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

Author

Sabbagh, David, Pierre Ablin, Gaël Varoquaux, Alexandre Gramfort, and Denis A. Engemann.

Published

May 18, 2020

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.

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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}
}