The Explanatory Force of Dynamical and Mathematical Models in Neuroscience: A Mechanistic Perspective

Philosophy of Science 78 (4):601-627 (2011)
We argue that dynamical and mathematical models in systems and cognitive neuro- science explain (rather than redescribe) a phenomenon only if there is a plausible mapping between elements in the model and elements in the mechanism for the phe- nomenon. We demonstrate how this model-to-mechanism-mapping constraint, when satisfied, endows a model with explanatory force with respect to the phenomenon to be explained. Several paradigmatic models including the Haken-Kelso-Bunz model of bimanual coordination and the difference-of-Gaussians model of visual receptive fields are explored.
Keywords Mechanistic explanation  Mechanism  Dynamics  Dynamical models  HKB model
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DOI 10.1086/661755
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References found in this work BETA
William Bechtel (2005). Explanation: A Mechanist Alternative. Studies in History and Philosophy of Biol and Biomed Sci 36 (2):421--441.
Robert A. Skipper & Roberta L. Millstein (2005). Thinking About Evolutionary Mechanisms: Natural Selection. Studies in History and Philosophy of Biological and Biomedical Sciences 36 (2):327-347.

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Citations of this work BETA
Ingo Brigandt (2013). Systems Biology and the Integration of Mechanistic Explanation and Mathematical Explanation. Studies in History and Philosophy of Biological and Biomedical Sciences 44 (4):477-492.
James Woodward (2013). Mechanistic Explanation: Its Scope and Limits. Aristotelian Society Supplementary Volume 87 (1):39-65.

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