Cross-species identification of conserved and divergent locomotor kinematic strategies using AutoGaitA

Distinct behaviors require the nervous system to execute specialized motor programs, each characterized by unique patterns of body muscle coordination. Whether the execution and adaptation of these programs follow conserved principles across species and perturbations remains unclear. To compare motor programs across species, perturbations, and behaviors, we developed the Python toolbox Automated Gait Analysis (AutoGaitA). Using AutoGaitA and inferring from kinematics, we found that locomotor programs in flies, mice, and humans rely on diverse mechanisms to generate limb propulsive strength, but employ a similar distal-to-proximal gradient of joint movement velocities. In addition, we showed that aging induces a loss of propulsive strength in all species while preserving the velocity gradient. Furthermore, we observed that in mice, locomotor programs adapt as an integrated function of concomitant perturbations, namely aging and task difficulty. Taken together, using our newly developed versatile quantitative framework AutoGaitA, we began to reveal the conserved and divergent mechanisms underlying the execution of locomotor programs in physiological and perturbed states.