Multiple Perspectives on Consciousness for Cognitive Science

EDITORIAL article Front. Psychol., 01 September 2011 | https://doi.org/10.3389/fpsyg.2011.00191

Back to table of contents Previous article Next article LettersFull AccessToward a Unifying Hypothesis for Schizophrenia and Autism Visual FragmentationFatemeh Bakouie, M.D., and Shahriar Gharibzadeh, M.D.Fatemeh BakouieSearch for more papers by this author, M.D., and Shahriar GharibzadehSearch for more papers by this author, M.D.Published Online:1 Jul 2011AboutSectionsView articleView PDFView EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinked InEmail View articleTo the Editor: Neurobiological research shows that consciousness has some neural correlates in the brain.1 Understanding these neural correlates may be helpful in revealing the mechanisms of consciousness defects in disorders like autism and schizophrenia. Neurobehavioral studies suggest that autistic patients do not integrate visuo-perceptual information efficiently, which leads to the fragmented visual world of autistic patients. Surprisingly, “perceptual fragmentation” and “inefficient neuro-integrative perceptual processing” have also been described in schizophrenia.2 Why, despite important differences, do these two diseases have such remarkable similarities? Certainly, the answer should be investigated at the cellular-molecular level. However, since the brain is a complex system with multiple interacting elements, it will be difficult to study the details at this level without having any initial insight. It seems that a systemic approach helps to solve the puzzle by bridging the distance between the cellular-molecular level and gross behavioral aspects. Some theories of consciousness provide such a systematic view, two of which are the “dynamic core hypothesis” (DCH) and “information-integration theory” (IIT). In this notion, consciousness arises from a group of neurons (the dynamic core) which, in their dynamics, through reentrant interactions in the thalamocortical system, are simultaneously differentiated and integrated. Based on these theories, in conscious states, the brain can integrate the many different parts (modalities) of a scene to form a unitary view, which would be perceived as an integrated experience.3,4 The authors hypothesize that the fragmented visual world of autistic and schizophrenic patients is interpretable based on DCH and IIT viewpoints: the integration of the dynamic core, which contains the neuronal cluster that produces the visuo-perceptual conscious state, is somehow diminished in both diseases, which causes the perceiver to have fragmented and nonunitary visual experience. For determining the main neurobiological cause, some scientific clues may help us: 1) the effect of dopamine overstimulation in schizophrenia is strongly suggested in many research findings; 2) dopamine involvement in autism is implicated in some studies; 3) it has been claimed that striatum is not a simple relay, and records in animal research show that striatal neurons could integrate spatial information (the effective contribution of dopaminergic signaling to the modulation of neuronal activity in striatum has also been reported); and 4) the concept of involvement of dopaminergic neurons in the regulation of the different cognitive aspects of behavior is illustrated in various experiments.5 Considering the abovementioned points, we believe that dopamine is involved in integration of information in dynamic core during visuo-perceptual tasks, which are disturbed both in schizophrenia and in autism. Since DCH and IIT present quantitative measures of neural system integration, using these measures may help us in understanding the role of dopamine in the mechanisms leading to visuo-perceptual fragmentation. Surely, experimental research is needed to validate our hypothesis.Neuromuscular Systems Laboratory, Biomedical Engineering Faculty, Amirkabir University of Technology1. Crick F , Koch C : Towards a neurobiological theory of consciousness. Sem Neurosci 1990; 2:263–275Google Scholar2. Bertone A , Mottron L , Faubert J : Autism and schizophrenia: similar perceptual consequence, different neurobiological etiology? Behav Brain Sci 2004; 27:4:592–593Crossref, Google Scholar3. Seth AK , Dienes Z , Cleeremans A , et al.: Measuring consciousness: relating behavioural and neurophysiological approaches. Trends Cogn Sci 2008; 12:314–321Crossref, Medline, Google Scholar4. Seth AK , Edelman GM : Consciousness and complexity. Springer Encyclopedia of Complexity and Systems Science, 2009; cogs.susx.ac.ukGoogle Scholar5. Nieoullon A : Dopamine and the regulation of cognition and attention. Prog Neurobiol 2002; 67:53–83Crossref, Medline, Google Scholar FiguresReferencesCited byDetailsCited ByNone Volume 23Issue 3 Summer 2011Pages E25-E25 Metrics History Published online 1 July 2011 Published in print 1 July 2011

