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Cognitive Models of Consciousness

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  1. Igor L. Aleksander (2007). Why Axiomatic Models of Being Conscious? Journal of Consciousness Studies 14 (7):15-27.
    This paper looks closely at previously enunciated axioms that specifically include phenomenology as the sense of a self in a perceptual world. This, we suggest, is an appropriate way of doing science on a first-person phenomenon. The axioms break consciousness down into five key components: presence, imagination, attention, volition and emotions. The paper examines anew the mechanism of each and how they interact to give a single sensation. An abstract architecture, the Kernel Architecture, is introduced as a starting point for (...)
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  2. Bernard J. Baars (2007). The Global Workspace Theory of Consciousness. In Max Velmans & Susan Schneider (eds.), The Blackwell Companion to Consciousness. Blackwell.
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  3. Bernard J. Baars (2006). Global Workspace Theory of Consciousness: Toward a Cognitive Neuroscience of Human Experience? In Steven Laureys (ed.), Boundaries of Consciousness. Elsevier.
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  4. Bernard J. Baars (2002). The Conscious Access Hypothesis: Origins and Recent Evidence. Trends in Cognitive Sciences 6 (1):47-52.
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  5. Bernard J. Baars (1998). Metaphors of Consciousness and Attention in the Brain. Trends in Neurosciences 21:58-62.
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  6. Bernard J. Baars (1997). In the Theater of Consciousness: The Workspace of the Mind. Oxford University Press.
    The study of conscious experience has seen remarkable strides in the last ten years, reflecting important technological breakthroughs and the enormous efforts of researchers in disciplines as varied as neuroscience, cognitive science, and philosophy. Although still embroiled in debate, scientists are now beginning to find common ground in their understanding of consciousness, which may pave the way for a unified explanation of how and why we experience and understand the world around us. Written by eminent psychologist Bernard J. Baars, Inside (...)
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  7. Bernard J. Baars (1988). A Cognitive Theory of Consciousness. Cambridge University Press.
    Conscious experience is one of the most difficult and thorny problems in psychological science. Its study has been neglected for many years, either because it was thought to be too difficult, or because the relevant evidence was thought to be poor. Bernard Baars suggests a way to specify empirical constraints on a theory of consciousness by contrasting well-established conscious phenomena - such as stimulus representations known to be attended, perceptual, and informative - with closely comparable unconscious ones - such as (...)
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  8. Bernard J. Baars, Thomas Zoega Ramsoy & Steven Laureys (2003). Brain, Conscious Experience, and the Observing Self. Trends in Neurosciences 26 (12):671-5.
    Conscious perception, like the sight of a coffee cup, seems to involve the brain identifying a stimulus. But conscious input activates more brain regions than are needed to identify coffee cups and faces. It spreads beyond sensory cortex to frontoparietal association areas, which do not serve stimulus identification as such. What is the role of those regions? Parietal cortex support the ‘first person perspective’ on the visual world, unconsciously framing the visual object stream. Some prefrontal areas select and interpret conscious (...)
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  9. John Barresi & John R. Christie (2002). Consciousness and Information Processing: A Reply to Durgin. Consciousness and Cognition 11 (2):372-374.
    Durgin's (2002) commentary on our article provides us with an opportunity to look more closely at the relationship between information processing and consciousness. In our article we contrasted the information processing approach to interpreting our data, with our own 'scientific' approach to consciousness. However, we should point out that, on our view, information processing as a methodology is not by itself in conflict with the scientific study of consciousness - indeed, we have adopted this very methodology in our experiments, which (...)
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  10. William P. Bechtel (1995). Consciousness: Perspectives From Symbolic and Connectionist AI. Neuropsychologia.
    For many people, consciousness is one of the defining characteristics of mental states. Thus, it is quite surprising that consciousness has, until quite recently, had very little role to play in the cognitive sciences. Three very popular multi-authored overviews of cognitive science, Stillings et al. [33], Posner [26], and Osherson et al. [25], do not have a single reference to consciousness in their indexes. One reason this seems surprising is that the cognitive revolution was, in large part, a repudiation of (...)
