FUSE: FUsing EEG–MEG in a Shared Embedding via self-supervised learning for BCI
Combining complementary neurophysiological modalities offers a promising strategy for improving motor imagery (MI) brain-computer interfaces (BCIs), but learning shared representations across modalities remains largely unexplored. Here, we propose a two-phase deep learning framework for multimodal EEG–MEG decoding that...