In this 2-minute video, Pierre Guetschel explains the main findings of the new paper on pre-training EEG foundation models. The study compares different masking geometries, i.e. which parts of the EEG signal are hidden during pre-training, across two self-supervised approaches: masked autoencoders (MAE) and joint-embedding predictive architectures (JEPA).