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  11. R. A. Brown (1997). Consciousness in a Self-Learning, Memory-Controlled, Compound Machine. Neural Networks 10:1333-85.
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  12. C. Browne, Robert W. Evans, N. Sales & Igor L. Aleksander (1997). Consciousness and Neural Cognizers: A Review of Some Recent Approaches. Neural Networks 10:1303-1316.
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  13. M. Cabanac (1996). On the Origin of Consciousness, a Postulate, and its Corollary. Neuroscience and Biobehavioral Reviews 20:33-40.
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  14. William H. Calvin (1998). Competing for Consciousness: A Darwinian Mechanism at an Appropriate Level of Explanation. Journal of Consciousness Studies 5 (4):389-404.
    Treating consciousness as awareness or attention greatly underestimates it, ignoring the temporary levels of organization associated with higher intellectual function (syntax, planning, logic, music). The tasks that require consciousness tend to be the ones that demand a lot of resources. Routine tasks can be handled on the back burner but dealing with ambiguity, groping around offline, generating creative choices, and performing precision movements may temporarily require substantial allocations of neocortex. Here I will attempt to clarify the appropriate levels of explanation (...)
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  15. Fu Chang, A Theory of Consciousness.
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  16. Jonathan D. Cohen & Jonathan W. Schooler (1997). Scientific Approaches to Consciousness. Lawrence Erlbaum.
  17. N. D. Cook (1999). Simulating Consciousness in a Bilateral Neural Network: ''Nuclear'' and ''Fringe'' Awareness. Consciousness and Cognition 8 (1):62-93.
    A technique for the bilateral activation of neural nets that leads to a functional asymmetry of two simulated ''cerebral hemispheres'' is described. The simulation is designed to perform object recognition, while exhibiting characteristics typical of human consciousness-specifically, the unitary nature of conscious attention, together with a dual awareness corresponding to the ''nucleus'' and ''fringe'' described by William James (1890). Sensory neural nets self-organize on the basis of five sensory features. The system is then taught arbitrary symbolic labels for a small (...)
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  18. Rodney M. J. Cotterill (1997). On the Mechanism of Consciousness. Journal of Consciousness Studies 4 (3):231-48.
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  19. L. Andrew Coward & Ron Sun (2004). Criteria for an Effective Theory of Consciousness and Some Preliminary Attempts. Consciousness and Cognition 13 (2):268-301.
    In the physical sciences a rigorous theory is a hierarchy of descriptions in which causal relationships between many general types of entity at a phenomenological level can be derived from causal relationships between smaller numbers of simpler entities at more detailed levels. The hierarchy of descriptions resembles the modular hierarchy created in electronic systems in order to be able to modify a complex functionality without excessive side effects. Such a hierarchy would make it possible to establish a rigorous scientific theory (...)
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  20. Stanislas Dehaene, Michel Kerszberg & Jean-Pierre Changeux (2001). A Neuronal Model of a Global Workspace in Effortful Cognitive Tasks. Pnas 95 (24):14529-14534.
  21. D. C. Dennett & C. F. Westbury (1999). Stability is Not Intrinsic. Behavioral and Brain Sciences 22 (1):153-154.
    A pure vehicle theory of the contents of consciousness is not possible. While it is true that hard-wired tacit representations are insufficient as content-vehicles, not all tacit representations are hard-wired. The definition of stability offered for patterns of neural activation is not well-motivated, and too simplistic. We disagree in particular with the assumption that stability within a network is purely intrinsic to that network. Many complex forms of stability within a network are apparent only when interpreted by something external to (...)
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  22. José-Luis Díaz (1997). A Patterned Process Approach to Brain, Consciousness, and Behavior. Philosophical Psychology 10 (2):179-195.
