| The interspike interval (ISI) density of the leaky integrate-and-fire neuron model driven by exponentially correlated Gaussian noise exhibits a dominant peak at small bursting intervals and a slow power-law decay of long interburst intervals. Due to this power-law decay, extreme ISI's have a large effect on the ISI statistics. This leads to a coefficient of variation which diverges as t^(1/2) and an unexpected suppression of ISI correlations. This is in clear contrast to the colored noise effect in simpler neuron models, where the effect of noise correlations appeared in higher order statistical measures. Additionally, we study the impact of a dichotomous driving force. |
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