arXiv · q-bio/0604020
Chaotic hopping between attractors in neural networks
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 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.
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J. Marro, J. J. Torres, J. M. Cortes. 2006-04-16. Chaotic hopping between attractors in neural networks. https://arxiv.org/abs/q-bio/0604020
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