    The architecture of brain, consciousness, and behavioral processes is shown to be formally similar in that all three may be conceived and depicted as Petri net patterned processes structured by a series of elements occurring or becoming active in stochastic succession, in parallel, with different rhythms of temporal iteration, and with a distinct qualitative manifestation in the spatiotemporal domain. A patterned process theory is derived from the isomorphic features of the models and contrasted with connectionist, dynamic system notions. This empirically (...)
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  23. Philip Dorrell, Computation Vs. Feelings and the Production/Judgment Model.
    Functional versus Subjective Consciousness The Example of Pain Dieting and Free Will The Production/Judgement Model Judgement is not Reward Feelings are Judgements Low-Bandwidth Channels Candidate Neural Control Channels Timing of Intention and Action Conclusion References Abstract.
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  24. Alexander A. Fingelkurts, Andrew A. Fingelkurts, Sergio Bagnato, Cristina Boccagni & Giuseppe Galardi (forthcoming). EEG Oscillatory States as Neuro-Phenomenology of Consciousness as Revealed From Patients in Vegetative and Minimally Conscious States. Consciousness and Cognition.
    The value of resting electroencephalogram (EEG) in revealing neural constitutes of consciousness (NCC) was examined. We quantified the dynamic repertoire, duration and oscillatory type of EEG microstates in eyes-closed rest in relation to the degree of expression of clinical self-consciousness. For NCC a model was suggested that contrasted normal, severely disturbed state of consciousness and state without consciousness. Patients with disorders of consciousness were used. Results suggested that the repertoire, duration and oscillatory type of EEG microstates in resting condition quantitatively (...)
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  25. Stan Franklin, Conscious Software: A Computational View of Mind.
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  26. Stan Franklin, Action Selection and Language Generation in "Conscious" Software Agents.
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  27. Stan Franklin & Art Graesser (1999). A Software Agent Model of Consciousness. Consciousness And Cognition 8 (3):285-301.
    Baars (1988, 1997) has proposed a psychological theory of consciousness, called global workspace theory. The present study describes a software agent implementation of that theory, called ''Conscious'' Mattie (CMattie). CMattie operates in a clerical domain from within a UNIX operating system, sending messages and interpreting messages in natural language that organize seminars at a university. CMattie fleshes out global workspace theory with a detailed computational model that integrates contemporary architectures in cognitive science and artificial intelligence. Baars (1997) lists the psychological (...)
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  28. Richard L. Gregory (1984). Is Consciousness Sensational Inferences? Perception 13:641-6.
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  29. Valerie Gray Hardcastle (1995). A Critique of Information Processing Theories of Consciousness. Minds and Machines 5 (1):89-107.
    Information processing theories in psychology give rise to executive theories of consciousness. Roughly speaking, these theories maintain that consciousness is a centralized processor that we use when processing novel or complex stimuli. The computational assumptions driving the executive theories are closely tied to the computer metaphor. However, those who take the metaphor serious — as I believe psychologists who advocate the executive theories do — end up accepting too particular a notion of a computing device. In this essay, I examine (...)
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  30. Stevan Harnad (1982). Consciousness: An Afterthought. Cognition and Brain Theory 5:29-47.
    There are many possible approaches to the mind/brain problem. One of the most prominent, and perhaps the most practical, is to ignore it.
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  31. E. Harth (1995). The Sketchpad Model: A Theory of Consciousness, Perception, and Imagery. Consciousness and Cognition 4:346-68.
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  32. M. Ito, Y. Miyashita & Edmund T. Rolls (1997). Cognition, Computation, and Consciousness. Oxford University Press.
  33. Ray S. Jackendoff (1987). Consciousness and the Computational Mind. MIT Press.
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  34. Michael H. Joseph & Samuel R. H. Joseph (2001). The Contents of Consciousness: From C to Shining C++. Behavioral and Brain Sciences 24 (1):188-189.
