Brain foundation model-guided source-selective domain adaptation for cross-subject EEG decoding
The study tackles challenging cross-subject motor-imagery decoding by using a pre-trained brain foundation model to select the most compatible source subjects. It adapts these selected sources to a target domain without using target labels, employing dual alignment strategies for feature and decision levels. This method improves performance on public benchmarks by leveraging transferability priors from the foundation model.