HyBRA-EEG: Hyperbolic Global-Local Brain-Region Aggregation for Self-Supervised EEG Representation Learning
HyBRA maps messy EEG data into a structured regional token space using hyperbolic geometry and channel evidence. It combines electrode locations, region priors, and feature-dependent distances to create superior self-supervised representations for EEG learning.