    We suggest that consciousness (C) should be addressed as a multilevel concept. We can provisionally identify at least three, rather than two, levels: Gray's system should relate at least to the lowest of these three levels. Although it is unlikely to be possible to develop a behavioural test for C, it is possible to speculate as to the evolutionary advantages offered by C and how C evolved through succeeding levels. Disturbances in the relationships between the levels of C could underlie (...)
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  35. Andrei G. Khromov (2001). Logical Self-Reference as a Model for Conscious Experience. Journal of Mathematical Psychology 45 (5):720-731.
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  36. Joan Lesley (2006). Awareness is Relative: Dissociation as the Organisation of Meaning. Consciousness and Cognition 15 (3):593-604.
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  37. D. Levine & W. Elsberry (1997). Optimality in Biological and Artificial Networks? Lawrence Erlbaum.
    This book is the third in a series based on conferences sponsored by the Metroplex Institute for Neural Dynamics, an interdisciplinary organization of neural ...
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  38. Dan Lloyd (1996). Consciousness, Connectionism, and Cognitive Neuroscience: A Meeting of the Minds. Philosophical Psychology 9 (1):61-78.
    Accounting for phenomenal structure—the forms, aspects, and features of conscious experience—poses a deep challenge for the scientific study of consciousness, but rather than abandon hope I propose a way forward. Connectionism, I argue, offers a bi-directional analogy, with its oft-noted “neural inspiration” on the one hand, and its largely unnoticed capacity to illuminate our phenomenology on the other. Specifically, distributed representations in a recurrent network enable networks to superpose categorical, contextual, and temporal information on a specific input representation, much as (...)
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  39. Dan Lloyd (1995). Consciousness: A Connectionist Manifesto. Minds and Machines 5 (2):161-85.
    Connectionism and phenomenology can mutually inform and mutually constrain each other. In this manifesto I outline an approach to consciousness based on distinctions developed by connectionists. Two core identities are central to a connectionist theory of consciouness: conscious states of mind are identical to occurrent activation patterns of processing units; and the variable dispositional strengths on connections between units store latent and unconscious information. Within this broad framework, a connectionist model of consciousness succeeds according to the degree of correspondence between (...)
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  40. Tiago V. Maia & Axel Cleeremans (2005). Consciousness: Converging Insights From Connectionist Modeling and Neuroscience. Trends in Cognitive Sciences 9 (8):397-404.
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  41. D. W. Mathis & M. Moxer (1995). On the Computational Utility of Consciousness. In G. Tesauro, D. Touretzky & T. Leen (eds.), Advances in Neural Information Processing Systems 7. MIT Press.
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  42. Josh McDermott (1995). Global Workspace Theory: Consciousness Explained? Harvard Brain 2 (1).
    The subject of consciousness, long shunned by mainstream psychology and the scientific community, has over the last two decades become a legitimate topic of scientific research. One of the most thorough attempts to formulate a theory of consciousness has come from Bernard Baars, a psychologist working at the Wright Institute. Baars proposes that consciousness is the result of a Global Workspace in the brain that distributes information to the huge number of parallel unconscious processors that form the rest of the (...)
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  43. George McKee, The Engine of Awareness: Autonomous Synchronous Representations.
    Objections to functional explanations of awareness assert that although functional systems may be adequate to explain behavior, including verbal behavior consisting of assertions of awareness by an individual, they cannot provide for the existence of phenomenal awareness. In this paper, a theory of awareness is proposed that counters this assertion by incorporating two advances: (1) a formal definition of representation, expressed in a functional notation: Newell's Representation Law, and 2) the introduction of real time into the analysis of awareness. This (...)
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  44. Donald Michie (1995). Consciousness as an Engineering Issue, Part. Journal of Consciousness Studies 2 (1):52-66.
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  45. Ezequiel Morsella (2005). The Function of Phenomenal States: Supramodular Interaction Theory. Psychological Review 112 (4):1000-1021.
