Realistic synaptic inputs for model neural networks

Abstract

An expression is derived relating the input current for a single neuron in a neural network to the firing rates of excitatory and inhibitory inputs synapsing on the dendritic tree of the neuron. Any dendritic geometry and any pattern of synaptic connections can be treated using the techniques presented. The input currents calculated, combined with known firing rate functions, allow the effects of synaptic conductance changes along dendritic cables to be included in a mean-field description of network behaviour. The shunting effects of inhibitory synaptic conductances provide a solution to the high firing rate problem in neutral network models.