Monthly
208 pp. per issue
8 1/2 x 11, illustrated
ISSN
0898-929X
E-ISSN
1530-8898
2014 Impact factor:
4.69

Journal of Cognitive Neuroscience

January 1, 2001, Vol. 13, No. 1, Pages 18-30
(doi: 10.1162/089892901564144)
© 2001 Massachusetts Institute of Technology
Similarity in Perception: A Window to Brain Organization
Article PDF (218.39 KB)
Abstract

This paper presents a neural model of similarity perception in identification tasks. It is based on self-organizing maps and population coding and is examined through five different identification experiments. Simulating an identification task, the neural model generates a confusion matrix that can be compared directly with that of human subjects. The model achieves a fairly accurate match with the pertaining experimental data both during training and thereafter. To achieve this fit, we find that the entire activity in the network should decline while learning the identification task, and that the population encoding of the specific stimuli should become sparse as the network organizes. Our results, thus, suggest that a self-organizing neural model employing population coding can account for identification processing while suggesting computational constraints on the underlying cortical networks.