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)


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.


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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  1. Brette R (2009) Generation of correlated spike trains. Neural Comput 21(1):188–215 CrossRefPubMedGoogle Scholar
  2. Cox DR, Isham V (1980) Point processes. Monographs on applied probability and statistics, vol 12. Chapman & Hall, London Google Scholar
  3. Gerstner W, Kistler WM (2002) Spiking neuron models: single neurons, populations, plasticity. Cambridge University Press, Cambridge Google Scholar
  4. Krumin M, Shoham S (2009) Generation of spike trains with controlled auto- and cross-correlation functions. Neural Comput 21(6):1642–1664 CrossRefPubMedGoogle Scholar
  5. Macke JH, Berens P, Ecker AS, Tolias AS, Bethge M (2009) Generating spike trains with specified correlation coefficients. Neural Comput 21(2):397–423 CrossRefPubMedGoogle Scholar
  6. Niebur E (2007) Generation of synthetic spike trains with defined pairwise correlations. Neural Comput 19(7):1720–1738. PMID: 17521277 CrossRefPubMedGoogle Scholar
  7. Ripley BD (1987) Stochastic simulation. Wiley, New York CrossRefGoogle Scholar
  8. Staude B, Rotter S, Grün S (2009) CuBIC: cumulant based inference of higher-order correlations. J Comput Neurosci. doi: 10.1007/s10827-009-0195-x PubMedGoogle Scholar
  9. Wikipedia, the free encyclopedia (2009) Exponential function. Online; accessed 28 December 2009 Google Scholar

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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