A common kind of explanation in cognitive neuroscience might be called function-theoretic: with some target cognitive capacity in view, the theorist hypothesizes that the system computes a well-defined function (in the mathematical sense) and explains how computing this function contributes to the exercise of the cognitive capacity. Recently, proponents of the so-called ‘new mechanist’ approach in philosophy of science have argued that a model of a cognitive capacity is explanatory only to the extent that it reveals the causal structure of (...) the mechanism underlying the capacity. If they are right, then a cognitive model that resists a transparent mapping to known neural mechanisms fails to be explanatory. I argue that a function-theoretic characterization of a cognitive capacity can be genuinely explanatory even absent an account of how the capacity is realized in neural hardware. (shrink)
I argue that the standard view of representation in computational cognitive science fails to account for the explanatory role content plays in cognitive models. In developing an alternative proposal I identify and characterize two kinds of content – mathematical and cognitive content – that play distinct roles in computational cognitive theorizing. I conclude by considering the prospects of computational cognitive science for explaining intrinsic intentionality.
Representationalism, in its most widely accepted form, is the view that the human mind is an information-using system, and that human cognitive capacities are to be understood as representational capacities. This chapter distinguishes several distinct theses that go by the name "representationalism," focusing on the view that is most prevalent in cogntive science. It also discusses some objections to the view and attempts to clarify the role that representational content plays in cognitive models that make use of the notion of (...) representation. (shrink)
The “top-down” and “bottom-up” approaches have been thought to exhaust the possibilities for doing cognitive neuroscience. We argue that neither approach is likely to succeed in providing a theory that enables us to understand how cognition is achieved in biological creatures like ourselves. We consider a promising third way of doing cognitive neuroscience, what might be called the “neural dynamic systems” approach, that construes cognitive neuroscience as an autonomous explanatory endeavor, aiming to characterize in its own terms the states and (...) processes responsible for brain-based cognition. We sketch the basic motivation for the approach, describe a particular version of the approach, so-called ‘Dynamic Causal Modeling’ (DCM), and consider a concrete example of DCM. This third way, we argue, has the potential to avoid the problems that afflict the other two approaches. (shrink)
Ever since Berkeley discussed the problem at length in his Essay Toward a New Theory of Vision, theorists of vision have attempted to explain why the moon appears larger on the horizon than it does at the zenith. Prevailing opinion has it that the contemporary perceptual psychologists Kaufman and Rock have finally explained the illusion. This paper argues that Kaufman and Rock have not refuted a Berkeleyan account of the illusion, and have over-interpreted their own experimental results. The moon illusion (...) remains unexplained, and a Berkeleyan account is still a contender. (shrink)
It has recently been argued that the success of the connectionist program in cognitive science would threaten folk psychology. I articulate and defend a "minimalist" construal of folk psychology that comports well with empirical evidence on the folk understanding of belief and is compatible with even the most radical developments in cognitive science.