A Diffusion Adaptation Approach to model Brain Responses in an EEG-based Hyperscanning Study

Abstract

In this paper, for the first time a brain connectivity-enhanced diffusion adaptation is introduced and applied to an electroencephalogram (EEG) hyperscanning brain-computer interfacing scenario where the EEGs from two brains are recorded during the performance of a collaborative task. In the diffusion adaptation formulation for modeling, the link between one brain (under rehabilitation) which follows the other (healthy) brain, the combination weights are replaced by the connectivity estimates and the corresponding EEG channels of the healthy subject are used as the targets for the adaptation algorithm. The outcome can be used as a new rehabilitation platform where the state of the patient under rehabilitation depends on how well his/her brain signals can follow the target brain signals.