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Cognitive Mechanisms and Computational Models: Explanation in Cognitive Neuroscience

Stinson, Catherine E (2013) Cognitive Mechanisms and Computational Models: Explanation in Cognitive Neuroscience. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Cognitive Neuroscience seeks to integrate cognitive psychology and neuroscience. I critique existing analyses of this integration project, and offer my own account of how it ought to be understood given the practices of researchers in these fields.

A recent proposal suggests that integration between cognitive psychology and neuroscience can be achieved `seamlessly' via mechanistic explanation. Cognitive models are elliptical mechanism sketches, according to this proposal. This proposal glosses over several difficulties concerning the practice of cognitive psychology and the nature of cognitive models, however. Although psychology's information-processing models superficially resemble mechanism sketches, they in fact systematically include and exclude different kinds of information. I distinguish two kinds of information-processing model, neither of which specifies the entities and activities characteristic of mechanistic models, even sketchily. Furthermore, theory development in psychology does not involve the filling in of these missing details, but rather refinement of the sorts of models they start out as. I contrast the development of psychology's attention filter models with the development of neurobiology's models of sodium channel filtering.

I argue that extending the account of mechanisms to include what I define as generic mechanisms provides a more promising route towards integration. Generic mechanisms are the in-the-world counterparts to abstract types. They thus have causal-explanatory powers which are shared by all the tokens that instantiate that type. This not only provides a way for generalizations to factor into mechanistic explanations, which allows for the `upward-looking' explanations needed for integrating cognitive models, but also solves some internal problems in the mechanism literature concerning schemas and explanatory relevance.

I illustrate how generic mechanisms are discovered and used with examples from computational cognitive neuroscience. I argue that connectionist models can be understood as approximations to generic brain mechanisms, which resolves a longstanding philosophical puzzle as to their role. Furthermore, I argue that understanding scientific models in general in terms of generic mechanisms allows for a unified account of the types of inferences made in modeling and in experiment.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Stinson, Catherine Eces35@pitt.eduCES35
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairMachamer, Peter Kpkmach@pitt.eduPKMACH
Committee CoChairSchaffner, Kenneth Fkfs@pitt.eduKFS
Committee MemberBogen,
Committee MemberThiels, Eddathiels@pitt.eduTHIELS
Date: 17 October 2013
Date Type: Publication
Defense Date: 9 August 2013
Approval Date: 17 October 2013
Submission Date: 12 August 2013
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 244
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > History and Philosophy of Science
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: explanation, neuroscience, psychology, computation, models, mechanism
Date Deposited: 17 Oct 2013 19:31
Last Modified: 15 Nov 2016 14:15

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