Firing Rate for a Generic Integrate-and-Fire Neuron with Exponentially Correlated Input

Abstract

The effect of time correlations in the afferent current on the firing rate of a generalized integrate-and-fire neuron model is studied. When the correlation time τ_c is small enough the firing rate can be calculated analytically for small values of the correlation amplitude α². It is shown that the rate decreases as $\sqrt {\tau _c }$ from its value at τ_c = 0. This limit behavior is universal for integrate-and-fire neurons driven by exponential correlated Gaussian input. The details of the model only determine the pre-factor multiplying $\sqrt {\tau _c }$ . Two model examples are discussed.