For a plain English summary, consider the eLife digest by Helena Perez Valle.
To get an overview on the paper, consider this Twitter thread:
I am very excited to share our latest work published in @eLife! We combined #MEG, #fMRI and #MRI for #BrainAge prediction & #biomarker development. Each modality added unique information & enhanced brain-behavior mapping! https://t.co/iCLYKsuUWY Thread👇 pic.twitter.com/dNEMlGnqXe
— Denis A. Engemann (@dngman) May 19, 2020
For a high-level presentation of the main findings check-out our OHBM 2020 Poster.
Or visit this Twitter thread:
Excited to share our paper @NeuroImage_EiC by @DavSabbagh with @PierreAblin @GaelVaroquaux @agramfort https://t.co/ke0wO8aqwk Nonlinear subject-level regression on M/EEG using linear models without source localization: theory + empirical benchmarks Thread👇 pic.twitter.com/0vevsO3UmG
— Denis A. Engemann (@dngman) May 18, 2020
For a discussion of the neurophysiologicla implications, please consider the companion article by Rodika Sokoliuk and Damian Cruse
Should you have no time to read the paper, this Twitter thread gives you the gist:
1/ New paper out! @Brain1878 https://t.co/l3VIfg4s9F Robust #MachineLearning of diagnosis from #EEG in disorders of #consciousness powered by @CEAParisSaclay @cdf1530 @Coma_Science @dc_uba @ERC_Research @Inria_Saclay @Inserm @mne_news @NeuroSpin_91 @icm_institute @scikit_learn pic.twitter.com/JsDMUYWw6C
— Denis A. Engemann (@dngman) October 4, 2018