual structures. These constraints surely apply to a®ect/emotion, mostly to the latter, since it is by de¯nition related to events in the body and environment. The construction of a universal conceptual space representing the universe of conscious contents is proposed to be the ¯rst step in the methodology of a science of consciousness. It requires collection of verbal and non-verbal reports of ¯rst-person experiences correlated to measured brain and body activity; inter-subjective validation of the reports, and construction of a conceptual space of conscious contents. An analysis of the structure of this space may further guide the search for arti¯cial reproductions of consciousness. The ¯rst step should be accompanied by a second one, the theoretical modeling of brain activity at multiple spatio-temporal scales, composing a state space of brain functions. This strategy implies that homeomorphisms [Fell, 2004] between the structure of conscious contents and the structure of brain/body activity are going to be found by means of a matching of the state space of human consciousness with the corresponding state space of human brain functions. Finding a solution for the issue of integration of emotional and cognitive processes is an important step in any attempt of successful modeling of natural or arti¯cial consciousness. A ¯rst move in the direction of including a®ective/ emotional processing as a fundamental component of consciousness is the Somatic Marker Hypothesis (SMH), by Dam asio and colleagues. According to the defenders of the hypothesis, a®ects/emotions are related to somatic states, being preceded and followed by cognitive processes. The latter include both basic and higher brain processes, from simple perceptions and thoughts to attention, evaluation, and decision-making. SMH considers a®ect/emotion as \a collection of changes in a body state connected to particular mental images (thoughts) that have activated a speci¯c brain system" [Dam asio, 1994, p. 159]. Feelings of emotions are ¯rst and foremost considered to be about the body: \they o®er us the cognition of our visceral and musculoskeletal state as it becomes a®ected by pre-organized mechanisms and by the cognitive structures that have developed under their in°uence" [Dam asio, 1994, p. 159].



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However, SMH defenders also hold that emotional appraisal can interfere with and even support higher cognitive functions, as decision-making: \individuals make judgment not only by assessing the severity of outcomes and their probability of occurrence, but also and primarily in terms of their emotional quality" [Bechara et al., 2000, p. 305]. This part of their theory leads to what would be considered as bad explanatory circularity, causing possible inconsistencies criticized by Bennett and Hacker [2005] and Rolls [2000]. Recognizing the embodiment of emotion would require more than merely mapping brain activity, since emotion is related to the actions of the living individual's body in the environment. While the content of each feeling can be considered to be the product of a specialized, epigenetically determined brain circuit or module, the content of emotions vary according to the context (state of the body and environment). In this regard, SMH brings an important contribution to the understanding of embodiment of emotions when taking into account the reciprocal signaling of brain and body. In spite of a possible explanatory circularity in its framework, the SMH may contribute to the description of integrative functions in the universal conceptual space of consciousness, since lived experiences should necessarily include the dynamical relation of brain, body and environment. A second position, illustrated by the work of LeDoux [1996] and Panksepp [1998], assumes the independence and, in many cases, a predominance of a®ects/ emotions on cognitive activity. This position is able to avoid most of the criticisms made to SMH by Rolls, since it does not attempt to derive the content of feelings and emotions from somatic activity, but take them as brain primitives. However, the predominance of emotion over cognition con°icts with empirical evidence gathered by SMH defenders, and contradicts theoretical argumentation by Bennett and Hacker. The latter authors are opposed to Damasio and colleagues only regarding the dependence of decision-making on somatic markers and related emotions. Considering available evidence reviewed by the above authors, we suggest that it could be encompassed by a third possibility of mapping the dynamics of cognitive and emotional processing. Perceptual/cognitive and a®ective/emotional functions are primitive brain functions, being able to occur both implicitly (unconsciously) and explicitly (consciously). Modeling of perceptual/cognitive systems in conceptual spaces was largely advanced by Gärdenfors [2000], while modeling of emotional systems was advanced by Panksepp [1988], in a pioneering work that could equally be translated to conceptual spaces. According to Panksepp [1998], our cognitive representation of the world merges within the processing of a®ective states. A®ective states are related to the awakening of primitive emotional command circuits in the whole extended neural network, including the operational systems he calls (using capitol letters) \SEEKING, FEAR, RAGE, LUST, CARE, PANIC, and PLAY" [Panksepp, 1998; 2005]. These would be fundamental dimensions of the human a®ective conceptual space that interact with perceptual/cognitive dimensions. Cognitions re-evoke feelings in function of our


