UBC Theses and Dissertations
Cognitive architecture and the brain : beyond domain-specific functional specification Bergeron, Vincent
My dissertation applies philosophical analysis to the problem of how we should cognitively characterize brain activity. Let us distinguish between high-level cognitive functions—e.g. decision-making, face recognition—and the lower-level computational operations that are carried out by discrete regions of the brain. One can assume that cognitive functions are assembled from interactions between relatively autonomous computational operations carried out by discrete brain regions. My thesis, stated very broadly, is that in order to be effective, the decomposition of a cognitive function into a set of interactions between localized computational operations may need to be specified domain-neutrally, and not in terms of a particular informational domain or stimulus class. Jerry Fodor’s influential work on modularity has sparked an industry of research that is based on the idea that the mind is, to a large extent, a configuration of domain-specific and relatively autonomous cognitive mechanisms, or modules. My treatment indicates how this modular approach must be modified in order successfully to decompose domain-specific cognitive functions into localizable computational operations. I proceed in two steps. First, I provide an analysis of the kinds of inferences that are used by cognitive scientists to postulate the existence of cognitive modules; I call these the modularity inferences. I offer a new characterization of these inferences, and argue that they can, and do, operate in three distinct modes in cognitive scientific research. Second, I present a general approach to the decomposition of a cognitive function into localizable computational operations. According to this approach, which I call the working zone approach, the contribution of a distinct brain region to a cognitive function is specified in terms of the type of operations that this region performs, and not in terms of a particular informational domain. I demonstrate the value of this approach in several research contexts within the cognitive sciences.
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