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  46. Gerard O'Brien & Jonathan Opie (2001). Connectionist Vehicles, Structural Resemblance, and the Phenomenal Mind. Communication and Cognition (Special Issue) 34 (1-2):13-38.
    We think the best prospect for a naturalistic explanation of phenomenal consciousness is to be found at the confluence of two influential ideas about the mind. The first is the _computational _ _theory of mind_: the theory that treats human cognitive processes as disciplined operations over neurally realised representing vehicles.1 The second is the _representationalist theory of _ _consciousness_: the theory that takes the phenomenal character of conscious experiences (the “what-it-is-likeness”) to be constituted by their representational content.2 Together these two (...)
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  47. Gerard O'Brien & Jonathan Opie (1999). Putting Content Into a Vehicle Theory of Consciousness. Behavioral and Brain Sciences 22 (1):175-196.
    The connectionist vehicle theory of phenomenal experience in the target article identifies consciousness with the brain’s explicit representation of information in the form of stable patterns of neural activity. Commentators raise concerns about both the conceptual and empirical adequacy of this proposal. On the former front they worry about our reliance on vehicles, on representation, on stable patterns of activity, and on our identity claim. On the latter front their concerns range from the general plausibility of a vehicle theory to (...)
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  48. Gerard O'Brien & Jonathan Opie (1999). A Connectionist Theory of Phenomenal Experience. 22 (1):127-48.
    When cognitive scientists apply computational theory to the problem of phenomenal consciousness, as many of them have been doing recently, there are two fundamentally distinct approaches available. Either consciousness is to be explained in terms of the nature of the representational vehicles the brain deploys; or it is to be explained in terms of the computational processes defined over these vehicles. We call versions of these two approaches vehicle and process theories of consciousness, respectively. However, while there may be space (...)
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  49. Jonathan Opie (2000). Consciousness in the Loops. Review of Cotterill, Enchanted Looms: Conscious Networks in Brains and Computers. Metascience 9 (2):277-82.
    Consciousness is a pretty sexy topic right now, as the plethora of recent books on the subject demonstrate. Everyone is having a go at it: philosophers, psychologists, neuroscientists and physicists, to mention just a few. And for every discipline or sub-discipline that pretends to some insight on the matter we find not only a different explanatory strategy, but a different take on the explanandum – there is widespread disagreement about _what_ a theory of consciousness should actually explain. However, one thing (...)
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  50. Mitch Parsell (2005). Review of P.O. Haikonen's The Cognitive Approach to Conscious Machines. Psyche 11 (2).
    Haikonen (2003) is an attempt to explicate a platform for modelling consciousness. The book sets out the foundational concepts behind Haikonen’s work in the area and proposes a particular modelling environment. This is developed in three parts: part 1 offers a brief analysis of the state of play in cognitive modelling; part 2 an extended treatment of the phenomena to be explained; part 3 promises a synthesis of the two preceding discussions to provide the necessary background and detail for the (...)
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  51. R. H. Phaf & G. Wolters (1997). A Constructivist and Connectionist View on Conscious and Nonconscious Processes. Philosophical Psychology 10 (3):287-307.
    Recent experimental findings reveal dissociations of conscious and nonconscious performance in many fields of psychological research, suggesting that conscious and nonconscious effects result from qualitatively different processes. A connectionist view of these processes is put forward in which consciousness is the consequence of construction processes taking place in three types of working memory in a specific type of recurrent neural network. The recurrences arise by feeding back output to the input of a central (representational) network. They are assumed to be (...)
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  52. A. Restian (1981). Informational Analysis of Consciousness. International Journal of Neuroscience 13:229-37.
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  53. Hugh M. Roberts (1968). Consciousness in Animals and Automata. Psychological Reports 22:1226-28.
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  54. Henry L. I. Roediger & Fergus I. M. Craik (1989). Varieties of Memory and Consciousness: Essays in Honor of Endel Tulving. Lawrence Erlbaum.
