Characterization of spatiotemporal dynamics in EEG data with optical flow patterns

In this study, we investigate the spatiotemporal dynamics of the neural oscillations by analyzing the electric potential that arises from neural activity. To characterize these dynamics, we use optical flow patterns such as sources, sinks, spirals and saddles. Analytical approximation helps us to establish some properties of pattern location and number. Specifically, sources and sinks are mainly located in the same location, while saddles are positioned between them. The number of saddles correlates with the sum of all the other patterns. These properties are confirmed in both the simulated and real EEG data.