Minimal models and canonical neural computations: the distinctness of computational explanation in neuroscience.
In a recent paper, Kaplan (Synthese 183:339-373, ) takes up the task of extending Craver's (Explaining the brain, ) mechanistic account of explanation in neuroscience to the new territory of computational neuroscience. He presents the model to mechanism mapping (3M) criterion as a condition for a mo...
| Publicado en: | Synthese Vol. 191; no. 2; pp. 127 - 154 |
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| Formato: | Artículo |
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Springer Nature
Jan2014
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=94095469&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 94095469 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00397857 4LI jtl: Synthese issn: 00397857 maglogo: N pubinfo: dt: Jan2014 vid: 191 iid: 2 pid: 237 pub: Springer Nature artinfo: ui: 94095469 10.1007/s11229-013-0369-y ppf: 127 ppct: 27 formats: fmt: @attributes: type: P size: 429KB tig: atl: Minimal models and canonical neural computations: the distinctness of computational explanation in neuroscience. aug: au: Chirimuuta, M. affil: History & Philosophy of Science, University of Pittsburgh, 1017 Cathedral of Learning, 4200 Fifth Avenue Pittsburgh 15260 USA su: Computational neuroscience Brain mapping Biophysics Explanatory style (Psychology) Optimality theory (Linguistics) Neural codes sug: subj: Computational neuroscience Brain mapping Biophysics Explanatory style (Psychology) Optimality theory (Linguistics) Neural codes keyword: Biology Computation Explanation Mechanism Neuroscience ab: In a recent paper, Kaplan (Synthese 183:339-373, ) takes up the task of extending Craver's (Explaining the brain, ) mechanistic account of explanation in neuroscience to the new territory of computational neuroscience. He presents the model to mechanism mapping (3M) criterion as a condition for a model's explanatory adequacy. This mechanistic approach is intended to replace earlier accounts which posited a level of computational analysis conceived as distinct and autonomous from underlying mechanistic details. In this paper I discuss work in computational neuroscience that creates difficulties for the mechanist project. Carandini and Heeger (Nat Rev Neurosci 13:51-62, ) propose that many neural response properties can be understood in terms of canonical neural computations. These are 'standard computational modules that apply the same fundamental operations in a variety of contexts.' Importantly, these computations can have numerous biophysical realisations, and so straightforward examination of the mechanisms underlying these computations carries little explanatory weight. Through a comparison between this modelling approach and minimal models in other branches of science, I argue that computational neuroscience frequently employs a distinct explanatory style, namely, efficient coding explanation. Such explanations cannot be assimilated into the mechanistic framework but do bear interesting similarities with evolutionary and optimality explanations elsewhere in biology. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Synthese is a copyright of Springer, 2014. All Rights Reserved. item: Synthese holder: Springer Nature dt: @attributes: year: 2014 holdings: @attributes: islocal: N |
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