Our groundbreaking research explores the intricate relationship between natural language processing (NLP) and electroencephalography (EEG) brain signals [1]. By leveraging advanced machine learning techniques, we aim to decode the neural patterns associated with language comprehension and production, ultimately enabling seamless communication between humans and machines. Our innovative approach has the potential to revolutionize brain-computer interfaces,speech recognition technologies, and assistive devices for individuals with communication impairments.

[1] Mohammadi Foumani, N., Mackellar, G., Ghane, S., Irtza, S., Nguyen, N., & Salehi, M. (2024, August). Eeg2rep: enhancing self-supervised EEG representation through informative masked inputs. In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (pp. 5544-5555).