Consciousness is a central issue in neuroscience, however, we still lack a formal framework that can address the nature of the relationship between consciousness and its physical substrates. In this review, we provide a novel mathematical framework of category theory (CT), in which we can define and study the sameness between different domains of phenomena such as consciousness and its neural substrates. CT was designed and developed to deal with the relationships between various domains of phenomena. We introduce three concepts of CT which include (i) category; (ii) inclusion functor and expansion functor; and, most importantly, (iii) natural transformation between the functors. Each of these mathematical concepts is related to specific features in the neural correlates of consciousness (NCC). In this novel framework, we will examine two of the major theories of consciousness, integrated information theory (IIT) of consciousness and temporospatial theory of consciousness (TTC). We conclude that CT, especially the application of the notion of natural transformation, highlights that we need to go beyond NCC and unravels questions that need to be addressed by any future neuroscientific theory of consciousness.

Various psychopathologies of self-awareness, such as somatoparaphrenia and thought insertion in schizophrenia, might seem to threaten the viability of the higher-order thought (HOT) theory of consciousness since it requires a HOT about one’s own mental state to accompany every conscious state. The HOT theory of consciousness says that what makes a mental state a conscious mental state is that there is a HOT to the effect that “I am in mental state M” (Rosenthal D. Consciousness and mind. New York: Oxford University Press; 2005, Gennaro R. The consciousness paradox: consciousness, concepts, and higher-order thoughts. Cambridge, MA: The MIT Press; 2012. p. 127–9.). In a previous publication (Gennaro R. Somatoparaphrenia, anosognosia, and higher-order thoughts. In: Gennaro R, editor. Disturbed consciousness: new essays on psychopathology and theories of consciousness. Cambridge, MA: The MIT Press; 2015. p. 57–8), I argued that a HOT theorist can adequately respond to this concern with respect to somatoparaphrenia. Somatoparaphrenia is a “depersonalization disorder” which is characterized by the sense of alienation from parts of one’s body. It is a bizarre type of body delusion where one denies ownership of a limb or an entire side of one’s body. My focus in the chapter, however, is on “inserted thoughts” which is a common symptom of schizophrenia, although it will also be useful to contrast it with somatoparaphrenia. Schizophrenia is a mental disorder which most commonly manifests itself through auditory hallucinations, paranoid or bizarre delusions, or disorganized speech and thinking. Thought insertion is the delusion that some thoughts are not “one’s own” in some sense or are somehow being inserted into one’s mind by someone else. Graham and Stephens (When self-consciousness breaks: alien voices and inserted thoughts. Cambridge, MA: The MIT Press; 2000), for example, have suggested that thought insertion should be understood as alienated self-consciousness or meta-representation. I argue that HOT theory has nothing to fear from this phenomenon either and can consistently explain what happens in this admittedly unusual case.

Global gamma band synchronisation is perhaps the most extensively studied candidate for a Neural Correlate of Consciousness (NCC) . Yet despite numerous studies confirming its association with consciousness, it seems to be neither sufficient nor necessary for the presence of all subjective experiences. Analysis of gamma synchronisation studies suggests that it is a correlate of the initial binding of expected, attended, task-dependent contents of consciousness, whereas task-irrelevant contents do not seem to require gamma synchronisation. While discovery of such a content-related NCC is a remarkable achievement for the neurophysiological research of consciousness, it does not fully explain some of the fundamental structural properties of consciousness, namely the temporal and spatial integration of all available experiences into a coherent stream of consciousness. As an alternative, instead of focusing solely on the selected contents of consciousness, the neural mechanisms of the fundamental properties of consciousness could be studied by contrasting states of (un)consciousness. Recent research into the states of consciousness suggests that, for instance, informational complexity is a highly sensitive predictor of the presence of consciousness, possibly reflecting background structural properties of the unity of subjective experiences. As a limiting factor, though, such a state-related NCC does not seem to reflect the phenomenal diversity of the contents of consciousness. Arguably, these limitations could be overcome by devising experimental setups that would simultaneously probe the neural correlates of the contents and the state of consciousness.

