Modeling neural spatiotemporal behavior

D. Horn

doi:10.1016/S0925-2312(02)00780-4

Modeling neural spatiotemporal behavior

2003-06-01

3

PRE

AI

DOI：10.1016/S0925-2312(02)00780-4

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We study some aspects of the dynamic neural filter (DNF), a recurrent network that produces spatiotemporal sequences in reaction to sets of constant inputs. The biological motivation for this study came from the observation of spatiotemporal patterns in the locust antenna] lobe. Some of the aspects of these results can be reformulated and characterized by the DNF. Studying deterministic dynamics we find differences between low and high numbers of neurons. For low numbers there exists clear correlation between distances in input space and edit distances of spatiotemporal sequences. For large numbers of neurons we observe divergence between close-by spatiotemporal sequences. Nonetheless neuronal correlations survive for small changes in input space. (C) 2002 Elsevier Science B.V. All rights reserved.

Keyword:

temporal coding

dynamic neural filter

recurrent network

olfaction

Modeling neural spatiotemporal behavior

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