This research investigates the potential utility of chaotic dynamics in neural information
processing. A novel chaotic spiking neural network model is presented which is composed
of non-linear dynamic state (NDS) neurons. The activity of each NDS neuron is driven by a
set of non-linear equations coupled with a threshold based spike output mechanism. If time-
delayed self-connections are enabled then the network stabilises to a periodic pattern of
activation. Previous publications of this work have demonstrated that the chaotic dynamics …