A discrete time neural network model with spiking neurons: II: Dynamics with noise View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2011-06

AUTHORS

B. Cessac

ABSTRACT

We provide rigorous and exact results characterizing the statistics of spike trains in a network of leaky Integrate-and-Fire neurons, where time is discrete and where neurons are submitted to noise, without restriction on the synaptic weights. We show the existence and uniqueness of an invariant measure of Gibbs type and discuss its properties. We also discuss Markovian approximations and relate them to the approaches currently used in computational neuroscience to analyse experimental spike trains statistics. More... »

PAGES

863-900

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00285-010-0358-4

DOI

http://dx.doi.org/10.1007/s00285-010-0358-4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1002696758

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/20658138


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