Periodic Reporting for period 3 - activeFly (Circuit mechanisms of self-movement estimation during walking) Reporting period: 2020-11-01 to 2022-04-30 Summary of the context and overall objectives of the project The brain evolves and operates in the context of locomotion. Although walking is perceived as a seemingly effortless behavior, it is based on a complex interaction between the Central Nervous System (CNS) and the environment. During this interaction, the CNS must monitor movement to plan and control future actions that support walking stability in a flexible manner. Such an internal estimate of self-motion is thought to emerge from a continuous interplay between signals related to motor commands, and self-generated sensory information (sensory feedback) that depends on visual- and mechanosensory-based signaling. This sensorimotor processing must operate on a moment-by-moment bases due to the highly dynamic nature of locomotion. Much is known about how mechanosensory systems, such as proprioception, monitor and guides leg movement during steps. In contrasts, which visual circuits monitor self-motion and operate on a stepwise manner, and how multimodal signals within these circuits are coordinated for a timely control of locomotion are basic questions that remain to be poorly understood and constitute the central focus of this project. To this end, we are using a combination of experimental strategies, including quantitative analysis of behavior in controlled, virtual reality-based environments, physiology in walking flies, perturbations of neural activity through genetically encoded actuators, and state of the art anatomical tools. Combined, these experiments will establish unprecedented causal relationships among dynamics of neural activity and locomotion control. The identified sensorimotor principles will establish a framework that can be tested in other scenarios or animal systems with implications both in health and disease. Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far To understand the role of visual feedback on walking control we need to answer whether and in which circumstances the fly brain uses self-generated visual information during locomotion. To this end, we have taken advantage of a highly structured and naturally occurring behavior, exploration, that is easily implemented in laboratory conditions under Virtual Reality environments. Using this paradigm, we have shown that visual feedback is critical to control the stability of the course direction, and it does so on a moment-by-moment bases. That is, visual circuits in the brain have access to a stepwise information that they combine with visual signals. Using a network sensitive to self-generated visual flow, we found that this circuit receives convergent visual and motor-related signals to form a faithful representation of course direction in a context-specific manner, a context that is driven on a moment-by-moment bases by leg-related circuits of the Ventral Nerve Cord of the fly, and that modulate the activity of the visual circuit for a timely control of course direction. Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far) The development of the exploratory walking paradigm in the Virtual Reality system (FlyVRena) and its use to reveal the role of visual feedback on walking control has established the fly Drosophila melanogaster as a solid model to study the neural bases for visually guided motor control and spatial information. We have made FlyVRena freely accessible (https://github.com/ChiappeLab) for its widespread use to study inset locomotion in naturalistic and controlled conditions. Ongoing and future work will focus on combining quantitative behavioral analysis that the lab has already established with state-of-the-art genetic tools to examine the contribution of genetically identified visuomotor neurons to course control. In addition, ongoing efforts are focusing on adapting FlyVRena for measuring and manipulating the activity of these neurons, located both within the brain and the Ventral Nerve Cord, to dissect how different networks within the CNS work together to monitor movement and control the stability of the direction of walking in a rapid and flexible manner. image-midtermreport.png
