Measuring Neural Synchrony by Message Passing

A novel approach to measure the interdependence of two time series is proposed, referred to as “stochastic event synchrony” (SES); it quantifies the alignment of two point processes by means of the following parameters: time delay, variance of the timing jitter, fraction of “spurious” events, and average similarity of events. SES may be applied to generic one-dimensional and multi-dimensional point processes, however, the paper mainly focusses on point processes in time-frequency domain. The average event similarity is in that case described by two parameters: the average frequency offset between events in the time-frequency plane, and the variance of the frequency offset (“frequency jitter”); SES then consists of five parameters in total. Those parameters quantify the synchrony of oscillatory events, and hence, they provide an alternative to existing synchrony measures that quantify amplitude or phase synchrony. The pairwise alignment of point processes is cast as a sta...

• Type: Conference
• Year: 2007
• Where: NIPS
• Authors: Justin Dauwels, François B. Vialatte, Tomasz M. Rutkowski, Andrzej Cichocki
• Keywords: Information Technology, NIPS 2007, Pairwise Alignment, Point Processes, Stochastic Event Synchrony