Rate coding: neurobiological network performing detection of the difference between mean spiking rates

Abstract

We propose a network of model neurones that "reads" the information encoded as a mean spiking rate by mechanisms relevant to the organism. The streams of independent irregular spiking activity with a Poisson distribution enters the network in parallel via two inputs. The network integrates both synaptic inputs and at the same time acts as a counter allowing their continuous comparison. Detection of the mean spiking rate difference is signalled by spikes emitted at the output. The exactness of the mean-rate discrimination was quantified by the probability of theoretically best comparison.