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Gating multiple signals through detailed balance of excitation and inhibition in spiking networks

Summary: Gating multiple signals through detailed balance of
excitation and inhibition in spiking networks
Tim P Vogels1,2 & L F Abbott1
Recent theoretical work has provided a basic understanding of signal propagation in networks of spiking neurons, but mechanisms
for gating and controlling these signals have not been investigated previously. Here we introduce an idea for the gating of multiple
signals in cortical networks that combines principles of signal propagation with aspects of balanced networks. Specifically, we
studied networks in which incoming excitatory signals are normally cancelled by locally evoked inhibition, leaving the targeted
layer unresponsive. Transmission can be gated `on' by modulating excitatory and inhibitory gains to upset this detailed balance.
We illustrate gating through detailed balance in large networks of integrate-and-fire neurons. We show successful gating of
multiple signals and study failure modes that produce effects reminiscent of clinically observed pathologies. Provided that the
individual signals are detectable, detailed balance has a large capacity for gating multiple signals.
Experimental observations1,2 as well as theoretical arguments3,4
suggest that excitation and inhibition are globally balanced
in cortical circuits. In a globally balanced network, each neuron
receives large but approximately equal amounts of excitation and
inhibition that, on average, cancel each other. Spontaneous activity
is driven by fluctuations in the total synaptic input, leading to
asynchronous and irregular patterns of spiking58. Such net-
works have been used to study signal propagation and to
determine conditions that support various signaling schemes916.


Source: Abbott, Laurence - Center for Neurobiology and Behavior & Department of Physiology and Cellular Biophysics, Columbia University
Lazar, Aurel A. - Department of Electrical Engineering, Columbia University


Collections: Biology and Medicine; Computer Technologies and Information Sciences