Improvement of Information Transmission of Supra-threshold Neural Stimuli with Stochastic Resonance in Hippocampal Neuron Network Models

Stochastic resonance(SR)has been observed to improve detection of subthreshold signals with additive noise(or fluctuations)in a single or an array of nonlinear threshold systems like neurons. However, it has been unclear how SR affects information transfer of supra-threshold neural stimuli in the central nervous system. The objective is to observe whether information transmission of supra-threshold stimuli can be improved by uncorrelated noise in an array of hippocampal CA1 neuron models through computer simulations. Mutual information was estimated as an index of information transmission from the population of spike trains. Results show that the mutual information was maximized at specific noise amplitude in the array of larger number of neuron models(N> 4)with supra-threshold SS(SSR). Moreover, it is shown that SSR could be observed at lower mean frequency(