Dynamical Models and Explanation in Neuroscience

Philosophy of Science 82 (1):32-54 (2015)
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Abstract

Kaplan and Craver claim that all explanations in neuroscience appeal to mechanisms. They extend this view to the use of mathematical models in neuroscience and propose a constraint such models must meet in order to be explanatory. I analyze a mathematical model used to provide explanations in dynamical systems neuroscience and indicate how this explanation cannot be accommodated by the mechanist framework. I argue that this explanation is well characterized by Batterman’s account of minimal model explanations and that it demonstrates how relationships between explanatory models in neuroscience and the systems they represent is more complex than has been appreciated

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Lauren N. Ross
University of California, Irvine

Citations of this work

Explanation in Computational Neuroscience: Causal and Non-causal.M. Chirimuuta - 2018 - British Journal for the Philosophy of Science 69 (3):849-880.
Getting over Atomism: Functional Decomposition in Complex Neural Systems.Daniel C. Burnston - 2021 - British Journal for the Philosophy of Science 72 (3):743-772.
Models and Explanation.Alisa Bokulich - 2017 - In Magnani Lorenzo & Bertolotti Tommaso Wayne (eds.), Springer Handbook of Model-Based Science. Springer. pp. 103-118.
Searching for Noncausal Explanations in a Sea of Causes.Alisa Bokulich - 2018 - In Alexander Reutlinger & Juha Saatsi (eds.), Explanation Beyond Causation: Philosophical Perspectives on Non-Causal Explanations. Oxford, United Kingdom: Oxford University Press.

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