David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jack Alan Reynolds
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In Steven Laureys (ed.), The Boundaries of Consciousness: Neurobiology and Neuropathology: Progress in Brain Research. Elsevier (2006)
Over the past few years numerous proposals have appeared that attempt to characterize consciousness in terms of what could be called its computational correlates: Principles of information processing with which to characterize the differences between conscious and unconscious processing. Proposed computational correlates include architectural specialization (such as the involvement of specific regions of the brain in conscious processing), properties of representations (such as their stability in time or their strength), and properties of specific processes (such as resonance, synchrony, interactivity, or information integration). In exactly the same way as one can engage in a search for the neural correlates of consciousness, one can thus search for the computational correlates of consciousness. The most direct way of doing is to contrast models of conscious versus unconscious information processing. In this paper, I review these developments and illustrate how computational modeling of specific cognitive processes can be useful in exploring and in formulating putative computational principles through which to capture the differences between conscious and unconscious cognition. What can be gained from such approaches to the problem of consciousness is an understanding of the function it plays in information processing and of the mechanisms that subtend it. Here, I suggest that the central function of consciousness is to make it possible for cognitive agents to exert ?exible, adaptive control over behavior. From this perspective, consciousness is best characterized as involving (1) a graded continuum de?ned over quality of representation, such that availability to consciousness and to cognitive control correlates with properties of representation, and (2) the implication of systems of meta-representations
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Nick Reed, Peter McLeod & Zoltan Dienes (2010). Implicit Knowledge and Motor Skill: What People Who Know How to Catch Don't Know. Consciousness and Cognition 19 (1):63-76.
Nir Fresco (2010). Explaining Computation Without Semantics: Keeping It Simple. [REVIEW] Minds and Machines 20 (2):165-181.
Vincian Gaillard, Muriel Vandenberghe, Arnaud Destrebecqz & Axel Cleeremans (2006). First and Third-Person Approaches in Implicit Learning Research. Consciousness and Cognition 15 (4):709-722.
Luis M. Augusto (2013). Unconscious Representations 1: Belying the Traditional Model of Human Cognition. [REVIEW] Axiomathes 23 (4):1-19.
Jean-Christophe Sarrazin, Axel Cleeremans & Patrick Haggard (2008). How Do We Know What We Are Doing?: Time, Intention and Awareness of Action. Consciousness and Cognition 17 (3):602-615.
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