Explanation and description in computational neuroscience

Synthese 183 (3):339-373 (2011)
Authors
David Michael Kaplan
Washington University in St. Louis
Abstract
The central aim of this paper is to shed light on the nature of explanation in computational neuroscience. I argue that computational models in this domain possess explanatory force to the extent that they describe the mechanisms responsible for producing a given phenomenon—paralleling how other mechanistic models explain. Conceiving computational explanation as a species of mechanistic explanation affords an important distinction between computational models that play genuine explanatory roles and those that merely provide accurate descriptions or predictions of phenomena. It also serves to clarify the pattern of model refinement and elaboration undertaken by computational neuroscientists.
Keywords Explanation  Mechanism  Computational models  Computational neuroscience
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DOI 10.1007/s11229-011-9970-0
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The Language of Thought.Jerry A. Fodor - 1975 - Harvard University Press.

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Explanation in Computational Neuroscience: Causal and Non-Causal.M. Chirimuuta - 2018 - British Journal for the Philosophy of Science 69 (3):849-880.

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