||Nervous systems and their constituent neurons often display complex dynamics in response to inputs with simple characteristics. Until recently, these behaviors were not even classified, let alone understood. This lack of understanding impedes determination of the utility of dynamical processing elements in artificial neural networks. This paper summarizes a comparison of the responses of an ionic permeability based neural model to periodic inhibitory driving with that of a living preparation. Unlike previous, simpler models, duplication of most neuron response types was excellent, and simulation results led to insights into neuron activities that were subsequently verified by examination of the living data. It is hoped that knowledge of the underlying physiological mechanisms and formal properties of neuron dynamics will lead to advances in artificial neural network computational theory.