The problem of consciousness is mostly regarded as identical to the mind-body problem. According to Chalmers’ philosophical arguments, the hard problem of consciousness lies in establishing and explaining the link between physical processes and conscious experiences, via psychological processes. A brief history of various theories of consciousness is given and a selection of theories are tested against Zeman’s three fundamental intuitions and Chalmers’ controversial zombie argument. The hard problem of consciousness is further described using Levine’s notion of an explanatory gap between physical matter and conscious experience, through the first and third persons. Various states, contents, levels and processes of consciousness are summarised, including Damasio and Meyer’s dual perspective for defining consciousness. Tart’s three definitions do not entirely describe altered states of consciousness. While the challenge of finding the core function of human and animal sleep remains unknown when tested under the null hypothesis, studies on the neural correlates of consciousness during meditation have revealed neuroplasticity effects. The synchrony of gamma brain oscillations reflecting various styles of meditation or attention, also known as the binding problem, may be related to conscious experiences. This binding problem with gamma brain oscillatory synchronization also arises in relation to sensory awareness or perception, affecting the perception of time and hallucinatory experiences in various disorders of consciousness such as severe schizophrenic and deja vu (in healthy or epileptic) patients. In conjunction with medication treatments, music therapy is often useful in accelerating the healing process in most such disorders of consciousness. It is still unknown how this sensory awareness to music is perceived in medicated patients suffering from disorders of consciousness. More clinically elusive are near death experiences, in which consciousness persists independently of brain function, where there is no scientific basis for such consciousness to exist and no physiological or psychological model that can explain it. Near death experiences can be regarded as a special state of consciousness, which provides further evidence that the consciousness problem may be very close to the mind-body problem that originates in Descartes’ classic theory of dualism and is transformed into Chalmers’ contemporary theory of natural dualism. The final section of this chapter offers an overview of all invited chapters.

One of the greatest challenges of consciousness research is to understand the relationship between consciousness and its implementing substrate. Current research into the neural correlates of consciousness regards the biological brain as being this substrate, but largely fails to clarify the nature of the brain-consciousness connection. A popular approach within this research is to construe brain-consciousness correlations in causal terms: the neural correlates of consciousness are the causes of states of consciousness. After introducing the notion of the neural correlate of consciousness, we argue (see Against Causal Accounts of NCCs) that this causal strategy is misguided. It implicitly involves an undesirable dualism of matter and mind and should thus be avoided. A non-causal account of the brain-mind correlations is to be preferred. We favor the theory of the identity of mind and brain, according to which states of phenomenal consciousness are identical with their neural correlates. Research into the neural correlates of consciousness and the theory of identity (in the philosophy of mind) are two major research paradigms that hitherto have had very little mutual contact. We aim to demonstrate that they can enrich each other. This is the task of the third part of the paper in which we show that the identity theory must work with a suitably defined concept of type. Surprisingly, neither philosophers nor neuroscientists have taken much care in defining this central concept; more often than not, the term is used only implicitly and vaguely. We attempt to open a debate on this subject and remedy this unhappy state of affairs, proposing a tentative hierarchical classification of phenomenal and neurophysiological types, spanning multiple levels of varying degrees of generality. The fourth part of the paper compares the theory of identity with other prominent conceptions of the mind-body connection. We conclude by stressing that scientists working on consciousness should engage more with metaphysical issues concerning the relation of brain processes and states of consciousness. Without this, the ultimate goals of consciousness research can hardly be fulfilled.

