Interspike interval variability for balanced networks with reversal potentials for large numbers of inputs
The hypothesis that the variability in the discharge of cortical neurons results from balanced excitation and inhibition is analyzed. A method is presented for analyzing the integrate and fire neural model with reversal potentials which enables the interspike interval distribution to be calculated in the Gaussian approximation. Results are presented for the perfect integrator model, for which a stable value of the membrane potential in the absence of the spiking mechanism exists. The results show close agreement with numerical simulations for large numbers of small amplitude inputs. The coefficient of variation is consistently less than 1.0, as observed in cortical neurons.
interspike interval variability reversal potentials perfect integrator integrate and fire neurons first-passage time