Deep Phenotyping of Sleep in Drosophila

Sleep is an evolutionarily conserved behavior, whose function is unknown. Here, we present a system for deep phenotyping of sleep in Drosophila. We developed a high-resolution video imaging system, coupled with closed-loop laser perturbation and optogenetic stimulation. To quantify sleep-associated microbehaviors, we trained a deep-learning network to annotate freely moving flies and developed a semi-supervised computational pipeline to classify behaviors. Quiescent flies exhibit a rich repertoire of microbehaviors, including proboscis pumping (PP) and haltere switches, which vary dynamically across the night. Using our system, we characterized the effects of activating two putative sleep circuits. These data reveal that putative activation of dFB neurons produces micromovements, not suggestive of sleep, while activation of R5 neurons triggers PP followed by behavioral quiescence. Our findings suggest that sleep in Drosophila is polyphasic and comprises different stages and sets the stage for a rigorous analysis of sleep and other behaviors in this species. ### Competing Interest Statement The authors have declared no competing interest.