Neural networks under periodic operating conditions: transitions between dynamic states

The authors model the nonlinear dynamics of a neural system under time-dependent operating conditions by letting a system parameter vary periodically with time in a higher order neural network. They demonstrate explicitly that the varying operating environment can cause transitions between periodically oscillatory states and chaotic states. They discuss these results in relation to information processing in such systems