Synaptic Transmission: An Information-Theoretic Perspective

Abstract

Here we analyze synaptic transmission from an information-theoretic perspective. We derive closed-form expressions for the lower-bounds on the capacity of a simple model of a cortical synapse under two explicit coding paradigms. Under the ``signal estimation'' paradigm, we assume the signal to be encoded in the mean firing rate of a Poisson neuron. The performance of an optimal linear estimator of the signal then provides a lower bound on the capacity for signal estimation. Under the ``signal detection'' paradigm, the presence or absence of the signal has to be detected. Performance of the optimal spike detector allows us to compute a lower bound on the capacity for signal detection. We find that single synapses (for empirically measured parameter values) transmit information poorly but significant improvement can be achieved with a small amount of redundancy.