Regular pulse train transformation by the monosynaptic connection-neurophysiological data and their treating with simple stochastic neuron model

Firing pattern of neuronal activity evoked by regular stimulation of monosynaptic inputs to the neurons is described with simple stochastic neuron model. The model gives definite possibilities for an indirect evaluation of transformation in the real neurons which have to fit the following demands: 1) background activity was absent; 2) evoked activity was stationary within the wide range of stimulation frequencies; 3) spike occurrence times were within narrow limits in relation to the nearest stimuli. Experimental data obtained on three types of monosynaptic connections with different intensity of excitatory postsynaptic effects are compared with the model.