Abstract

We establish a formal similarity between a neural network with random synaptic background activity and a physical system in a heat bath. We then use techniques from nonequilibrium statistical physics to evaluate the average linear response of a lateral inhibitory network in a random background. We show how averaging over the background leads to nontrivial frequency-dependent modifications in network response.

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