'Self' and the Problem of Consciousness

Attempts to create empirically based theories of consciousness face two kinds of obsta­cles. First, the dominant strategy of searching for the neural correlates of consciousness has been unsuccessful due to the lack of working hypotheses about their causal connec­tion with conscious states. The second obstacle is multiplicity of explananda – the lack of sufficient evidence for the belief that everything that we consider to be phenomena of consciousness or conscious states is ontologically unified. Perhaps, these issues are caused by the fact that the sciences of consciousness are devoid of an analog to the radio engineering level, which, in addition to theoretical electrodynamics, is essential for un­derstanding the principles of radio devices’ functioning. This level of knowledge should include a simplified ontology of the subject area, allowing one to isolate fundamental functional relationships at its algorithmic level. Considering the history of the sciences of consciousness and the specifics of their subject, the optimal candidate for the role of the engineering level of knowledge could be a computational approach, which would involve describing the subject as a combination of computational primitives that allow for the implementation of algorithms generating conscious states. Such an approach looks even more promising as non-computational theories of consciousness based on tradi­tional natural science paradoxically remain de facto metaphysical (speculative). In addi­tion to different approaches to the criteria for a “good” empirical (non-speculative) theory of consciousness, the paper provides an overview of a theory of consciousness based on the active inference hypothesis. The analysis of this theory suggests that a computa­tional model underlying a good theory of consciousness should not be deterministic, but probabilistic.

haracterizing Human-like Consciousness: An Integrative Approach

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<i>Human and Animal Minds: The Consciousness Questions Laid to Rest</i>

The Online Workshop on Theories of Consciousness (OWTC), a set of live online (text only) discussions carried out in 2009 at the site Nature.com, was an attempt to organize and find minimal agreement on the epistemological bases for scientific and philosophical research on the Theory of Consciousness. This paper covers the guidelines I proposed to the group; some issues discussed after the presentation of the first seminars on “Models of Conscousness”, by Anil Seth, and “Cognitive Theories of Consciousness”, by Vincent de Gardelle; as well as some discussions with the participants about these topics. Following the Concluding Remarks, I added an Epilogue written some years after the Workshop.Keywords: Consciousness; brain; physiology; epistemology; neurons; astrocytes; explanatory models.

