Coding properties of spiking neurons: reverse and cross-correlations
What is the meaning of a single spike? Spike-triggered averaging (reverse correlations) yields the typical input just before a spike. Similarly, cross-correlations describe the probability of firing an output spike given (one additional) presynaptic input spike. In this paper, we analytically calculate reverse and cross-correlations for a spiking neuron model with escape noise. The influence of neuronal parameters (such as the membrane time constant, the noise level, and the mean firing rate) on the form of the correlation function is illustrated. The calculation is done in the framework of a population theory that is reviewed. The relation of the population activity equations to population density methods is discussed. Finally, we indicate the role of cross-correlations in spike-time dependent Hebbian plasticity.
spiking neurons cross-correlations reverse correlations noise population activity integrate-and-fire model population equations rate model hebbian learning spike-time dependent plasticity