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Proceedings Paper

Nonrenewal spike trains generated by stochastic neuron models
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Paper Abstract

Many of the stochastic neuron models employed in the neurobiological literature generate renewal point processes, i.e., successive intervals between spikes are statistically uncorrelated. Recently, however, much experimental evidence for positive and negative correlations in the interspike interval (ISI) sequence of real neurons has been accumulated. It has been shown that these correlations can have implications for neuronal functions. We study a leaky integrate-and-fire (LIF) model with a dynamical threshold or an adaptation current both of which lead to negative correlations. Conditions are identified where these models are equivalent. The ISI statistics, the serial correlation coefficient, and the power spectrum of the spike train, are numerically investigated for various parameter sets.

Paper Details

Date Published: 7 May 2003
PDF: 10 pages
Proc. SPIE 5114, Noise in Complex Systems and Stochastic Dynamics, (7 May 2003); doi: 10.1117/12.488882
Show Author Affiliations
Benjamin Lindner, Univ. of Ottawa (Canada)
Andre Longtin, Univ. of Ottawa (Canada)


Published in SPIE Proceedings Vol. 5114:
Noise in Complex Systems and Stochastic Dynamics
Lutz Schimansky-Geier; Derek Abbott; Alexander Neiman; Christian Van den Broeck, Editor(s)

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