A novel transformer architecture for EEG decoding and neuroscientific analysis (opens in new tab)

Deep learning has significantly advanced brain-computer interface (BCI) technology. However, most deep learning models operate as black boxes, limiting their clinical applicability and scientific interpretability. This lack of transparency makes it difficult to determine whether predictions are driven by genuine neural activity or artifacts. To address this limitation, we propose Analformer, a novel Transformer-based architecture designed to achieve both high predictive performance and neuros...