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past experiences and history of conditioning, thus interacting with emotional self-regulation. The dynamics of emotional systems tends to be more egocentric and unconditionally a®ective than cognitive functioning, since the goal of cognitive processes is generally to provide more subtle solutions to problems posed by emotional arousal. In hominids, the evolution of certain higher symbolic abilities provided ways for organisms to solve con°icts that are very di±cult from an exclusively emotional perspective. The increasing in°uence of cortical functions provides cognitive resources to solve con°icts during human maturation. This evolution was critically \guided by the pre-existing neurobiological exigencies of organisms" [Panksepp, 2001, p. 144]. In fact, these exigencies are related to subcortical emotional and motivational abilities \which are generally more similar among living mammalian species than their higher cortico-cognitive functions which have diverged more considerably" [Panksepp, 2001, p. 144]. A®ective states re°ect evolutionary value codes. In this sense, the projection of feelings onto environmental events and objects was one of the simplest ways for evolution to persistently guide perceptual priorities of the cognitive apparatus. This type of interaction occurs by means of global neurodynamic processes in the brain, making possible that cognitive problems could be ameliorated simply by adjusting the underlying emotional feelings, and vice versa. In other words, a®ective states of consciousness \may, quite simply, be among the most robust and e®ective ways to rechannel cognitive resources" [Panksepp, 2001, p. 152]. Cognitive forms of consciousness were evolutionarily grounded \on the prior evolution of a®ective forms of consciousness, which inform organisms what it might be worth thinking about" [Panksepp, 2001, p. 152]. When brain functions occur consciously, there must necessarily be an integration to de¯ne their access to the coordination of covert and overt behavior. This integration possibly happens in some kind of \Global Workspace" [Baars, 1997] embodied in brain activity. One possible implementation of the workspace is by means of neuro-astroglial interactions, as recently suggested by one of us [Pereira Jr. and Furlan, 2009; 2010]. In this approach, each brain circuit or functional module is considered to be specialized for a speci¯c function, while the integration occurs by means of the operation of a supplementary mechanism that involves virtually all specialized circuits/modules, but is not identi¯ed with any of them. 4. From Arti¯cial Intelligence to Arti¯cial Consciousness The project of \strong" Arti¯cial Intelligence was to construct machines able of performing human cognitive functions. Critics soon noted that aspects of these functions could not be performed by Turing machines; some of them also predicted that these functions would not be reduced to digital computations, because of several di±culties (as the combinatorial complexity and frame problems). The same objections apply to projects of arti¯cial consciousness, which also poses two


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additional problems:


(a) What is required for an agent to be conscious, besides information processing? (b) What is the (arti¯cially reproducible) biophysical mechanism su±cient to execute it? An attempt to overcome initial di±culties is the \embodied and embedded" paradigm of cognition, which claims that the strategy of implementing computations based on internal databases should be substituted by an analogue of brain-bodyenvironment interactions. One of the main attempts to bring this idea to reality was Rodney Brooks' robot \Cog", which has a central processing unit embedded in a human-like half-body and was \educated" by a woman playing the role of \mother" in a human-like environment [Brooks et al., 1998]. Why would a robot like Cog not, in principle, become a conscious agent? More simply, why a thermostat that measures and controls room temperature does not feel hot or cold? The answer, of course, depends on the concept of consciousness that is assumed. Before making a speci¯c proposal (see next section), we would like to review some alternatives presented by several authors. A ¯rst line of reasoning is that not any representation is conscious, but only a subclass explicit representations. The problem here is to identify what features make a representation explicit for the agent. For human beings, explicitness is often related to symbolic and/or linguistic formulation of content. This line of reasoning leads to di±cult issues of syntax and semantic processing, as those discussed by Mandik [1999], leading to the suggestion of a \procedural psychosemantics" that evaluates properties of introspective content of experiences (\qualia") regarding their e®ects (instead of their causes). This reasoning does not apply to all qualia, but to spatial properties related to motor control. In this regard, the theory of a \retinoid system" by Trehub [1991] describes a brain subsystem able to construct an egocentric three-dimensional transparent representation of the world. Like in Mandik's approach, this proposal is limited to the spatial structure of perceptual consciousness. The retinoid system is a model of brain mechanisms supporting our egocentric spatial representation of the world, leaving open the explanation of other dimensions of the conceptual space and corresponding brain mechanisms. Another possible requirement is the capacity of elaborating self-referential representations, as in High-Order Thought theories of consciousness [Rosenthal, 2002; 2004]. Rosenthal [2002] begins by distinguishing between \creature consciousness" and \state consciousness", assuming that animals like frogs and turtles are creature-conscious while being fully state-unconscious (i.e., all their mental states may well not be conscious). Arguing from what seems to ¯gure in the phenomenon of state consciousness, he argues that \being aware of a mental state…is not a su±cient condition for the state to be conscious". In his view, consciousness consists in a thought to the e®ect that one is in the state in question, and the thought must not rely on any inference. This holds for both conscious intentional states and conscious


