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Chapitre D'ouvrage Année : 2010

Synaptic noise : experiments, computational consequences and methods to analyze experimental data

Résumé

In the cerebral cortex of awake animals, neurons are subject to tremendous fluctuating activity, mostly of synaptic origin, termed "synaptic noise". Synaptic noise is the dominant source of membrane potential fluctuations in neurons and can have a strong influence on their integrative properties. We review here the experimental measurements of synaptic noise, and its modelling by conductance-based stochastic processes. We then review the consequences of synaptic noise on neuronal integrative properties, as predicted by computational models and investigated experimentally using the dynamic clamp. We also review analysis methods such as spike-triggered average or conductance analysis, which are derived from the modelling of synaptic noise by stochastic processes. These different approaches aim at understanding the integrative properties of neocortical neurons in the intact brain.
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hal-00739674 , version 1 (08-10-2012)

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Alain Destexhe, Michael Rudolph. Synaptic noise : experiments, computational consequences and methods to analyze experimental data. Carlo Laing, Gabriel J Lord (Eds). Stochastic Processes in Neuroscience, Oxford University Press, non spécifié, 2010, 9780199235070. ⟨10.1093/acprof:oso/9780199235070.001.0001⟩. ⟨hal-00739674⟩

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