Chaos in random neural networks

H. Sompolinsky*, A. Crisanti, H. J. Sommers

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

724 Scopus citations

Abstract

A continuous-time dynamic model of a network of N nonlinear elements interacting via random asymmetric couplings is studied. A self-consistent mean-field theory, exact in the N limit, predicts a transition from a stationary phase to a chaotic phase occurring at a critical value of the gain parameter. The autocorrelations of the chaotic flow as well as the maximal Lyapunov exponent are calculated.

Original languageEnglish
Pages (from-to)259-262
Number of pages4
JournalPhysical Review Letters
Volume61
Issue number3
DOIs
StatePublished - 1988

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