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.
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Cardanobile, S., Rotter, S. (2010). Simulation of Stochastic Point Processes with Defined Properties. In: Grün, S., Rotter, S. (eds) Analysis of Parallel Spike Trains. Springer Series in Computational Neuroscience, vol 7. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-5675-0_16
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DOI: https://doi.org/10.1007/978-1-4419-5675-0_16
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4419-5674-3
Online ISBN: 978-1-4419-5675-0
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