Advances on Real Time M/EEG Neural Feature Extraction
Payam S. Shabestari, Delphine Ribes, Lara Défayes, Dong-Zhen Cai, Emily A. Groves, Hamid Behjat, Dimitri Van De Ville, Tobias Kleinjung, Adrian Naas, Nicolas Henchoz, Andreas Sonderegger, Patrick K. A. Neff · 2025
This paper introduces MNE-RT, a Python package designed for real-time neural feature extraction from magne-toencephalography (MEG) and electroencephalography (EEG) signals in Brain-Computer Interface (BCI) systems. The package incorporates efficient algorithms spanning traditional univariate metrics, such as frequency band power and entropy, to advanced bivariate connectivity measures. It is compatible with various recording systems, enabling the extraction of neural targets from brain signals in real time, with potential applications in enhancing neurofeedback efficacy.