SUMMARY Like many visually active animals including humans, flies generate both smooth and rapid, saccadic movements to stabilize their visual gaze. How rapid body saccades and smooth movement interact for simultaneous object pursuit and gaze stabilization is not understood. We directly observed these interactions in magnetically-tethered Drosophila free to rotate about the yaw axis. A moving bar elicited sustained bouts of saccades following the bar, with surprisingly little smooth movement. By contrast, a moving panorama elicited robust smooth movement interspersed with occasional optomotor saccades. The amplitude, angular velocity, and torque transients of bar-fixation saccades were finely tuned to the speed of bar motion, and were triggered by a threshold in the temporal integral of the bar error angle, rather than its absolute retinal position error. Optomotor saccades were tuned to the dynamics of panoramic image motion, and were triggered by a threshold in the integral of velocity over time. A hybrid control model based on integrated motion cues simulates saccade trigger and dynamics. We propose a novel algorithm for tuning fixation saccades in flies.

Highlights d LC12 and LC15 are ON-OFF visual feature detectors d LC15 responds to moving bars, whereas LC12 responds to objects of any size d Object responses from both LCs are suppressed when the background is moving d Octopamine restores object responses in LC12 and LC15 against a moving background Authors

Animals use active sensing to respond to sensory inputs and guide future motor decisions. In flight, flies generate a pattern of head and body movements to stabilize gaze. How the brain relays visual information to control head and body movements and how active head movements influence downstream motor control remains elusive. Using a control theoretic framework, we studied the optomotor gaze stabilization reflex in tethered flight and quantified how head movements stabilize visual motion and shape wing steering efforts in fruit flies (Drosophila). By shaping visual inputs, head movements increased the gain of wing steering responses and coordination between stimulus and wings, pointing to a tight coupling between head and wing movements. Head movements followed the visual stimulus in as little as 10 ms—a delay similar to the human vestibulo-ocular reflex—whereas wing steering responses lagged by more than 40 ms. This timing difference suggests a temporal order in the flow of visual information such that the head filters visual information eliciting downstream wing steering responses. Head fixation significantly decreased the mechanical power generated by the flight motor by reducing wingbeat frequency and overall thrust. By simulating an elementary motion detector array, we show that head movements shift the effective visual input dynamic range onto the sensitivity optimum of the motion vision pathway. Taken together, our results reveal a transformative influence of active vision on flight motor responses in flies. Our work provides a framework for understanding how to coordinate moving sensors on a moving body.

Exceptional performance is often considered to be elegant and free of ‘errors’ or missteps. During the most extreme escape behaviours, neural control can approach or exceed its operating limits in response time and bandwidth. Here we show that small, rapid running cockroaches with robust exoskeletons select head-on collisions with obstacles to maintain the fastest escape speeds possible to transition up a vertical wall. Instead of avoidance, animals use their passive body shape and compliance to negotiate challenging environments. Cockroaches running at over 1 m or 50 body lengths per second transition from the floor to a vertical wall within 75 ms by using their head like an automobile bumper, mechanically mediating the manoeuvre. Inspired by the animal's behaviour, we demonstrate a passive, high-speed, mechanically mediated vertical transitions with a small, palm-sized legged robot. By creating a collision model for animal and human materials, we suggest a size dependence favouring mechanical mediation below 1 kg that we term the ‘Haldane limit’. Relying on the mechanical control offered by soft exoskeletons represents a paradigm shift for understanding the control of small animals and the next generation of running, climbing and flying robots where the use of the body can off-load the demand for rapid sensing and actuation.