  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.
