Abstract
Cross-correlation between stimuli and neuronal discharges determines the peri-stimulus spike density. This density function is usually estimated by the peri-stimulus time histogram (PSTH). In this paper an alternative method for spike-density estimation is considered that employs estimation of the rate of an inhomogeneous Poisson process by Jth waiting times. This procedure is called the RIPP density estimate. It involves sorting the spike times for all trials and obtaining the Poisson rates for successive groups of spikes. By application of this procedure to simulated action-potential sequences from the leaky-integrator model subject to a realistic input, it is shown that the RIPP density estimate reveals much more information from a given set of spike train data than PSTH. An application of the RIPP density estimate to experimental spike train data from a human hand muscle motoneuron subject to a low-threshold-afferent volley is also presented.
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