An Approach to Visualization of Information Flow of EEGs by Directed Coherence Analysis

Abstract

In this paper, we proposed and examined source estimation of EEG (Electroencephalogram) by directed coherence analysis. While ordinary coherence analysis estimates the degree of linear correlation of two time series as a total, directed coherence analysis can extract a correlation with direction in the frequency domain. We estimated information flow between electrodes pasted on a head of subject based on this method. Though the directed coherence analysis is usually applied to analyze the relations between two time series with direction, we proposed an expanded method to estimate the directed coherences between more than two signals at the same time and visualize the signal sources by mapping them. It is confirmed that the estimated positions of signal sources were more adequate than the result of an usual mapping method by simulations and the experimental results.