Whether it is to adapt to changes of the body or the environmental conditions, or to learn new motor skills, animals must modify their actions to execute tasks accurately in a process known as motor learning. Several models, such as forward and inverse models, and direct learning policy have been proposed for motor adaptation in humans. Through the update of these internal models and policies, the brain is thought to maintain an accurate representation of self-motion for precise motor control. Despite the importance of this neurobiological process for smooth movement control, injury and disease recovery, it remains unclear how accurate self-motion representations update motor commands. For instance, an important component of motor learning concerns the recalibration between sensory signals and internal motor information, and generally involves the generation of an error signal due to the mismatch between the observed and intended movement.
Exploratory animals structure their behavior to maximize gaze stability, thereby facilitating the acquisition of visual and spatial information while minimizing retinal slip. Such gaze control depends on multi-sensory integration, but the circuit mechanisms underlying precise multi-modal calibration during locomotion remain unclear. Partially, This is due to the complexity of the mammalian brain, and the distributed nature of circuits involved in motor control, recruiting several distributed areas of the mammalian brain with unclear specific contribution.The fruit fly, Drosophila melanogaster, provides a unique opportunity for a comprehensive mechanistic understanding of motor learning because of its compact brain and the recently developed whole central nervous system connectomic dataset, both of which facilitates the study of distributed internal representations, and the role of specific brain areas and genetically identified classes of neurons.
Previous work in the Chiappe laboratory as shown that walking flies maximize gaze stability through distinct coordinated head and body motor program. Moreover, gaze stability was improved when self-generated visual feedback was available to the animal and use to tune postural reflexes. We aim to unravel the neural basis of motor adaptation using a population of visual neurons thought to contribute to steering control, and whose activity is strongly modulated by the insect’s ongoing motor programs. We combined 2-photon calcium imaging and a virtual reality environment where we could manipulated the self-motion generated visual feedback available to the animal.
