Chaotic hopping between attractors in neural networks

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dc.creatorMarro, J.
dc.creatorTorres, J. J.
dc.creatorCortes, J. M.
dc.date2006-04-16
dc.date.accessioned2026-07-07T07:11:45Z
dc.date.available2026-07-07T07:11:45Z
dc.descriptionWe 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 systems 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.
dc.description12 pages, 5 figures
dc.identifierhttps://arxiv.org/abs/q-bio/0604020
dc.identifierhttp://arxiv.org/abs/q-bio/0604020
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/111876
dc.subjectNeurons and Cognition
dc.titleChaotic hopping between attractors in neural networks
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