Online research in philosophy

As stressed by Perruchet & Vinter, the SOC model echoes Johnson-Laird's mental model theory. Indeed, the latter rejects rule-based processing and assumes that reasoning is achieved through the manipulation of conscious representations. However, the mental model theory as well as its modified versions resorts to the abstraction of complex schemas and some form of implicit logic that seems incompatible with the SOC approach.

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.

The self-organizing consciousness (SOC) is not sufficient to account for young children's ability to acquire complex rules and word-object mappings. First, the attention-association cycles suggested by the SOC are unlikely to happen because recurrence of particular stimulus properties usually disengages the attention of an observer. Second, “primitive processors” preinstalled in the system make the SOC unnecessarily complex.

Through the concept of self-organizing consciousness (SOC), we posit that the dynamic of the mind stems from the recurrent interplay between the properties of conscious experiences and the properties of the world, hence making it unnecessary to postulate the existence of an unconscious mental level. In contrast, arguments are provided by commentators for the need for a functional level of organization located between the neural and the conscious. Other commentaries challenge us concerning the ability of our model to account for specific phenomena in the domains of language, reasoning, incubation, and creativity. The possibility of unconscious semantic access and other alleged instances of adapted performance in the absence of any conscious counterpart are also put forth as evidence against our view. Our response emphasizes the fact that opponents to our model often present as factual, theory-free evidence which is in fact nothing more than the postulates underlying the classical computational framework.

While the study of implicit learning is nothing new, the field as a whole has come to embody — over the last decade or so — ongoing questioning about three of the most fundamental debates in the cognitive sciences: The nature of consciousness, the nature of mental representation (in particular the difficult issue of abstraction), and the role of experience in shaping the cognitive system. Our main goal in this chapter is to offer a framework that attempts to integrate current thinking about these three issues in a way that specifically links consciousness with adaptation and learning. Our assumptions about this relationship are rooted in further assumptions about the nature of processing and of representation in cognitive systems. When considered together, we believe that these assumptions offer a new perspective on the relationships between conscious and unconscious processing and on the function of consciousness in cognitive systems.

In this chapter, I sketch a conceptual framework which takes it as a starting point that conscious and unconscious cognition are rooted in the same set of interacting learning mechanisms and representational systems. On this view, the extent to which a representation is conscious depends in a graded manner on properties such as its stability in time or its strength. Crucially, these properties are accrued as a result of learning, which is in turn viewed as a mandatory process that always accompanies information processing. From this perspective, consciousness is best characterized as involving (1) a graded continuum defined over “quality of representation”, such that availability to consciousness and to cognitive control correlates with quality , and (2) the implication of systems of metarepresentations. A first implication of these ideas is that the main function of consciousness is to make flexible, adaptive control over behavior possible. A second, much more speculative implication, is that we learn to be conscious. This I call the “radical plasticity thesis” — the hypothesis that consciousness emerges in systems capable not only of learning about their environment, but also about their own internal representations of it.

We propose that the isomorphism generally observed between the representations composing our momentary phenomenal experience and the structure of the world is the end-product of a progressive organization that emerges thanks to elementary associative processes that take our conscious representations themselves as the stuff on which they operate, a thesis that we summarize in the concept of Self-Organizing Consciousness (SOC). Key Words: Associative learning; automatism; consciousness; development; implicit learning; incubation; language; mental representation; perception; phenomenal experience.

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Perruchet and Vinter stop short of fully embracing the implications of their own SOC framework and hence end up defending an implausible perspective on consciousness. We suggest instead that consciousness should be viewed as a graded dimension defined over quality of representation. This graded perspective eliminates the most problematic aspects of the cognitive unconscious without denying its existence altogether.