O'Brien & Opie's (O&O's) theory demands a view of unconscious processing that is incompatible with virtually all current PDP models of neural activity. Relative to the alternatives, the theory is closer to an AI than a parallel distributed processing (PDP) perspective, and its treatment of phenomenology is ad hoc. It raises at least one important question: Could features of network relaxation be the “switch” that turns an unconscious into a conscious network?

Current computational psychology, especially as described by Fodor (1975, 1980, 1981), Pylyshyn (1980), and Stich (1983), is both a bold, promising program for cognitive science and an alternative to naturalistic psychology (Putnam 1975). Whereas naturalistic psychology depends on the general scientific framework to fix the meanings of general terms and, hence, the content of thoughts utilizing or expressed in those terms, computational cognitive theory banishes semantical considerations in psychological investigations, embracing methodological, not ontological, solipsism. I intend to argue that computational (...) psychology cannot individuate thoughts as it promises. For, semantics is fundamental in fixing an important subset of the computational relations that, according to the computational theory, are supposed both to obtain among thoughts and, thereby, to determine their identity conditions. If what I contend is correct, then contrary to what its advocates maintain, computational psychology is not preferable to naturalistic psychology as a research strategy in cognitive science. (shrink)

. Humans can be described as existing somewhere on a descriptive continuum between the poles expressed by the metaphors “humans are machines” and “humans are animals.” Arguments for these metaphors are examined, and the metaphors are rejected as absolute descriptions of humans. After a brief examination of the nature of metaphor, all metaphors are discovered to mediate between biological and cultural evolution. Contrary to the reductionist program of sociobiologists, religious metaphors that generate transcendent meaning offer a legitimate description of humans.

The cognitive neuropsychological understanding of a cognitive system is roughly that of a ‘mental organ’, which is independent of other systems, specializes in some cognitive task, and exhibits a certain kind of internal cohesiveness. This is all quite vague, and I try to make it more precise. A more precise understanding of cognitive systems will make it possible to articulate in some detail an alternative to the Fodorian doctrine of modularity (since not all cognitive systems are modules), but it will (...) also provide a better understanding of what a module is (since all modules are cognitive systems). (shrink)

To avoid teleological interpretations, it is important to make a distinction between functions and uses of consciousness, and to address questions concerning the consequences of consciousness. Assumptions about the phylogenetic distribution of consciousness are examined. It is concluded that there is some value in identifying consciousness an exclusively human attribute.

Gray's integration of the different levels of description and explanation in his theory is problematic: The introduction of consciousness into his theorising consists of the mind-brain identity assumption, which tells us nothing new. There need not be correlations between levels of description. Gray's account does not extend beyond “brute” correlation. Integration must be achieved in a principled, mutually constraining way.

Traditional views separate cognitive processes from sensory–motor processes, seeing cognition as amodal, propositional, and compositional, and thus fundamentally different from the processes that underlie perceiving and acting. These were the ideas on which cognitive science was founded 30 years ago. However, advancing discoveries in neuroscience, cognitive neuroscience, and psychology suggests that cognition may be inseparable from processes of perceiving and acting. From this perspective, this study considers the future of cognitive science with respect to the study of cognitive development.

Hebbian cell-assembly theory and attractor networks are good starting points for modeling cortical processing. Detailed cell models can be useful in understanding the dynamics of attractor networks. Cell assemblies are likely to be distributed, with the cortical column as the local processing unit. Synaptic memory may be dominant in all but the first couple of seconds.

Hebbian mechanisms are justified according to their functional utility in an evolutionary sense. The selective advantage of correlating content-contingent stimuli reflects the putative common cause of temporally or spatially contiguous inputs. The selective consequences of such correlations are discussed by using examples from the evolution of signal form in sexual selection and model-mimic coevolution. We suggest that evolutionary justification might be considered in addition to neurophysiology plansibility when constructing representational models.