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Neural Computation

February 1, 2000, Vol. 12, No. 2, Pages 367-384
(doi: 10.1162/089976600300015835)
© 2000 Massachusetts Institute of Technology
Noise in Integrate-and-Fire Neurons: From Stochastic Input to Escape Rates
Article PDF (223.57 KB)

We analyze the effect of noise in integrate-and-fire neurons driven by time-dependent input and compare the diffusion approximation for the membrane potential to escape noise. It is shown that for time-dependent subthreshold input, diffusive noise can be replaced by escape noise with a hazard function that has a gaussian dependence on the distance between the (noise-free) membrane voltage and threshold. The approximation is improved if we add to the hazard function a probability current proportional to the derivative of the voltage. Stochastic resonance in response to periodic input occurs in both noise models and exhibits similar characteristics.