Abstract
The mechanisms by which excitatory and inhibitory input impulse sequences interact in changing the spike probability in neurons were examined in the three mathematical models of single neurons ; a poisson deleting model proposed by Ten Hoopen, a real time neuron model which is close to physiological reality, and a stochastic automaton model for the temporal pattern discrimination discussed in previous paper.
The interval histograms of response processes in these models are similar to those used for experimental data, first found by Bishop et al. for geniculate neuron activity. Here, the real time neuron model shows its own characteristics that in case of some decay constants of EPSP and IPSP the response activity of this model has the statistical dependence on the sequence of interspike intervals which is estimated by the serial correlation coefficients. Finally, when the distribution form of the inhibitory input impulse sequence changes, each interval histogram of response distribution in these model is affected by its input form.
