Whole-body 3D kinematics of freely behaving Drosophila
Ispizua, J. I.; Abe, E. T. T.; Yan, J.; Othayoth, R.; Sawtelle, S.; Atkins, F.; Shiozaki, H.; Meier, N. R.; Wong, J.; Tran, T. T.; Mori, C. K.; Voigts, J.; Stern, D. L.; Brunton, B. W.; Tuthill, J. C.; Johnson, R. E.
Show abstract
Understanding how nervous systems generate coordinated movement requires precise measurement of body kinematics during natural behavior. The fruit fly, Drosophila, is a model organism with sophisticated behavior and well-studied neural circuits, but tracking fly movements in 3D remains challenging because of their teeny bodies, rapid movements, and frequent self-occlusions. Here we present a pipeline for markerless, full-body 3D pose estimation of fly terrestrial behavior, combining seven synchronized high-speed cameras to capture whole-body kinematics at 800 frames per second. We trained a hybrid 2D/3D deep learning model to track 50 keypoints, then refined them to produce anatomically feasible kinematic trajectories through a retargeting process that solved an inverse kinematics problem constrained by a biomechanical body model. Analysis of 3D kinematics revealed that flies perform grounded running across their full speed range, without transitioning between discrete gaits. Using multi-animal tracking, we found that courting males coordinate both wings during song and modulate body pitch to track the females vertical position. Our open-source pipeline and 3D kinematic dataset of fly behavior provide a foundation for neuromechanical modeling and mechanistic studies of motor control in a genetically tractable model organism.
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