EEG Based Source Localization and Functional Connectivity Analysis

Soe Myat Thu, Khin Pa Pa Aung

Abstract: Nowadays Electroencephalography (EEG) is one of the most attractive Brain-Computer Interfaces (BCI) models to analyze brain signals source localization and connectivity estimation. Unlike other neuroimaging modalities such as fMRI, MEG, and PET; EEG has its higher temporal resolution that senses EEG is currently interesting area for many BCI researchers. However, the precise results of source localization and connectivity are challenging problems that mostly depend on the head models and inverse modeling methods. This paper focused on source localization and functional connectivity analysis using EEG signal over single-trial movement imaginary (MI) tasks by using brainstorm toolbox. Data obtained from the nature dataset that was recorded from 12 subjects, 29 recordings with 19 channels EEG device and MATLAB software utilized for the task.