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Learning synfire chains: Turning noise into signal

Record type: Article

A model of cortical neurons capable of sustaining a low level of spontaneous activity is investigated. Without learning the activity of the network is chaotic. We report on attempts to learn synfire chains in this type of network by introducing a Hebbian learning mechanism and exciting a small set of neurons at random intervals. We discuss the types of instabilities that can arise and prevent the formation of long synfire chains and also discuss various biologically plausible mechanisms which to some extent cure these instabilities.

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Citation

Hertz, John and Prügel-Bennett, Adam (1996) Learning synfire chains: Turning noise into signal International Journal of Neural Systems, 7, (4), pp. 445-451.

More information

Published date: 1996
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 254244
URI: http://eprints.soton.ac.uk/id/eprint/254244
ISSN: 0129-0657
PURE UUID: 6646a14c-040b-40e1-8433-f04c62cb6061

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Date deposited: 12 Jan 2001
Last modified: 18 Jul 2017 09:53

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Contributors

Author: John Hertz
Author: Adam Prügel-Bennett

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