Visualization of Brain Dynamics based on the Robust Approach of Blind Signal Separation

Abstract

In this paper, we propose a robust approach of noisy blind source separation to visualize the dynamics of brain activities. To decompose the brain waves from noisy observation with high power of outliers, we propose a scale-free approach of blind source separation. Applying the proposed approach to the single-trial phantom data and AEF data, we evaluate the effectiveness of our proposed approach and visualize the dynamics of brain activities, which is impossible when analyzing the averaged data.