Characterization of spatiotemporal dynamics in EEG data during picture naming with optical flow patterns

We present an analysis of the spatiotemporal dynamics of the oscillations in the electric potential that arises from neural activity. Depending on the frequency and phase of oscillations, these dynamics can be characterized as standing waves or as out-of-phase and modulated waves, which represent a combination of standing and moving waves. We characterize these dynamics as optical flow patterns, in terms of sources, sinks, spirals and saddles. Analytical and numerical solutions are compared with real EEG data acquired during a picture-naming task. Analytical approximation of standing waves allows us to establish some properties of pattern location and number. Namely, sources and sinks have mainly the same location, while saddles are located 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.