Cognitive Signal

Cognitive signal decoding aims to understand and interpret brain activity related to cognitive processes, particularly language processing, by translating neural signals into meaningful information. Current research focuses on developing advanced decoding models, such as those employing disentangled attention mechanisms across frequency, spatial, and temporal domains, and spiking neural networks leveraging phase encoding. These efforts leverage diverse data sources, including fMRI and EEG, and are increasingly incorporating large language models to bridge the gap between neural activity and linguistic features. This work holds significant implications for advancing brain-computer interfaces and furthering our understanding of the neural basis of cognition.