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The local is running on the express track: Localist models better facilitate understanding of nervous system function

Published online by Cambridge University Press:  17 March 2005

Paul A. Koch  and
Gerry Leisman
Paul A. Koch*
Affiliation:
School of Engineering, New York Institute of Technology, Old Westbury, NY11568
Gerry Leisman*
Affiliation:
Carrick Institute for Clinical Ergonomics, Rehabilitation and Applied Neurosciences, School of Engineering, State University of New York at Farmingdale, Farmingdale, NY11735-1021
*
[email protected]
[email protected]
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Abstract:

Artificial neural networks have weaknesses as models of cognition. A conventional neural network has limitations of computational power. The localist representation is at least equal to its competition. We contend that locally connected neural networks are perfectly capable of storing and retrieving the individual features, but the process of reconstruction must be otherwise explained. We support the localist position but propose a “hybrid” model that can begin to explain cognition in anatomically plausible terms.

Type
Continuing Commentary
Information
Behavioral and Brain Sciences , Volume 27 , Issue 5 , October 2004 , pp. 699 - 700
Copyright
Copyright © Cambridge University Press 2004

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Footnotes

Commentary onMike Page (2000). Connectionist modelling in psychology: A localist manifesto. BBS 23(4):443–512.