20 years of "noise" - Contributions of computational
neuroscience to the exploration the effect of background activity
on central neurons.
In: 20 Years of Computational Neuroscience, Edited by
Bower, J., Springer, New York, pp. 167-186, 2013.
The central nervous system is subject to many different sources of
noise, which have fascinated researchers since the beginning of
electrophysiological recordings. In cerebral cortex, the largest
amplitude noise source is the "synaptic noise", which is dominant
in intracellular recordings in vivo. The consequences of
this background activity is a classic theme of modeling studies.
In the last 20 years, this field tremendously progressed as the
synaptic noise was measured for the first time using quantitative
methods. These measurements have allowed computational models not
only to be more realistic and closer to the biological data, but
also to investigate the consequences of synaptic noise in more
quantitative terms, measurable in experiments. As a consequence,
the "high-conductance state" conferred by this intense activity
in vivo could also be replicated in neurons maintained in
vitro using dynamic-clamp techniques. In addition,
mathematical approaches of stochastic systems provided new methods
to analyze synaptic noise and obtain critical information such as
the optimal conductance patterns leading to spike discharges. It
is only through such a combination of different disciplines, such
as experiments, computational models and theory, that we will be
able to understand how neurons compute in such noisy states.
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