Spike train statistics: from mathematical models to software to experiments - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2014

Spike train statistics: from mathematical models to software to experiments

Bruno Cessac

Abstract

Recent advances in multi-electrodes array acquisition has made it possible torecord the activity of up to several hundreds of neurons at the same time andto register their collective spiking activity. This opens up new perspectivesin understanding how a neuronal network encodes the response to a stimulus, andwhat a spike train tells up about the network structure and nonlinear dynamics.For this, one has to develop statistical models properly handling thespatio-temporal aspects of spike trains, including memory effects. In thistalk, I will review several such statistical models, including Maximum EntropyModels, Generalized Linear Model or neuromimetic models dealing with theiradvantages, limits, and relations.
Marseille2014.pdf (3.08 Mo) Télécharger le fichier
Format : Presentation
Origin : Files produced by the author(s)

Dates and versions

hal-01095746 , version 1 (23-12-2014)

Identifiers

  • HAL Id : hal-01095746 , version 1

Cite

Bruno Cessac. Spike train statistics: from mathematical models to software to experiments. 6th Workshop in Computational Neuroscience in Marseille, Mar 2014, Marseille, France. ⟨hal-01095746⟩
217 View
39 Download

Share

Gmail Facebook X LinkedIn More