Firing Rate for a Generic Integrate-and-Fire Neuron with Exponentially Correlated Input
نویسندگان
چکیده
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 τc is small enough the firing rate can be calculated analytically for small values of the correlation amplitude α. It is shown that the rate decreases as √ τc from its value at τc = 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 √ τc. Two model examples are discussed.
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