Miniature linear and split-belt treadmills reveal mechanisms of adaptive motor control in walking Drosophila

To navigate complex environments, walking animals must detect and overcome unexpected perturbations. One technical challenge when investigating adaptive locomotion is measuring behavioral responses to precise perturbations during naturalistic walking; another is that experimentally silencing neurons in sensorimotor circuits often reduces spontaneous locomotion. To overcome these obstacles, we introduce miniature treadmill systems for coercing locomotion and tracking 3D kinematics of walking Drosophila. By systematically comparing walking in three experimental setups, we show that flies compelled to walk on the linear treadmill have similar stepping kinematics to freely walking flies, while kinematics of tethered walking flies are subtly different. Genetically silencing mechanosensory neurons alters step kinematics of flies walking on the linear treadmill across all speeds, while inter-leg coordination remains intact. We also found that flies can maintain a forward heading on a split-belt treadmill by adapting the step distance of their middle legs. Overall, these insights demonstrate the utility of miniature treadmills for studying insect locomotion.

Methods
The datasets within this repository were collected by recording flies with high-speed cameras walking on a mini treadmill (linear or split-belt treadmill), freely in a featureless arena, or on a ball suspended in air while tethered. Flies on the linear treadmill and split-belt treadmills were recorded with 5 high-speed cameras at 180 and 200 fps, respectively. Flies walking in the arena were recorded at 150 fps with a top-down camera. Lastly, tethered flies walking on the ball were recorded with 6 high-speed cameras at 300 fps. We then used modern pose estimation tools (DeepLabCut and Anipose for treadmill and tethered walking flies, and SLEAP for freely walking flies) to extract 2D or 3D positions for labeled key points (i.e. points on the body and leg tips). We then computed walking kinematics from these positions using Python. Please refer to the corresponding paper for more details on data collection and processing.