Neural reuse: A fundamental organizational principle of the brain

Behavioral and Brain Sciences 33 (4):245 (2010)
Abstract
An emerging class of theories concerning the functional structure of the brain takes the reuse of neural circuitry for various cognitive purposes to be a central organizational principle. According to these theories, it is quite common for neural circuits established for one purpose to be exapted (exploited, recycled, redeployed) during evolution or normal development, and be put to different uses, often without losing their original functions. Neural reuse theories thus differ from the usual understanding of the role of neural plasticity (which is, after all, a kind of reuse) in brain organization along the following lines: According to neural reuse, circuits can continue to acquire new uses after an initial or original function is established; the acquisition of new uses need not involve unusual circumstances such as injury or loss of established function; and the acquisition of a new use need not involve (much) local change to circuit structure (e.g., it might involve only the establishment of functional connections to new neural partners). Thus, neural reuse theories offer a distinct perspective on several topics of general interest, such as: the evolution and development of the brain, including (for instance) the evolutionary-developmental pathway supporting primate tool use and human language; the degree of modularity in brain organization; the degree of localization of cognitive function; and the cortical parcellation problem and the prospects (and proper methods to employ) for function to structure mapping. The idea also has some practical implications in the areas of rehabilitative medicine and machine interface design.
Keywords brain   development   evolution   exaptation   functional architecture   localization   modularity
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References found in this work BETA
Lawrence W. Barsalou (1999). Perceptual Symbol Systems. Behavioral and Brain Sciences 22 (4):577-660.

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Citations of this work BETA
Eric Mandelbaum (2013). Numerical Architecture. Topics in Cognitive Science 5 (1):367-386.

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