Chaos in neural networks with dynamic synapses

We investigated the activity of localized excitatory and inhibitory populations coupled by dynamic synapses. Using numerical simulations, we analyzed the Liapunov exponents as well as fractal dimension of the network for various sets of parameters in order to find regimes of periodic and chaotic behavior. We found that chaotic behavior usually develops when external inputs are near threshold, and that chaos develops through a series of period doublings. It is robust and stable over considerable volume in parameter space. Within chaotic regimes intermittent behavior is exhibited. We investigated the average behavior of the network and shown that the response of the network is approximately linear to the excitatory input across various dynamical regimes. (C) 2000 Elsevier Science B.V. All rights reserved.