Random Forests

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

To get an overview on the paper, consider this Twitter thread: 📢🥁💫Our latest benchmarks of #BrainAge prediction from #MEG #EEG is out in @NeuroImage_EiC https://t.co/w1fxeTBB3j. #BIDS pipeline, 4 datasets, >2500 recordings, #DeepLearning & classical #MachineLearning; @mne_news & Braindecode.

Combining magnetoencephalography with MRI enhances learning of surrogate-biomarkers

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!

Robust EEG-based cross-site and cross-protocol classification of states of consciousness

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: