Chaotic hopping between attractors in neural automata

J. Marro, J.J. Torres and J.M. Cortes. Chaotic hopping between attractors in neural automata. Neural Networks 20: 230-235, 2007 [pdf]

We present a neurobiologically-inspired stochastic cellular automaton whose state jumps with time between the attractors corresponding to a series of stored patterns. The jumping varies from regular to chaotic as the model parameters are modified. The resulting irregular behavior, which mimics the state of attention in which a system shows a great adaptability to changing stimulus, is a consequence in the model of short-time presynaptic noise which induces synaptic depression. We discuss results from both a mean-field analysis and Monte Carlo simulations.

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