Silent reading produces decodable word-level information in EEG that improves with more training data—this opens a scalable path to studying how the brain processes language without relying on unreliable self-reports of inner speech.
Researchers decoded which words people were silently reading from brain activity (EEG), using 49 hours of data from one participant. They trained a neural network to match EEG signals with word embeddings from a language model, achieving above-chance accuracy on 240,000 word presentations.