Cross-Subject Generalization for EEG Decoding: A Survey of Deep Learning Methods

This survey reviews deep learning methods for cross-subject EEG decoding, addressing the challenge of high inter-subject variability and domain shift. It categorizes current literature into methodological families like feature alignment and contrastive learning, emphasizing rigorous evaluation and theoretical considerations.