Brain Decoding

Brain decoding aims to reconstruct mental states or sensory experiences from brain activity patterns measured using techniques like fMRI and EEG. Current research heavily utilizes deep learning models, including transformers, convolutional neural networks, and graph neural networks, often incorporating techniques like self-supervised learning and transfer learning to improve accuracy and address challenges like cross-subject variability and limited data. This field is significant for advancing our understanding of brain function, developing brain-computer interfaces for communication and control, and potentially improving diagnosis and treatment of neurological and psychiatric disorders.