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qualitative states, such as sensations. This is not an easy idea to implement in arti¯cial systems, since before being able of self-reference it is necessary for the system to have a Self ! This result is expected in the long run for evolutionary computing paradigms, but there is no guarantee that it will occur. Other di±culties are that the operation of self-reference is related to logical paradox, and possibly absent in non-numan animals. One scienti¯cally promising project is the attempt to quantify conscious integrated information and related subjective experiences [Tononi, 2005; Balduzzi and Tononi, 2009]. Tononi's theoretical framework is based on two ideas: that consciousness is \informative" in the sense that any conscious state is a \reduction of uncertainty" (it rules out many alternatives); and that conscious states integrate brain information by means of causal interactions among its parts. He developed a framework to measure the quantity of integrated information (phi) in brains that may be useful for medical diagnosis and technological purposes, such as measuring it in arti¯cial systems. A new development of the theory includes an approach to the qualities of subjective experience (\qualia"). What would be the relation of integrated information with qualitative subjective experience? Balduzzi and Tononi explain that \for integrated information to be high, a system must be connected in such a way that information is generated by causal interactions among rather than within its parts… The set of all submechanisms of the system… conveniently captures all possible combinations of causal interactions" [Balduzzi and Tononi, 2009, p. 5]. Then they introduce the concept of \informational relationship" to represent \di®erences that make a di®erence" to the system. How does a causal interaction \make a di®erence"? A condition of possibility is the existence of a pre-existing conceptual space where entanglements (i.e., integrated information relations) can be speci¯ed: \a fundamental property of q-arrows (informational relationships APJ/LA) is their entanglement… the extent to which an informational relationship does not reduce to its component relationships (sub-q-arrows)" [Balduzzi and Tononi, 2009, p. 6]. Each \quale" corresponds to an activation of the conceptual space (\qualia space", in their terminology) by causal brain mechanisms; therefore, contrary to the model presented by Stanley [1999], subjective experiences would not pre-exist in qualia space, but are constructed from brain activity. Although mathematically well built, both models still lack biophysical grounding. We suggest that the proposal reviewed in the next section provides what is missing to understand the brain basis of information integration and/or to implement the concept in an arti¯cial agent. A sophisticated interdisciplinary approach is the \physics of mind" proposed by Perlovsky [2009]. Conscious processes are conceived as the matching of forms at several levels, e.g., from retina to prefrontal neurons in the visual system. The initial vague patterns that drive top-down signaling are innate (given by the Knowledge instinct). At some point in human ontogenesis, this process includes language circuits (also innate the Language instinct), which allows us to use abstract forms that are



