Statistics of spike trains in conductance-based neural networks: Rigorous results View Full Text


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Article Info

DATE

2011-12

AUTHORS

Bruno Cessac

ABSTRACT

We consider a conductance-based neural network inspired by the generalized Integrate and Fire model introduced by Rudolph and Destexhe in 1996. We show the existence and uniqueness of a unique Gibbs distribution characterizing spike train statistics. The corresponding Gibbs potential is explicitly computed. These results hold in the presence of a time-dependent stimulus and apply therefore to non-stationary dynamics. More... »

PAGES

8

References to SciGraph publications

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  • 2011-06. A discrete time neural network model with spiking neurons: II: Dynamics with noise in JOURNAL OF MATHEMATICAL BIOLOGY
  • 1999-09. Precise spike synchronization in monkey motor cortex involved in preparation for movement in EXPERIMENTAL BRAIN RESEARCH
  • 2010. Information Geometry of Multiple Spike Trains in ANALYSIS OF PARALLEL SPIKE TRAINS
  • 2008-03. A discrete time neural network model with spiking neurons in JOURNAL OF MATHEMATICAL BIOLOGY
  • 1999-04. Smooth Dynamics and New Theoretical Ideas in Nonequilibrium Statistical Mechanics in JOURNAL OF STATISTICAL PHYSICS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/2190-8567-1-8

    DOI

    http://dx.doi.org/10.1186/2190-8567-1-8

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1045250300

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/22657160


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