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Simulation of Stochastic Point Processes with Defined Properties

  • Stefano Cardanobile
  • Stefan Rotter
Part of the Springer Series in Computational Neuroscience book series (NEUROSCI, volume 7)

Abstract

We describe procedures that allow one to numerically simulate artificial spike trains matching real spike trains with respect to interspike interval distributions, in particular firing rates, interspike interval irregularity, and spike-count variability, and also time-varying firing rates and the corresponding properties in the nonstationary case.

Keywords

Poisson Process Point Process Hazard Rate Spike Train Renewal Process 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Bernstein Center FreiburgAlbert-Ludwig UniversityFreiburgGermany
  2. 2.Bernstein Center Freiburg & Faculty of BiologyAlbert-Ludwig UniversityFreiburgGermany

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