Neural representation of consciously seen and unseen information.
Scientific reports March 6, 2025 Pablo Rodríguez-San Esteban, Jose A Gonzalez-Lopez, Ana B Chica
Machine learning can decode whether someone consciously perceives a near-threshold visual stimulus from their EEG brain signals, and using time-frequency representations of the signal improves decoding accuracy over raw voltage, especially in theta and alpha frequency bands. In a task where participants viewed faint Gabor gratings and reported whether they saw them, the model successfully detected the presence or absence of a stimulus and the participant's subjective perception, but could not decode the grating's orientation. Unconscious processing of unseen stimuli was evident both behaviorally and neurally, but these unconscious representations were less stable over time and appeared only at early perceptual stages around 100 milliseconds and during response preparation.