Incorporating quantitative EEG analysis into the MNI Open Science neuroinformatics ecosystem

Jorge Bosch-Bayard, PhD Presenter
Montreal Neurological Institute
Montreal, Montreal 
Canada
 
2781 
Software Demonstrations 
Revived interest in electrophysiology, driven by the maturity of EEG source imaging, has led to new informatics challenges (7). Integrating sophisticated EEG analysis with high-performance computing is pivotal to promulgating standardized methods across research and clinical settings (1).

In response, a collaboration from the Cuban Neuroscience Center (CNEURO), the University of Electronic Science and Technology of China (UESTC) and the Montreal Neurological Institute (MNI) is incorporating CNEURO's quantitative EEG methods into the MNI Open Neuroscience ecosystem, based on the LORIS and CBRAIN data- and tool-sharing platforms (3).

CNEURO's Quantitative EEG toolbox (qEEGt) was recently released via CBRAIN (9). Its VARETA source imaging method (2), age regression equations and calculation of z- spectra are published on GitHub and Zenodo. The qEEGt toolbox leverages Bayesian estimation of source localization and connectivity for improved spatial resolution, and produces age-corrected normative SPM maps of EEG log source spectra. Given the impact of SPM across neuroimaging (5), such open-access toolkits hold similar potential for electrophysiology.