Explanation and description in computational neuroscience.
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 mec...
| Published in: | Synthese Vol. 183; no. 3; pp. 339 - 374 |
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| Format: | Article |
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Springer Nature
Dec2011
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=66903731&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 66903731 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00397857 4LI jtl: Synthese issn: 00397857 maglogo: N pubinfo: dt: Dec2011 vid: 183 iid: 3 pid: 237 pub: Springer Nature artinfo: ui: 66903731 10.1007/s11229-011-9970-0 ppf: 339 ppct: 35 formats: fmt: @attributes: type: P size: 517KB tig: atl: Explanation and description in computational neuroscience. aug: au: Kaplan, David affil: Department of Anatomy and Neurobiology, Washington University School of Medicine, 660 South Euclid Avenue Saint Louis 63110 USA su: Computational neuroscience Phenomenology Mechanism (Philosophy) Explanation Mathematical models sug: subj: Computational neuroscience Phenomenology Mechanism (Philosophy) Explanation Mathematical models keyword: Computational models Mechanism ab: 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. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Synthese is a copyright of Springer, 2011. All Rights Reserved. item: Synthese holder: Springer Nature dt: @attributes: year: 2011 holdings: @attributes: islocal: N |
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