Information Measures in a Small Network of Spiking Neurons

We consider a small network, consisting of a reference unit that receives background inputs from the large network in which it is embedded and strong inputs from an excitatory unit and an inhibitory unit that generate constant amplitude jumps (upward or downward) in its membrane potential. The jumps occur at either exponential or inverse Gaussian distributed times. The entropy and the Kullback-Leibler distance between the spiking distributions are employed to study the effect of the inputs with a special attention to the role of inhibitory ones.