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not innate (\memes"). The matching process applies to cognitive functions of other animal species. Conscious representations are those that become crisp along the matching processes. Perlovsky's model is not strictly Kantian, since in the faculty of understanding described in Critique of Pure Reason there is no matching of internal (a priori) and external (empirical) forms. All forms are a priori experience only gives us the matter to ¯ll internal templates of space/time/causation/substance, etc. In Perlovsky's model, called \Dynamic Logic", the matching process a®ords an interaction of externally originated and internal information patterns, avoiding the problem of combinatorial complexity by means of an adequate use of Fuzzy Logics (instead of the Principle of the Excluded Middle). A criticism we make is about the relation of crispness and a®ective/emotional states regarding consciousness. Possibly there is not a necessary connection between the proposed con°ict-solving role of consciousness and crispness. A solution of a con°ict of instincts/re°exes may be just choosing one of the vague unconscious alternatives and abandoning the others. Of course, in some cases it may be better to make a synthesis that uses parts of di®erent con°icting alternatives, but there is no reason to assume that the synthesis has to be crisper than the original alternatives. In fact, it may be even more vague if based on Fuzzy reasoning. More importantly, we did not see a fundamental role for feelings in the conduction of the process that leads to consciousness. Emotional feeling (as aesthetical feeling) is regarded as a byproduct of good matching, not as a factor for selection of forms to reach consciousness. It seems the model assumes like most of Modern Philosophy and contemporary Cognitive Science that we are rational beings driven by cognitive processes. We would better suggest that besides the Language and the Knowledge instincts assumed by Perlovsky we also have A®ective instincts, as argued in the context of Jaak Panksepp's A®ective Neuroscience (following Cannon's and McLean's approach, also assumed by LeDoux and others). If the a®ective instincts are introduced as fundamental together with the knowledge and language instincts then the relation between crispness and consciousness would have to be rede¯ned, since this property would not apply to feelings. In fact, feelings are not \representations" measured as being more or less accurate relatively to an intentional object or process. If feelings are considered to be important players in the consciousness game, the crispness of representations would not be the main parameter in the construction of scales to measure degrees of consciousness. In this section, we conclude for the need of an approach that goes beyond SMH, inserting a®ective operational systems as fundamental dimensions of the conceptual space. A question remains about the nature of a®ective states in the brain, and how to implement it in arti¯cial systems. The next section is about a new approach to the brain mechanisms underlying a®ective states and their putative biophysical nature.

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5. A Viable Implementation of Universal Conceptual Spaces in Neuro-Astroglial Networks In a recent work, Pereira Jr. and Furlan [2010] propose a new model of consciousness that includes a central role for astrocytes. The principles of this model can be extended to arti¯cial systems. The model departs from the sketch of a large scale Ion Trap Quantum Computer (ITQC) adapted to biological conditions [Pereira Jr., 2007]. In quantum computing models, it is assumed that the trajectory of particles, under well known initial and boundary conditions (quasi-isolated micro-system frozen to the ground state) is determined by fundamental physical laws. As these laws are temporally invariant, computations carried in this kind of system are considered to be reversible. In a biological macro-system, there are at least three factors that indicate an incompleteness of quantum theory to describe the dynamics: (a) The process of decoherence (or objective reduction or \collapse") of the wavefunction, attributed (by several authors) to supplementary factors; (b) The many-body problem (discussed by Poincare as \three-body problem"), leading to an impossibility of deterministic calculation of the trajectory. At this point, Statistical Mechanics take the place of Quantum Theory in the explanation of observed macro-phenomena; (c) The Second Law of Thermodynamics, causing the evolution of the macro-system to be irreversible. Initial conditions of living systems include a database, the DNA, from which Biological Maxwell Demons (enzymes) are built. The Second Law requires that the work of enzymes, reducing internal entropy, must be compensated by means of consumption of useful energy from the environment, implying that these systems must consume food to survive. Both DNA information present in the initial state and the necessity of consumption of low entropy from the environment are not theorems of Quantum Theory. These conditions, necessary for the existence of life, are also related to the formation of coherent calcium waves in astrocytes, since a class of proteins crucial for brain activity, the ligand-gated ion channels (e.g., NMDA channels) operate like Biological Maxwell Demons, controlling the °uxes of ions through cellular membranes and compartments. We conceive large calcium waves as composed of an ensemble of small standing waves, each one inside an astrocyte microdomain. Their connection, forming a larger pattern of coherent activity, is made by ATP signaling (in the case of the \domino e®ect", see Pereira Jr. and Furlan [2010]) and by neuronal synchronous ¯ring (in the case of the \carousel e®ect", see Pereira Jr. and Furlan [2010]). Microdomains are subcellular, but the domino and carousel e®ects are assumed to transpose their patterns to a collective of cells, thus composing a fractal multiscale pattern. Also quantum entanglement of calcium ions possibly plays a role in intercellular communication, but this communication can occur only after the waves are formed. With entanglement, when a small wave inside a microdomain is formed, another



