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The Journal of Neuroscience, January 15, 2002, 22(2):584-591

Redundancy Reduction and Sustained Firing with Stochastic Depressing Synapses

Mark S. Goldman^{1, 3}, Pedro Maldonado⁴, and L. F. Abbott^{1, 2}

¹ Volen Center and ² Department of Biology, Brandeis University, Waltham, Massachusetts 02454, ³ Department of Physics, Harvard University, Cambridge, Massachusetts 02138, and ⁴ Facultad de Medicina, Instituto de Ciencias Biomedicas, Universidad de Chile, Santiago, Chile

Many synapses in the CNS transmit only a fraction of the action potentials that reach them. Although unreliable, such synapses do not transmit completely randomly, because the probability of transmission depends on the recent history of synaptic activity. We examine how a variety of spike trains, including examples recorded from area V1 of monkeys freely viewing natural scenes, are transmitted through a realistic model synapse with activity-dependent depression arising from vesicle depletion or postrelease refractoriness. The resulting sequences of transmitted spikes are significantly less correlated, and hence less redundant, than the presynaptic spike trains that generate them. The spike trains we analyze, which are typical of those recorded in a variety of brain regions, have positive autocorrelations because of the occurrence of variable length periods of sustained firing at approximately constant rates. Sustained firing may, at first, seem inconsistent with input from depressing synapses. We show, however, that such a pattern of activity can arise if the postsynaptic neuron is driven by a fixed population of direct, "feedforward" inputs accompanied by a variable number of delayed, "reverberatory" inputs. This leads to a prediction for the number and latency distribution of the inputs that typically drive a cortical neuron.

Key words: synaptic depression; natural stimuli; information theory; redundancy; correlation; V1

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Copyright © 2002 Society for Neuroscience  0270-6474/02/222584-08$05.00/0

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