Denis A. Engemann
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  • Age prediction from M/EEG across 4 large datasets using 5 distinct models
  • Summary
  • Citation

A reusable benchmark of brain-age prediction from M/EEG resting-state signals

paper
published
neuroscience
M/EEG
machine learning
brain age
Author

Engemann, Denis A., Apolline Mellot, Richard Höchenberger, Hubert Banville, David Sabbagh, Lukas Gemein, Tonio Ball, and Alexandre Gramfort

Published

July 22, 2022

Age prediction from M/EEG across 4 large datasets using 5 distinct models

Summary

This Twitter thread summarizes the work and walks you through the main findings.

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Citation

@article{engemann2022reusable,
  title={A reusable benchmark of brain-age prediction from M/EEG resting-state signals},
  author={Engemann, Denis A and Mellot, Apolline and H{\"o}chenberger, Richard and Banville, Hubert and Sabbagh, David and Gemein, Lukas and Ball, Tonio and Gramfort, Alexandre},
  journal={Neuroimage},
  volume={262},
  pages={119521},
  year={2022},
  publisher={Elsevier}
}