Rate limitations of unitary event analysis

Unitary event analysis is a new method for detecting episodes of synchroniz ed neural activity (Riehle, Grun, Diesmann, & Aertsen, 1997). It detects ti me intervals that contain coincident firing at higher rates than would be e xpected if the neurons fired as independent inhomogeneous Poisson processes ; all coincidences in such intervals are called unitary events (UEs). Chang es in the frequency of UEs that are correlated with behavioral states may i ndicate synchronization of neural firing that mediates or represents the be havioral state. We show that UE analysis is subject to severe limitations due to the underl ying discrete statistics of the number of coincident events. These limitati ons are particularly stringent for low (0-10 spikes/s) firing rates. Under these conditions, the frequency of UEs is a random variable with a large va riation relative to its mean. The relative variation decreases with increas ing firing rate, and we compute the lowest firing rate, at which the 95% co nfidence interval around the mean frequency of UEs excludes zero. This random variation in UE frequency makes interpretation of changes in UE s problematic for neurons with low firing rates. As a typical example, when analyzing 150 trials of an experiment using an averaging window 100 ms wid e and a 5 ms coincidence window, firing rates should be greater than 7 spik es per second.