A generic neural model based on excitatory-inhibitory neural population

Experimental studies in neurophysiology show that the response of a biological neuron is random, and only by averaging many observations is it possible to obtain predictable results. It is postulated, therefore, that the collective activity generated by large numbers of locally redundant neurons in a neural population is more significant in a computational content rather than the activity generated by a single neuron. The objective of this paper is to develop a generic neural model based on the concept of neural populations. For analytical simplicity, only two subpopulations, namely excitatory and inhibitory neurons, are assumed to exist in a neural population. It is shown in this paper that the existing neural models can be derived from the proposed generic model.