Direct coupling and inhomogeneity assist neurons to detect correlation in low amplitude noises

Abstract

We address a question on the effect of common stochastic inputs on the correlation of the spikes trains of two neurons when they are possibly nonidentical and are coupled through direct connections. We show that the change in the correlation of low amplitude stochastic inputs can be better detected when the neurons are connected by direct excitatory couplings. Depending on whether the neurons are identical or they are slightly different, symmetric or asymmetric connections can increase the sensitivity of the system to the input correlation by changing the mean slope of correlation transfer function over a given range of input correlation. In either case, there is also an optimum value for synaptic strength which maximizes the sensitivity of the system to the changes in input correlation.