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  55. Edmund T. Rolls (1997). Consciousness in Neural Networks? Neural Networks 10:1227-1303.
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  56. T. Shallice (1972). Dual Functions of Consciousness. Psychological Review 79:383-93.
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  57. Murray Shanahan (2010). Embodiment and the Inner Life: Cognition and Consciousness in the Space of Possible Minds. Oxford University Press.
    From this post-reflective point of view, the book argues for an intimate relationship between cognition, sensorimotor embodiment, and the integrative character ...
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  58. Murray Shanahan (2006). A Cognitive Architecture That Combines Internal Simulation with a Global Workspace. Consciousness and Cognition 15 (2):433-449.
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  59. Murray Shanahan (2005). Global Access, Embodiment, and the Conscious Subject. Journal of Consciousness Studies 12 (12):46-66.
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  60. Murray Shanahan & Bernard J. Baars (2005). Applying Global Workspace Theory to the Frame Problem. Cognition 98 (2):157-176.
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  61. Serge P. Shohov (2002). Advances in Psychology Research. Nova Science Publishers.
    "Advances in Psychology Research" presents original research results on the leading edge of psychology.
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  62. G. Sommerhoff (1996). Consciousness as an Internal Integrating System. Journal of Consciousness Studies 3:139-57.
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  63. G. Sommerhoff & Karl F. MacDorman (1994). An Account of Consciousness in Physical and Functional Terms: A Target for Research in the Neurosciences. Integrative Physiological and Behavioral Science 29:151-81.
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  64. B. L. Strehler (1989). Monitors: Key Mechanisms and Roles in the Development and Aging of the Consciousness and Self. Mechanisms of Ageing and Development 47:85-132.
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  65. Ron Sun (2004). Criteria for an Effective Theory of Consciousness and Some Preliminary Attempts. Consciousness and Cognition 13 (2):268-301.
    In the physical sciences a rigorous theory is a hierarchy of descriptions in which causal relationships between many general types of entity at a phenomenological level can be derived from causal relationships between smaller numbers of simpler entities at more detailed levels. The hierarchy of descriptions resembles the modular hierarchy created in electronic systems in order to be able to modify a complex functionality without excessive side effects. Such a hierarchy would make it possible to establish a rigorous scientific theory (...)
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  66. Ron Sun (2001). Computation, Reduction, and Teleology of Consciousness. Cognitive Systems Research 1 (1):241-249.
    This paper aims to explore mechanistic and teleological explanations of consciousness. In terms of mechanistic explanations, it critiques various existing views, especially those embodied by existing computational cognitive models. In this regard, the paper argues in favor of the explanation based on the distinction between localist (symbolic) representation and distributed representation (as formulated in the connectionist literature), which reduces the phenomenological difference to a mechanistic difference. Furthermore, to establish a teleological explanation of consciousness, the paper discusses the issue of the (...)
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  67. Ron Sun (1999). Accounting for the Computational Basis of Consciousness: A Connectionist Approach. Consciousness and Cognition 8 (4):529-565.
    This paper argues for an explanation of the mechanistic (computational) basis of consciousness that is based on the distinction between localist (symbolic) representation and distributed representation, the ideas of which have been put forth in the connectionist literature. A model is developed to substantiate and test this approach. The paper also explores the issue of the functional roles of consciousness, in relation to the proposed mechanistic explanation of consciousness. The model, embodying the representational difference, is able to account for the (...)
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  68. Ron Sun (1997). Learning, Action, and Consciousness: A Hybrid Approach Toward Modeling Consciousness. Neural Networks 10:1317-33.
    _role, especially in learning, and through devising hybrid neural network models that (in a qualitative manner) approxi-_ _mate characteristics of human consciousness. In doing so, the paper examines explicit and implicit learning in a variety_ _of psychological experiments and delineates the conscious/unconscious distinction in terms of the two types of learning_ _and their respective products. The distinctions are captured in a two-level action-based model C_larion_. Some funda-_ _mental theoretical issues are also clari?ed with the help of the model. Comparisons with (...)
