Brain signatures indexing variation in internal processing during perceptual decision-making.

Meaningful variation in internal states remains challenging to discover and characterize. Using modularity-maximation, a data-driven classification method, we identify two subsets of trials with distinct spatial-temporal brain activity and differing in the amount of information required to reach a decision. These results open a new way to identify brain states relevant to cognition and behavior not associated with experimental factors.