Advances in Modeling Human Category Learning with DIVA Kenneth J. Kurtz (kkurtz@binghamton.edu) Department of Psychology, Binghamton University Binghamton, NY, USA 13902-6000 Keywords: category learning, classification, neural networks, autoencoder, computational models, selective attention, rules be made based on the ability of each category channel to accurately predict a single feature. This attention-like mechanism is completely independent of the learning process, but it allows the model to exploit its fast mastery of diagnostic within-categories statistical properties. With this design feature, DIVA yields impressive fits to a range of category learning phenomena that were previously thought to depend on attentionally-mediated similarity to reference points or the use of hybrid/separate systems including an explicit, independent rule-learning component. Further discussion will address novel predictions and results extending DIVA to the domains of inference learning, unsupervised learning, classification of continuous-dimension stimuli, and structured representations in learning and comparison (e.g., Kurtz, 2005; Kurtz & Loewenstein, 2007; Levering & Kurtz, 2006). Theoretical background The DIVA (Divergent Autoencoder) model of human category learning (Kurtz, 2007) brings renewed vitality to a set of compelling explanatory principles that had fallen out of favor after failing to account for benchmark learning phenomena like the relative ease of acquisition of elemental category structures (Shepard, Hovland, & Jenkins, 1961). Core principles that distinguish DIVA from other error-driven adaptive network models like ALCOVE (Kruschke, 1992) and SUSTAIN (Love, Gureckis, & Medin, 2004) are: (1) a learning mechanism based on abstraction/recoding of inputs, as opposed to selective attention and association with fixed item representations; (2) representing knowledge about category instances in the connection weights, rather than in localist internal nodes of a network; (3) learning and classifying based on reconstructive success (goodness-of-fit) using an auto-associative mechanism that preserves, distorts, and infers features of the input in light of category knowledge, as opposed to computing the match between the input and reference points (exemplars, prototypes, rules). The DIVA model incorporates these principles by treating categories as coordinated statistical models – each category is learned as a channel of an autoencoder network trained with standard backpropagation. The feedforward network consists of a set of nodes encoding the input features, a single set of hidden nodes for recoding all inputs, and distinct (divergent) sets of output nodes that generate a decoding or reconstruction of the input features in light of each possible category. The relative success of reconstruction on each channel determines the probability of classification. This learning process implements a modified form of principle components analysis (PCA) in which the recoding weights compactly encode the important variability in the training set and the decoding weights yield a construal of the input features in terms of each category. In sum, the system assesses how well an input accords with the statistical model underlying each category and interprets A/B classification as follows: To what extent is it possible to make sense of the available data as being the features of an A versus as being the features of a B? References Kruschke, J. K. (1992). ALCOVE: An exemplar-based connectionist model of category learning. Psychological Review, 99, 22-44. Kurtz, K.J. (2005). On knowing the category before knowing the features. Proceedings of the 27 th Annual Conference of the Cognitive Science Society. Mahwah, NJ: Lawrence Erlbaum Associates. Kurtz, K.J. (2005). Abstraction versus selective attention in classification learning. Proceedings of the 27 th Annual Conference of the Cognitive Science Society. Mahwah, NJ: Lawrence Erlbaum Associates. Kurtz, K.J. (2005). Re-representation in comparison: Building an empirical case. Journal of Experimental & Theoretical Artificial Intelligence, 17, 447-459. Kurtz, K.J. (2007). The divergent autoencoder (DIVA) model of category learning. Psychonomic Bulletin & Review, 14, Kurtz, K.J., & Loewenstein, J. (2007). Converging on a new role for analogy in problem solving and retrieval: When two problems are better than one. Memory & Cognition, Levering, K., & Kurtz, K.J. (2006). The influence of learning to distinguish categories on graded structure. Proceedings of the 28 th Annual Conference of the Cognitive Science Society. Mahwah, NJ: Lawrence Erlbaum Associates. Love, B.C., Medin, D.L, & Gureckis, T.M (2004). SUSTAIN: A network model of category learning. Psychological Review, 111, 309-332. Shepard, R.N., Hovland, C.L., & Jenkins, H.M. (1961). Learning and memorization of classifications. Psychological Monographs, 75 (13, Whole No. 517). A new design principle and new findings This presentation focuses on a new design feature, as well as simulation results, that importantly extend the depth and breadth of the DIVA account. Specifically, an additional mechanism for generating classification responses based on the reconstructive outputs has been developed. Rather than assessing reconstructive success across all features, the use of unidimensional evaluation allows classification decisions to

Jean-Paul Sartre believed that consciousness entails self-consciousness, or, even more strongly, that consciousnessisself-consciousness. As Kathleen Wider puts it in her terrific bookThe Bodily Nature of Consciousness: Sartre and Contemporary Philosophy of Mind,‘all consciousness is, by its very nature, self-consciousness.’ I share this view with Sartre and have elsewhere argued for it at length. My overall aim in this paper is to examine Sartre's theory of consciousness against the background of the so-called ‘higher-order thought theory of consciousness’ (the HOT theory) which, in turn, will shed light on the structure of conscious mental states as well as on Sartre's theory of (self-) consciousness and reflection. Another goal of this paper is, following Wider, to show how Sartre's views can be understood from a contemporary analytic perspective. Sartre's theory of consciousness is often confusing to the so-called ‘analytic Anglo-American’ tradition, but I attempt to show how this obstacle can be overcome against the backdrop of a specific contemporary theory of consciousness.