Ion Channel Stochasticity May Be Critical in Determining the Reliability and Precision of Spike Timing

The Žring reliability and precision of an isopotential membrane patch consisting of a realistically large number of ion channels is investigated using a stochastic Hodgkin-Huxley (HH) model. In sharp contrast to the deterministic HH model, the biophysically inspired stochastic model reproduces qualitatively the different reliability and precision characteristics of spike Žring in response to DC and uctuating current input in neocortical neurons, as reported by Mainen & Sejnowski (1995). For DC inputs, spike timing is highly unreliable; the reliability and precision are signiŽcantly increased for uctuating current input. This behavior is critically determined by the relatively small number of excitable channels that are opened near threshold for spike Žring rather than by the total number of channels that exist in the membrane patch. Channel uctuations, together with the inherent bistability in the HH equations, give rise to three additional experimentally observed phenomena: subthreshold oscillations in the membrane voltage for DC input, “spontaneous ” spikes for subthreshold inputs, and “missing” spikes for suprathreshold inputs.We suggest that the noise inherent in the operation of ion channels enables neurons to act as “smart” encoders. Slowly varying, uncorrelated inputs are coded with low reliability and accuracy and, hence, the information about such inputs is encoded almost exclusively by the spike rate. On the other hand, correlated presynaptic activity produces sharp uctuations in the input to the postsynaptic cell, which are then encoded with high reliability and accuracy. In this case, information about the input exists in the exact timing of the spikes. We conclude that channel stochasticity should be considered in realistic models of neurons.