Exploration of event-induced EEG phase synchronization patterns in cognitive tasks using a time–frequency-topography visualization system

In this paper, we present a method for the study of synchronization patterns measured from EEG scalp potentials in psychophysiological experiments. This method is based on various techniques: a time–frequency decomposition using sinusoidal filters which improve phase accuracy for low frequencies, a Bayesian approach for the estimation of significant synchrony changes, and a time–frequency-topography visualization technique which allows for easy exploration and provides detailed insights of a particular experiment. Particularly, we focus on in-phase synchrony using an instantaneous phase-lock measure. We also discuss some of the most common methods in the literature, focusing on their relevance to long-range synchrony analysis; this discussion includes a comparison among various synchrony measures. Finally, we present the analysis of a figure categorization experiment to illustrate our method.