Predictive regression modeling with MEG/EEG: from source power to signals and cognitive states
paper
published
neuroscience
M/EEG
machine learning
brain age
Riemannian geometry
spatial filtering
Generative models for learning biomarkers from brain activity recorded with M/EEG
Summary
This Twitter thread summarizes the work and walks you through the main findings.
Citation
@article{sabbagh2020predictive,
title={Predictive regression modeling with MEG/EEG: from source power to signals and cognitive states},
author={Sabbagh, David and Ablin, Pierre and Varoquaux, Ga{\"e}l and Gramfort, Alexandre and Engemann, Denis A},
journal={NeuroImage},
volume={222},
pages={116893},
year={2020},
publisher={Elsevier}
}