DocumentCode :
1082207
Title :
Contextual Categorization by Lateral Inhibition
Author :
Waxman, S.G.
Author_Institution :
Dept. of Anatomy and Medical Science Program Albert Einstein College of Medicine Bronx, N.Y. 10461
Volume :
4
Issue :
2
fYear :
1968
fDate :
7/1/1968 12:00:00 AM
Firstpage :
191
Lastpage :
192
Abstract :
A mechanism is proposed whereby categorization of stimuli is performed on the basis of the context in which such stimuli occur. This mechanism depends on lateral inhibition, which has been experimentally shown to operate in a number of biological receptor systems. It is assumed that n areas in the brain correspond to n classes into which a stimulus might be classified, the category chosen corresponding to the area of maximal excitation. Establishment of mutually inhibitory connections between these areas, such that inhibition follows the equation for lateral inhibition and such that areas corresponding to "like" classes inhibit each other less than areas corresponding to "unlike" classes, leads to contextual categorization.
Keywords :
Computational modeling; Computer simulation; Context modeling; Distributed computing; Equations; Gaussian distribution; Mathematics; Random sequences; Random variables; Stochastic systems;
fLanguage :
English
Journal_Title :
Systems Science and Cybernetics, IEEE Transactions on
Publisher :
ieee
ISSN :
0536-1567
Type :
jour
DOI :
10.1109/TSSC.1968.300149
Filename :
4082141
Link To Document :
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