Has anyone tried quantizing some metric of brain activity (EEG etc.) into a set of tokens, and then training a Transformer model on it? I wonder if hidden in t

Has anyone tried quantizing some metric of brain activity (EEG etc.) into a set of tokens, and then training a Transformer model on it? I wonder if hidden in that is some good prior for human-cognition-related activities, i.e. extend the token space to add human language tokens, train on that and see if it trains significantly faster than a randomly initialized model.