Information Maximization Explains the Sparseness of Presynaptic Neural Response.

Abstract

In a sensory neural network, where a population of presynaptic neurons sends information to a downstream neuron, maximizing information transmission depends on utilizing the full operating range of the output of the postsynaptic neuron. Because the convergence of presynaptic inputs naturally biases higher outputs, a sparse input distribution would counter such bias and optimize information transmission.