Noise in I&F neurons: from stochastic input to escape rates

[Hans Ekkehard Plesser]

Dear Connectionists!

I would like to announce a paper on noisy integrate-and-fire dynamics
that has been accepted for publication in Neural Computation:

  Noise in integrate-and-fire neurons:
       from stochastic input to escape rates

  by Hans E. Plesser and Wulfram Gerstner

The paper is available on-line at

  http://www.chaos.gwdg.de/~plesser/publications.html  .

Abstract:

  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 sub-threshold input, diffusive noise can be replaced by 
  escape noise with a hazard function that has a Gaussian dependence 
  upon 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.  


Hans E. Plesser

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Hans Ekkehard Plesser                
Nonlinear Dynamics Group             Tel.  :     ++49-551-5176-421
MPI for Fluid Dynamics               Fax   :     ++49-551-5176-409
D-37073 Goettingen, Germany	     e-mail: plesser at chaos.gwdg.de
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