Online research in philosophy

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 study of preconscious versus conscious processing has an extensive history in cognitive psychology, dating back to the writings of William James. Much of the experimental work on this issue has focused on perception, conceived of as input analysis, and on the relation of consciousness to attentional processing. The present paper examines when input analysis becomes conscious from the perspectives of cognitive modelling, methodology, and a more detailed understanding of what is meant by "conscious processing." Current evidence suggests that perception becomes conscious at a late-arising stage of focal-attentive processing concerned with information integration and dissemination. Reliable criteria for determining when perception becomes conscious combine the evidence of "first-person," phenomenological reports with "third-person" functional dissociations between preconscious and conscious processing. There are three, distinct senses in which a process may be said to be "conscious." It might be "conscious" (a) in the sense that one is conscious of the process, (b) in the sense that the operation of the process is accompanied by consciousness (of its results) and (c) in the sense that consciousness enters into or causally influences the process. Consciousness of familiar stimuli, rather than entering into input analysis, appears to follow it, in human information processing. Processes closely associated with the appearance of consciousness such as information integration and dissemination appear to operate unconsciously. Consequently, perception appears to be "conscious" only in sense (b).

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 effects of brain damage. Finally, mind/body interactions in clinical and experimental settings are considered, including the somatic effects of imagery, biofeedback and placebo effects. Every chapter is written by an expert in the field. They each provide a clear overview of existing research along with an exciting new synthesis of consciousness studies. The The Science of Consciousness will be invaluable for students, researchers and clinicians interested in the developments and directions of this rapidly growing field.

As far as an adequate understanding of phenomenal consciousness is concerned, representationalist theories of mind which are modelled on the information processing paradigm, are, as much as corresponding neurobiological or functionalist theories, confronted with a series of arguments based on inverted or absent qualia considerations. These considerations display the following pattern: assuming we had complete knowledge about the neural and functional states which subserve the occurrence of phenomenal consciousness, would it not still be conceivable that these neural states (or states with the same causal r.

It's very interesting to see neurophysiological evidence brought to bear on the puzzling question of conscious experience. Many have observed that information-processing models of cognition seem to leave consciousness untouched; it is natural to hope that turning to neurophysiology might lead us to the Holy Grail. Still, I think there are reasons to be skeptical. There are good reasons to suppose that neurophysiological investigation contributes to cognitive explanation at best in virtue of constraining the information-processing structure of cognition. Of course this is a very large and significant role for it to play, but it may be over-optimistic to suppose that it can play some further explanatory role, taking us where information-processing theories cannot. If so, then neurophysiological accounts will be no more and no less successful at dealing with consciousness than information-processing accounts are.

It's very interesting to see neurophysiological evidence brought to bear on the puzzling question of conscious experience. Many have observed that information-processing models of cognition seem to leave consciousness untouched; it is natural to hope that turning to neurophysiology might lead us to the Holy Grail. Still, I think there are reasons to be skeptical. There are good reasons to suppose that neurophysiological investigation contributes to cognitive explanation at best in virtue of constraining the information-processing structure of cognition. Of course this is a very large and significant role for it to play, but it may be over-optimistic to suppose that it can play some further explanatory role, taking us where information-processing theories cannot. If so, then neurophysiological accounts will be no more and no less successful at dealing with consciousness than information-processing accounts are.

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 the arguments from theoretical computational considerations that cognitive psychologists use to support their general approach in order to show that they make unwarranted assumptions about the processing attributes of consciousness. I then go on to examine the assumptions behind executive theories which grow out of the computer metaphor of cognitive psychology and conclude that we may not be the sort of computational machine cognitive psychology assumes and that cognitive psychology''s approach in itself does not buy us anything in developing theories of consciousness. Hence, the state space in which we may locate consciousness is vast, even within an information processing framework.

Investigations of the function of consciousness in human information processing have focused mainly on two questions: (1) where does consciousness enter into the information processing sequence and (2) how does conscious processing differ from preconscious and unconscious processing. Input analysis is thought to be initially "preconscious," "pre-attentive," fast, involuntary, and automatic. This is followed by "conscious," "focal-attentive" analysis which is relatively slow, voluntary, and flexible. It is thought that simple, familiar stimuli can be identified preconsciously, but conscious processing is needed to identify complex, novel stimuli. Conscious processing has also been thought to be necessary for choice, learning and memory, and the organization of complex, novel responses, particularly those requiring planning, reflection, or creativity.

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 we purport to use to investigate consciousness. Furthermore, Durgin's own review of the history of research on metacontrast (Lachter & Durgin, 1999) shows that some researchers investigating metacontrast also thought that they were in the business of evaluating the role of consciousness in accounting for their effects. Yet, there is no doubt that metacontrast research is a paradigm case of research generated from an information processing perspective. So, prima facie, investigating consciousness and using information processing methodology are compatible.