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Updated: Feb 3, 2026

Establishing a Device for Sleep Deprivation in Mice
Published on: September 22, 2023
Sleep deprivation selectively enhances interpersonal emotion recognition from dynamic facial expressions at long
Benjamin Sack1, Katja Broer1, Silke Anders1
1Social and Affective Neuroscience, Department of Neurology, Universität zu Lübeck, Germany.
Abstract:
Observational and experimental studies have shown that sleep deprivation disinhibits emotional responses to disturbing and rewarding external events. On the other hand, most studies on sleep deprivation and interpersonal emotion recognition report that sensitivity to others' emotions is dampened during sleep deprivation. This is at odds with current neuroscientific theories of social cognition that assume that affective experiences and emotion recognition in others are closely tied at the neural and physiological level. In this observational study we show that sleep deprivation can actually increase emotion recognition accuracy from dynamically unfolding facial expressions if they are viewed sufficiently long. Participants viewed 2-4 s or 8-10s video clips of female senders who facially communicated anger, disgust, fear or sadness to their romantic partner and evaluated the sender's affective state in a forced-choice paradigm, either during sleep deprivation after a night shift (N = 40) or after normal night sleep (N = 50). All participants showed a significant increase in emotion recognition accuracy from 2-4 s to 8-10 s stimulus presentation times. Emotion recognition accuracy did not differ between sleep-deprived and control participants for 2-4 s videos, but sleep-deprived participants showed significantly higher emotion recognition accuracy than control participants for 8-10 s videos. We surmise that this effect might be due to the break-down of prefrontal activity associated with sleep deprivation, which might not only disinhibit affective responses to external events but might also release simulation-based neural processes that contribute to interpersonal emotion recognition from dynamic facial expressions at longer time scales than usually investigated in emotion recognition studies.
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