Rate Limitations of Unitary Event Analysis

A. Roy, P. N. Steinmetz, E. Niebur
2000 Neural Computation  
Unitary event analysis is a new method for detecting episodes of synchronized neural activity (Riehle, Grün, Diesmann, & Aertsen, 1997). It detects time intervals that contain coincident ring at higher rates than would be expected if the neurons red as independent inhomogeneous Poisson processes; all coincidences in such intervals are called unitary events (UEs). Changes in the frequency of UEs that are correlated with behavioral states may indicate synchronization of neural ring that mediates
more » ... ring that mediates or represents the behavioral state. We show that UE analysis is subject to severe limitations due to the underlying discrete statistics of the number of coincident events. These limitations are particularly stringent for low (0-10 spikes/s) ring rates. Under these conditions, the frequency of UEs is a random variable with a large variation relative to its mean. The relative variation decreases with increasing ring rate, and we compute the lowest ring rate, at which the 95% con dence interval around the mean frequency of UEs excludes zero. This random variation in UE frequency makes interpretation of changes in UEs problematic for neurons with low ring rates. As a typical example, when analyzing 150 trials of an experiment using an averaging window 100 ms wide and a 5 ms coincidence window, ring rates should be greater than 7 spikes per second.
doi:10.1162/089976600300015060 pmid:10976139 fatcat:ilbpb7xqozajfawpxsmudwy7vi