Neural networks with low local firing rates

N. Rubin, H. Sompolinsky

Research output: Contribution to journalArticlepeer-review

Abstract

Neural network models of associative memory with uniform inhibition are studied. It is shown that for sufficiently strong inhibition the system orders only partially even at low temperatures. A fraction of the neurons freezes in a quiescent state while the activities of the rest of the neurons fluctuate in time around an average level that is small compared to the saturation level. These models may help understanding the origin of the low neuronal firing rates observed in cortical recordings.

Original languageEnglish (US)
Pages (from-to)465-470
Number of pages6
JournalEPL
Volume10
Issue number5
DOIs
StatePublished - Nov 1 1989

ASJC Scopus subject areas

  • Physics and Astronomy(all)

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