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Modulation of visual recognition is manifested through sleep in lower and higher-level visual processing

Poster Session B - Sunday, March 8, 2026, 8:00 – 10:00 am PDT, Fairview/Kitsilano Ballroom

Fumiaki Sato¹ (), Ryosuke Katsumata¹, Takeru Matsuda^1,2, Masako Tamaki^1,3; ¹RIKEN Center for Brain Science, Japan, ²The University of Tokyo, ³RIKEN Cluster for Pioneering Research, Japan

Whether obtaining semantic information about unfamiliar objects alters higher-level visual processing and whether it occurs instantly has been controversial. Accumulating evidence indicates that sleep plays a role in visual perception following extensive training (Tamaki et al., 2020, Nat. Neurosci.; Tamaki et al., 2020, PNAS). In the present study, we tested whether sleep facilitates visual recognition without extensive training and whether the process involves lower and higher-level changes. Before and after a 90-minute interval with (nap group, N=19) or without (break group, N=17) sleep with polysomnography, participants performed a newly-developed Mooney-image identification task where they were presented with various types of binarized images only once or twice and asked to respond whether they recognized the image via 2AFC and to report the content of each image. Our results showed that visual recognition accuracy improved significantly only after the nap; i.e., subjective recognition became significantly more consistent with detection accuracy. To identify the neural underpinnings driving the change in visual recognition after sleep, we applied a data-driven functional connectivity analysis to sleep EEG. We found that stronger visual-nonvisual network connectivity predicted sleep-dependent recognition change. Next, to investigate the effects of sleep on visual processing during the task, we fit linear regression models to task EEG data. We found that early event-related potentials in occipital (N1p) and fronto-central (N1a) regions, evoked 120‒150 ms post-stimulus, were modulated by sleep. Thus, sleep spontaneously calibrates visual recognition without extensive training through network-level changes, resulting in changes to both lower- and higher-level visual processing.

Topic Area: PERCEPTION & ACTION: Vision