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Decoding Synapses Kamal Sen, J. C. Jorge-Rivera, Eve Marder, and L. F. Abbott

Summary: Decoding Synapses
Kamal Sen, J. C. Jorge-Rivera, Eve Marder, and L. F. Abbott
Volen Center, Brandeis University, Waltham, Massachusetts 02254
The strength of many synapses is modified by various use and
time-dependent processes, including facilitation and depres-
sion. A general description of synaptic transfer characteristics
must account for the history-dependence of synaptic efficacy
and should be able to predict the postsynaptic response to any
temporal pattern of presynaptic activity. To generate such a
description, we use an approach similar to the decoding
method used to reconstruct a sensory input from a neuronal
firing pattern. Specifically, a mathematical fit of the postsynap-
tic response to an isolated action potential is multiplied by an
amplitude factor that depends on a time-dependent function
summed over all previous presynaptic spikes. The amplitude
factor is, in general, a nonlinear function of this sum. Approxi-
mate forms of the time-dependent function and the nonlinearity
are extracted from the data, and then both functions are con-
structed more precisely by a learning algorithm. This approach,
which should be applicable to a wide variety of synapses, is


Source: Abbott, Laurence - Center for Neurobiology and Behavior & Department of Physiology and Cellular Biophysics, Columbia University


Collections: Biology and Medicine