Some theorists who emphasize the complexity of biological and cognitive systems and who advocate the employment of the tools of dynamical systems theory in explaining them construe complexity and reduction as exclusive alternatives. This paper argues that reduction, an approach to explanation that decomposes complex activities and localizes the components within the complex system, is not only compatible with an emphasis on complexity, but provides the foundation for dynamical analysis. Explanation via decomposition and localization is nonetheless extremely challenging, and an (...) analysis of recent cognitive neuroscience research on memory is used to illustrate what is involved. Memory researchers split between advocating memory systems and advocating memory processes, and I argue that it is the latter approach that provides the critical sort of decomposition and localization for explaining memory. The challenges of linking distinguishable functions with brain processes is illustrated by two examples: competing hypotheses about the contribution of the hippocampus and competing attempts to link areas in frontal cortex with memory processing. (shrink)

Explanations in the life sciences frequently involve presenting a model of the mechanism taken to be responsible for a given phenomenon. Such explanations depart in numerous ways from nomological explanations commonly presented in philosophy of science. This paper focuses on three sorts of differences. First, scientists who develop mechanistic explanations are not limited to linguistic representations and logical inference; they frequently employ diagrams to characterize mechanisms and simulations to reason about them. Thus, the epistemic resources for presenting mechanistic explanations are (...) considerably richer than those suggested by a nomological framework. Second, the fact that mechanisms involve organized systems of component parts and operations provides direction to both the discovery and testing of mechanistic explanations. Finally, models of mechanisms are developed for specific exemplars and are not represented in terms of universally quantified statements. Generalization involves investigating both the similarity of new exemplars to those already studied and the variations between them. (shrink)

In my book How the Mind Works, I defended the theory that the human mind is a naturally selected system of organs of computation. Jerry Fodor claims that 'the mind doesn't work that way'(in a book with that title) because (1) Turing Machines cannot duplicate humans' ability to perform abduction (inference to the best explanation); (2) though a massively modular system could succeed at abduction, such a system is implausible on other grounds; and (3) evolution adds nothing to our understanding (...) of the mind. In this review I show that these arguments are flawed. First, my claim that the mind is a computational system is different from the claim Fodor attacks (that the mind has the architecture of a Turing Machine); therefore the practical limitations of Turing Machines are irrelevant. Second, Fodor identifies abduction with the cumulative accomplishments of the scientific community over millennia. This is very different from the accomplishments of human common sense, so the supposed gap between human cognition and computational models may be illusory. Third, my claim about biological specialization, as seen in organ systems, is distinct from Fodor's own notion of encapsulated modules, so the limitations of the latter are irrelevant. Fourth, Fodor's arguments dismissing of the relevance of evolution to psychology are unsound. (shrink)

A neighbor who strikes it rich evokes both admiration and envy, and a similar mix of emotions must be aroused in many neighborhoods of cognitive science when the residents look at the results of research in color perception. It provides what is probably the most widely acknowledged success story of any domain of scientific psychology: the success, against all expectation, of the opponent process theory of color perception. Initially proposed by a Ewald Hering, a nineteenth century physiologist, it drew its (...) inspiration from the existence of opposing muscle groups. Hering thought that analogous opposing processes could explain some aspects of color perception, but the resulting theory was more complicated and less intuitive than that proposed by the great Hermann von Helmholtz. Helmholtz carried his day, but in the long run Hering turned out to be right. (shrink)

For more than a century the paradigm inspiringcognitive neuroscience has been modular and localist.Contemporary research in functional brain imaginggenerally relies on methods favorable to localizingparticular functions in one or more specific brainregions. Meanwhile, connectionist cognitive scientistshave celebrated the computational powers ofdistributed processing, and pioneered methods forinterpreting distributed representations. This papertakes a connectionist approach to functionalneuroimaging. A tabulation of 35 PET (positronemission tomography) experiments strongly indicatesdistributed function for at least the ''medium sized''anatomical units, the cortical Brodmann areas. Moreimportant, when these PET (...) experiments were interpretedas distributed representations, multidimensionalscaling revealed a ''brain activation space'' with asalient structure organized primarily by the sensorymodality of the stimulus, and secondarily by the typeof motor response. These results suggest that currentanalytical techniques in functional neuroimagingshould be augmented by distributed processinganalyses, and that these analyses may lead to manydiscoveries about the structure of ''inner space.''. (shrink)

This paper defends cognitive neuroscience’s project of developing mechanistic explan- ations of cognitive processes through decomposition and localization against objections raised by William Uttal in The New Phrenology. The key issue between Uttal and researchers pursuing cognitive neuroscience is that Uttal bets against the possibility of decomposing mental operations into component elementary operations which are localized in distinct brain regions. The paper argues that it is through advancing and revising what are likely to be overly simplistic and incorrect decompositions that (...) the goals of cognitive neuroscience are likely to be achieved. (shrink)

A great deal of philosophy of mind in the modern era has been driven by an intense aversion to Cartesian dualism. In the 1950s, materialists claimed to have succeeded once and for all in exorcising the Cartesian ghost by identifying the mind with the brain. In subsequent decades, cognitive science put scientific meat on this metaphysical skeleton by explicating mental processes as digital computation implemented in the brain's hardware.

A spate of recent anti-localizationist publications have re-ignited the old debate about the localization of function. Many of the recent attacks on localization, however, are directed at what I will argue to be a narrow and outmoded view of localization, and thus have little conceptual or empirical impact. What I hope to present here is an analysis of functional localization that more adequately reflects the sophistication and complexity of its use in neuroscientific research, both historically and recently. Proceeding first by (...) way of contrast, I examine theanti-localizationist positions of holism andequipotentiationism. Then, I present a four-fold analysis of localization according to physical scope, physical kind, functional scope, and functional kind. Next, I turn to a discussion of the heuristic value oflocalization in deciphering structure-functionrelationships. Finally, I hope to show that the overall view of functional localization that emerges from these considerations constitutes a much more elusive target than its critics assume. It serves to mitigate, and insome instances even defeat, some forms ofanti-localizationist criticisms. (shrink)