A Sensory-Motor Control Model of Animal Flight Explains Why Bats Fly Differently in Light Versus Dark

Animal flight requires fine motor control. However, it is unknown how flying animals rapidly transform noisy sensory information into adequate motor commands. Here we developed a sensorimotor control model that explains vertebrate flight guidance with high fidelity. This simple model accurately reconstructed complex trajectories of bats flying in the dark. The model implies that in order to apply appropriate motor commands, bats have to estimate not only the angle-to-target, as was previously assumed, but also the angular velocity (“proportional-derivative” controller). Next, we conducted experiments in which bats flew in light conditions. When using vision, bats altered their movements, reducing the flight curvature. This change was explained by the model via reduction in sensory noise under vision versus pure echolocation. These results imply a surprising link between sensory noise and movement dynamics. We propose that this sensory-motor link is fundamental to motion control in rapidly moving animals under different sensory conditions, on land, sea, or air.Author Summary: Bats are extremely skillful aviators: they are able to capture prey and land on targets under challenging flight conditions, as well as maneuver accurately using either echolocation or vision. It remains a mystery, however, how bats—or other flying animals—rapidly translate the noisy incoming sensory information into correct motor commands in order to converge onto a target. To address this question, we developed a sensorimotor control model that explains animal flight guidance and tested it in bats with experiments conducted under dark and light conditions. The model reproduced the bats’ flight trajectory with very high accuracy, suggesting that bats have to estimate not only the angle to target but also changes in the angle over time (angular velocity). Additionally, we demonstrate that the bat must suppress its sensory noise by integrating sensory information over several sonar pulses in order to successfully guide its flight. Comparisons of flight trajectories in light and dark suggest that the surprisingly curved flights exhibited by bats in the dark are due to sensory noise, not motor limitations. We hypothesize that rapidly moving animals must adaptively change their motor control strategy to optimally match the sensory conditions. A model of animal flight guidance suggests that bats use estimates of angular velocity and time-integrated sensory information to find their targets, and explains why bats fly straighter in the light than in the dark.