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Localist representation can improve efficiency for detection and counting

Published online by Cambridge University Press:  30 August 2019

Horace Barlow  and
Anthony Gardner-Medwin
Horace Barlow
Affiliation:
Physiological Laboratory, Cambridge CB2 3EG, [email protected]
Anthony Gardner-Medwin
Affiliation:
Department of Physiology, University College London, London WC1E 6BT, [email protected]
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Abstract

Almost all representations have both distributed and localist aspects, depending upon what properties of the data are being considered. With noisy data, features represented in a localist way can be detected very efficiently, and in binary representations they can be counted more efficiently than those represented in a distributed way. Brains operate in noisy environments, so the localist representation of behaviourally important events is advantageous, and fits what has been found experimentally. Distributed representations require more neurons to perform as efficiently, but they do have greater versatility.

Type
Brief Report
Information
Behavioral and Brain Sciences , Volume 23 , Issue 4 , August 2000 , pp. 467 - 468
Copyright
2000 Cambridge University Press

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