Effect of increasing inhibitory inputs on information processing within a small network of spiking neurons

In this paper the activity of a spiking neuron A that receives a background input from the network in which it is embedded and strong inputs from an excitatory unit E and an inhibitory unit I is studied. The membrane potential of the neuron A is described by a jump diffusion model. Several types of interspike interval distributions of the excitatory strong inputs are considered as Poissonian inhibitory inputs increase intensity. It is shown that, independently of the distribution of the excitatory inpu, they are more efficiently transmitted as inhibition increases to larger intensities.