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small wave in a spatially distant region of the astrocyte network can be a®ected, without any particle from the initial wave being actually transported to the second. However, quantum entanglement cannot explain the formation of waves, since this process requires mechanical causation. The two, domino and carousel e®ects, are intended to explain the formation of waves; after formed, quantum entanglement may occur within them. Considering both e®ects, the time needed to produce a large coherent calcium wave is close to the time needed to form small calcium waves in microdomains. Our claim is that the brain substrate of feelings cannot be a FM (Frequency Modulated), but has to be an AM (Amplitude Modulated) pattern. FM is very good to transmit information and reduce noise. The problem is that it requires a decoder to read the message. In the brain, FM a®ords a digital-like encoding of sensory and motor signals. In the ¯rst case, the receiver is a CNS (Central Nervous System) neuron; in the second case, a muscle or gland. However, the idea of FM information transmission to consciousness would require an homunculus, which was resuscitated by Crick and Koch [2003]. We conceptualize our feelings (e.g., pains and pleasures) as homeomorphic to large and coherent AM astrocytic calcium waves, instead of Morse-like sequences of pulses in millions of neurons. As the astroglial calcium wave is conceived as the ¯nal stage of conscious processing, there is no need of a receiver. The ¯nal step would be an analog reproduction (a \presentation", not a \representation") of the properties of the world, by means of an AM waveform, which feedsback on the whole living individual. Therefore, at the end of the line there should be a collective large-scale AM wave. The only place for it in the brain is the astroglial network. Neurons process information and trigger muscle/gland action without having the feeling of what is going on. The dendritic graded potential is ¯ltered by the axon hillock to generate a Frequency Modulated (FM) signal along the axon. Synapses receives only this signal; they do not have access to the dendritic AM pattern. The di®erence for the astrocyte network is the possibility of a collective AM wave. Phibram [1991] and Hamero® [2010], appealed to dendritic ¯elds as substrates of consciousness, but how would one dendritic tree transmit its AM pattern to others? The solution found by Hamero® is to make electric synapses responsible for this task, but the attempt fails because these synapses only transmit electric current that °ows to a segment of a dendrite, not the information pattern present in the graded potential as a whole. All brain areas contain both neurons and astrocytes. Their cognitive functions are mediated by glutamatergic transmission. Neurons operate as specialized information processing detectors/¯lters/relays, but do not convey a feeling about the content of the information they process. For example, in the amygdala, neurons ¯re to a®ective/ emotional salient/relevant stimuli, but the corresponding feelings are not instantiated by them [see Pessoa and Adolphs, 2010]. Pereira Jr. and Furlan [2010] propose that feelings are instantiated by a large astroglial network connected to the


