Synaptic "noise": Experiments, computational consequences and
methods to analyze experimental data.
Alain Destexhe and Michelle Rudolph-Lilith
In: Stochastic Methods in Neuroscience, Edited by Laing C
and Lord GJ, Oxford University Press, Oxford UK, pp. 242-271 (2010).
In the cerebral cortex of awake animals, neurons are subject to a
tremendous fluctuating activity mostly of synaptic origin and 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 modeling by conductance-based
stochastic processes. We next review the consequences of synaptic
noise on neuronal integrative properties, as predicted by
computational models and investigated experimentally using
dynamic-clamp. We also review analysis methods, such as
spike-triggered average or conductance analysis, which are derived
from the modeling 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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