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Summary: Mechanism of gain modulation at single neuron
and network levels
M. Brozovi & L. F. Abbott & R. A. Andersen
Received: 12 February 2007 /Revised: 17 November 2007 /Accepted: 3 December 2007 / Published online: 23 January 2008
# Springer Science + Business Media, LLC 2007
Abstract Gain modulation, in which the sensitivity of a
neural response to one input is modified by a second input,
is studied at single-neuron and network levels. At the single
neuron level, gain modulation can arise if the two inputs are
subject to a direct multiplicative interaction. Alternatively,
these inputs can be summed in a linear manner by the
neuron and gain modulation can arise, instead, from a
nonlinear inputoutput relationship. We derive a mathe-
matical constraint that can distinguish these two mecha-
nisms even though they can look very similar, provided
sufficient data of the appropriate type are available.
Previously, it has been shown in coordinate transformation
studies that artificial neurons with sigmoid transfer func-
tions can acquire a nonlinear additive form of gain
modulation through learning-driven adjustment of synaptic
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