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  69. N. E. Sviderskaya (1991). Consciousness and Information Selection. Neuroscience and Behavioral Physiology 21:526-31.
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  70. John G. Taylor, Modeling Consciousness.
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  71. John G. Taylor (1998). Constructing the Relational Mind. Psyche 4 (10).
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  72. John G. Taylor (1997). Neural Networks for Consciousness. Neural Networks 10:1207-27.
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  73. John G. Taylor (1996). A Competition for Consciousness? Neurocomputing 11:271-96.
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  74. John G. Taylor & H. Mueller-Gaertner (1997). Non-Invasive Analysis of Awareness. Neural Networks 10:1185-1194.
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  75. Kenneth A. Taylor (2001). Applying Continuous Modelling to Consciousness. Journal of Consciousness Studies 8 (2):45-60.
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  76. G. Tesauro, D. Touretzky & T. Leen (1995). Advances in Neural Information Processing Systems 7. MIT Press.
    November 28-December 1, 1994, Denver, Colorado NIPS is the longest running annual meeting devoted to Neural Information Processing Systems.
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  77. Frederick Toates (2006). A Model of the Hierarchy of Behaviour, Cognition, and Consciousness. Consciousness and Cognition 15 (1):75-118.
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  78. Giulio Srinivasan Tononi (2007). The Information Integration Theory of Consciousness. In Max Velmans & Susan Schneider (eds.), The Blackwell Companion to Consciousness. Blackwell.
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  79. Giulio Srinivasan Tononi (2006). Consciousness, Information Integration and the Brain. In Steven Laureys (ed.), Boundaries of Consciousness. Elsevier.
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  80. Cees van Leeuwen (2007). What Needs to Emerge to Make You Conscious? Journal of Consciousness Studies 14 (1):115-136.
    Perceptual experience can be explained by contextualized brain dynamics. An inner loop of ongoing activity within the brain produces dynamic patterns of synchronization and de- synchronization that are necessary, but not sufficient, for visual experience. This inner loop is controlled by evolution, development, socialization, learning, task and perception- action contingencies, which constitute an outer loop. This outer loop is sufficient, but not necessary, for visual experience. Jointly, the inner and outer loop may offer sufficient and necessary conditions for the emergence (...)
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  81. Max Velmans (1996). The Science of Consciousness: Psychological, Neuropsychological, and Clinical Reviews. Routledge.
    Of all the problems facing science none are more challenging yet fascinating than those posed by consciousness. In The Science of Consciousness leading researchers examine how consciousness is being investigated in the key areas of cognitive psychology, neuropsychology and clinical psychology. Within cognitive psychology, special focus is given to the function of consciousness, and to the relation of conscious processing to nonconscious processing in perception, learning, memory and information dissemination. Neuropsychology includes examination of the neural conditions for consciousness and the (...)
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  82. Kunio Yasue, Marj Jibu & Tarcisio Della Senta (2002). No Matter, Never Mind: Proceedings of Toward a Science of Consciousness: Fundamental Approaches (Tokyo '99). John Benjamins.
    For brain science, the binary code is embodied in the all or none characteristic of nerve impulses by which one part of the brain communicates with another. ...
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  83. Philip David Zelazo, Morris Moscovitch & Evan Thompson (2007). The Cambridge Handbook of Consciousness. Cambridge University Press.
    The Cambridge Handbook of Consciousness is the first of its kind in the field, and its appearance marks a unique time in the history of intellectual inquiry on the topic. After decades during which consciousness was considered beyond the scope of legitimate scientific investigation, consciousness re-emerged as a popular focus of research towards the end of the last century, and it has remained so for nearly 20 years. There are now so many different lines of investigation on consciousness that the (...)
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