SYNAPTIC INTEGRATION AND INPUT-OUTPUT RELATIONS IN COMPUTER-SIMULATED NEURON

Abstract

On the basis of physiological facts, a mathematical neuron model was constructed for the computer simulation of synaptic integration. The simulation model had multiple excitatory and inhibitory synaptic input channels and a single output channel (an axon). Random spike trains were fed to each of the input channels of the simulated neuron, and interspike interval histograms of its output spike trains were calculated, varying the number of input channels, the size of PSP, and the recovery process from refractory. Increasing the number of excitatory input spikes, output spikes increased and the distribution of their intervals was shifted to the Poisson type. Inhibitory inputs diminished the output spikes and their intervals distributed more widely. Powerful inhibitory inputs made the output interspike interval histogram become bimodal. The size of PSP and the recovery process also influenced the output patterns. The interspike interval histograms of the output trains of the model with various parameters were compared with those of the giant neurons in the nervous system of the marine mollusc, Onchidium verruculatum, observing the intracellular records of their activity.