Large-scale analysis of neural activity and connectivity from high-density electroencephalographic data

Area of Science:

• Neuroscience
• Computational Neuroscience
• Biomedical Engineering

Background:

• High-density electroencephalography (hdEEG) is crucial for studying human brain activity and connectivity.
• Traditional hdEEG analysis is time-consuming and resource-intensive, limiting its application to large datasets.
• A need exists for efficient, automated tools to handle complex hdEEG data analysis workflows.

Purpose of the Study:

• To introduce the Noninvasive Electrophysiology Toolbox (NET), an open-source software solution.
• To provide a comprehensive tool for large-scale analysis of hdEEG data.
• To enable efficient and automated processing of complex neural data.

Main Methods:

• Developed NET as a cross-platform MATLAB-based software.
• Integrated tools for the complete hdEEG analysis workflow: signal pre-processing, head modelling, source localization, and quantification.
• Enabled analysis of reconstructed neural signals for time-locked responses, functional connectivity, and brain mapping.
• Designed for unsupervised automation and integration into existing workflows.

Main Results:

• NET facilitates large-scale analysis of hdEEG data, from raw signals to quantitative neural data.
• The software supports traditional and advanced analyses, including functional connectivity and brain mapping.
• Quantitative neural data can be exported for compatibility with other software.
• NET is freely available with a GUI and tutorial for non-commercial use and open-source development.

Conclusions:

• NET provides an efficient, automated solution for large-scale hdEEG data analysis.
• The toolbox streamlines complex analyses, making them feasible for extensive datasets.
• NET's customizable nature supports integration into diverse research workflows.