Abstract
The ensemble-averaged response function of a compartmental model neuron with randomly distributed synaptic background activity is calculated using a coherent potential approximation. This is used to determine the steady-state firing-rate of a recurrent neural network. The firing-rate is found to decrease as the mean level of background activity across the network is increased; a uniform background (zero variance) leads to a greater reduction than a randomly distributed one (non-zero variance).
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