  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.
