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Communication Dans Un Congrès Année : 2010

Parametric estimation of spike train statistics by Gibbs distributions : an application to bio-inspired and experimental data

Résumé

We review here the basics of the formalism of Gibbs distributions and its numerical implementation, (its details published elsewhere \cite{vasquez-cessac-etal:10}, in order to characterizing the statistics of multi-unit spike trains. We present this here with the aim to analyze and modeling synthetic data, especially bio-inspired simulated data e.g. from Virtual Retina \cite{wohrer-kornprobst:09}, but also experimental data Multi-Electrode-Array(MEA) recordings from retina obtained by Adrian Palacios. We remark that Gibbs distribution allow us to estimate the spike statistics, given a design choice, but also to compare different models, thus answering comparative questions about the neural code.
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Dates et versions

hal-00553441 , version 1 (16-03-2011)

Identifiants

  • HAL Id : hal-00553441 , version 1

Citer

Bruno Cessac, Juan Carlos Vasquez, Hassan Nasser, Horacio Rostro-Gonzalez, Thierry Viéville, et al.. Parametric estimation of spike train statistics by Gibbs distributions : an application to bio-inspired and experimental data. Cinquième conférence plénière française de Neurosciences Computationnelles, "Neurocomp'10", Aug 2010, Lyon, France. ⟨hal-00553441⟩
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