Fokker–Planck and Fortet Equation-Based Parameter Estimation for a Leaky Integrate-and-Fire Model with Sinusoidal and Stochastic Forcing

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dc.contributor.authorIolov, Alexandre
dc.contributor.authorDitlevsen, Susanne
dc.contributor.authorLongtin, André
dc.date.accessioned2015-12-18T10:58:29Z
dc.date.available2015-12-18T10:58:29Z
dc.date.issued2014-04-17
dc.identifier.citationThe Journal of Mathematical Neuroscience. 2014 Apr 17;4(1):4
dc.identifier.urihttp://dx.doi.org/10.1186/2190-8567-4-4
dc.identifier.urihttp://hdl.handle.net/10393/33973
dc.description.abstractAbstract Analysis of sinusoidal noisy leaky integrate-and-fire models and comparison with experimental data are important to understand the neural code and neural synchronization and rhythms. In this paper, we propose two methods to estimate input parameters using interspike interval data only. One is based on numerical solutions of the Fokker–Planck equation, and the other is based on an integral equation, which is fulfilled by the interspike interval probability density. This generalizes previous methods tailored to stationary data to the case of time-dependent input. The main contribution is a binning method to circumvent the problems of nonstationarity, and an easy-to-implement initializer for the numerical procedures. The methods are compared on simulated data. List of Abbreviations LIF: Leaky integrate-and-fire ISI: Interspike interval SDE: Stochastic differential equation PDE: Partial differential equation
dc.titleFokker–Planck and Fortet Equation-Based Parameter Estimation for a Leaky Integrate-and-Fire Model with Sinusoidal and Stochastic Forcing
dc.typeJournal Article
dc.date.updated2015-12-18T10:58:29Z
dc.language.rfc3066en
dc.rights.holderA. Iolov et al.; licensee Springer
CollectionLibre accès - Publications // Open Access - Publications

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