eConnectome: A MATLAB toolbox for mapping and imaging of brain functional connectivity

Area of Science:

• Neuroscience
• Computational Neuroscience
• Biomedical Engineering

Background:

• Functional connectivity analysis is crucial for understanding brain network dynamics.
• Existing tools may lack comprehensive features for both scalp and source-level electrophysiological data.
• Accurate mapping of brain networks requires robust preprocessing and analysis methods.

Purpose of the Study:

• To introduce eConnectome, a novel MATLAB-based toolbox for electrophysiological connectivity analysis.
• To provide an integrated platform for mapping and imaging functional connectivity from EEG and ECoG data.
• To facilitate advanced analysis of brain networks at both scalp and cortical levels.

Main Methods:

• Development of a MATLAB toolbox (eConnectome) with graphical user interfaces.
• Implementation of EEG/ECoG preprocessing, scalp spatial mapping, and cortical source estimation.
• Integration of Granger causality measures (DTF, aDTF) and cortical current density inverse imaging.

Main Results:

• eConnectome offers comprehensive functions for electrophysiological data analysis.
• The toolbox enables directional interaction estimation in brain functional networks.
• Cortical source domain analysis is achievable from scalp EEG data.

Conclusions:

• eConnectome provides a versatile and open-source platform for electrophysiological connectivity research.
• The toolbox supports advanced functional connectivity mapping from EEG and ECoG.
• eConnectome facilitates non-commercial and academic research in brain network analysis.