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amygdala's astrocytes. In this view, it is not the amygdala that feels fear, or the insula that feels pain or pleasure; the conscious subject is the whole brain/body of the living individual, having the astroglial network as the main connector (Master Hub) between his/her subsystems (blood, cerebral °uid, muscles, neurons). According to model developed by Pereira Jr. and Furlan [2010], the Slow Cortical Potential [He and Raichle, 2009] involved in default networks, as well as ERP waves associated to conscious processing (P300, N400, etc.) would be mediated by the astroglial network. Of course, scalp EEG does not tell us if the potential is mediated by neuronal or astroglial transmission, but the relative slowness and concentrated power of the wave suggests that it is mediated by the astroglial network instead of neuron axon bundles (if so, the wave would be faster and have less impact on the EEG). What would be the neurocentric interpretation of how the slow cortical potential moves along brain tissue? The standard explanation is that the potential would move along super¯cial layers of the cortex as a result of sequential excitation and inhibition of columns. Thalamic glutamatergic input to a pyramidal neuron in deeper layers elicit both a feedback to thalamus and an excitatory signal to super¯cial layers of the same column. Excitation of this column leads to the excitation of inhibitory neurons in adjacent columns, which inhibit the pyramidal neuron. Meanwhile, the super¯cial layer neurons have propagated the excitation to another column, where the whole cycle occurs again, and so on. The propagation would be by means of horizontal cortico-cotical connections (endogenous) or by means of thalamic guidance (in the case of an external stimulation). Magnetoencephalography would detect this movement of the excitatory potential, while the EEG only detects the outcome. The propagation of waves measured by scalp EEG by means of dendritic columns is a hypothesis made to save the phenomena, but the hypothesis has never been really proven. The clearest theoretical fact is that dendritic ¯elds in tripartite synapses activate astrocytes and vice versa (astrocyte calcium waves feedback on neurons). Therefore, the reasonable conclusion is that any slow cortical potential must involve both dendritic ¯elds and astroglial calcium waves. One most interesting test to check which one is more important to consciousness is to identify which one is absent in non-REM sleep. An important result found by Tononi and colleagues [Massimini et al., 2010] is compatible with the idea that lack of connectivity during non-REM sleep results from deactivation of the astrocyte network. Neurons continue to produce graded and action potentials during this phase of sleep, the main di®erence being that they synchronize in slower frequencies (3 Hz; Delta). Pereira Jr. and Furlan [2009] hypothesized that the relevant e®ect of Delta for unconsciousness is on astrocytes; with 3 Hz, coherent large calcium waves are not formed in the astrocyte network. However, a neurocentric explanation is also possible. Considering changes of concentration of available transmitters during slow-wave sleep, it may be the case that one of the steps in the chain of neuronal events is blocked. New results and computer simulations may helpfully indicate the causes of reduced cortical connectivity during non-REM sleep.


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6. Concluding Remarks In our view of brain instantiation of the universal conceptual space of human consciousness, conscious states are conceived as a conjoint product neuronal and astroglial activity. Paraphrasing the title of Dam asio's book, consciousness is \the feeling" (or sentience) of \what happens" (information contents embodied in spatially distributed neuronal activity). Sentience is supported by wavelike processing in astrocytes, while awareness (in the sense of information processing) would depend on digital-like information transmission by neurons. Neuronal dendritic ¯elds are wavelike, but axonal transmissions are not. Dendritic ¯elds contain the information that becomes conscious, but consciousness occurs only when these patterns are integrated by the astrocytic network into a wavelike unity. Consciousness is conceived as astroglial integration of information contents carried by neurons. In this context, we make terminological equivalences: [astrocyte analog wavelike processing ¼ ½information integration ¼ ½feeling ¼ ½sentience. Then consciousness is ½ðastroglialÞ sentience of ðneuronalÞ awareness ¼ [the feeling of the information content] ¼ ½\the feeling of what happens". Neither neuronal awareness of information nor astroglial sentience (e.g., unconscious emotions) are fully conscious. When they get together, higher degrees of consciousness occur. Speci¯city is neuronal. Di®erent features are represented by means of activation of neuronal receptive ¯elds. Astrocytes do not reproduce neuronal information with ¯delity. The astrocytic wavelike response conveys the feeling, which is intrinsically di®use. In the above view, exclusive neuronal or astroglial activation would correspond to lower degrees proto-consciousness while conjoint activation would correspond to higher degrees full consciousness, i.e., awareness with a feeling. \The feeling" is also similar to Thomas Nagel's \what's like to be" that was important for Chalmers' reasoning [Chalmers, 1995; 1996]. According to these guidelines, the generation of arti¯cial conscious agents would require both computational and a®ective mechanisms to reproduce neuronal functions specialized digital processing of features of information and astroglial functions integration of such a distributed processing and generation of a feeling about the message carried by the signals. These mechanisms are physically di®erent; the ¯rst one is based on ¯lters exchanging discrete signals, while the second operate on wavelike patterns in a continuum medium. A universal conceptual space of consciousness would correspond to invariants resulting from the conjoint operation of both mechanisms. The degree of reproduction of human consciousness would depend on the arti¯cial mechanisms being similar to those achieved in our evolutionary and historical pathways.

Acknowledgments CNPQ (Brazilian funding agency grant conceded to APJ), Leonid Perlovsky, David Balduzzi, James Robertson, Chris Nunn, Arnold Trehub, David Rosenthal,

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Antonio Chella and an anonymous reviewer, for discussion and suggestions that helped to improve the text and the message.


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