Noisy dendrites: Models of dendritic integration in vivo.
Alain Destexhe and Michelle Rudolph-Lilith
In: The Computing Dendrite, Edited by Cuntz H, Remme MWH
and Torben-Nielsen B, Springer, New York, pp. 173-190, 2014.
While dendritic processing has been well characterized in vitro,
there is little experimental data and models available about the
integrative properties of dendrites in vivo. Here, we review
existing computational models to infer the dendritic processing of
neocortical pyramidal neurons in vivo. We start by summarizing
experimental measurements of the "high-conductance states" of
cortical neurons in vivo. Next, we show models predicting that, in
such states, the responsiveness of cortical neurons should be
greatly enhanced, in particular due to the presence of
high-amplitude fluctuations ("synaptic noise"). We infer that in
dendrites this effect should be particularly strong, leading to the
spontaneous activation of dendritic spikes. The presence of noise
in dendrites also enhances spike propagation. We show that
opposite distance-dependences of spike initiation and propagation
result in roughly location-independent synaptic efficacies. In
addition, in high-conductance states, dendrites display sharper
temporal processing capabilities. Thus, we conclude that noisy
active dendrites behave more "democratically", and that dendrites
should have enhanced processing capabilities in vivo.
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