Chaotic hopping between attractors in neural networks

Authors:
Joaquín Marro;Joaquín J. Torres;Jesús M. Cortés
Affiliations:
Institute Carlos I for Theoretical and Computational Physics, and Departamento de Electromagnetismo y Física de la Materia, University of Granada, E-18071-Granada, Spain;Institute Carlos I for Theoretical and Computational Physics, and Departamento de Electromagnetismo y Física de la Materia, University of Granada, E-18071-Granada, Spain;Institute Carlos I for Theoretical and Computational Physics, and Departamento de Electromagnetismo y Física de la Materia, University of Granada, E-18071-Granada, Spain
Venue:
Neural Networks
Year:
2007

Citing 7
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Abstract

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.