Action selection in insects: how a microbrain knows what to do. Identifying what to do demands integrating sensory information with our current physiological state and memory of past experience to select the best possible action. This is the action selection problem. Our project aims to discover how tiny insect brains solve this fundamental problem. The project combines neural recordings from animals exploring virtual reality, behavioural analyses and computational modelling. The expected outco ....Action selection in insects: how a microbrain knows what to do. Identifying what to do demands integrating sensory information with our current physiological state and memory of past experience to select the best possible action. This is the action selection problem. Our project aims to discover how tiny insect brains solve this fundamental problem. The project combines neural recordings from animals exploring virtual reality, behavioural analyses and computational modelling. The expected outcome is a new understanding of the brain as an effective behavioural control system. This will benefit systems and comparative neuroscience. Our findings may also inspire solutions for robotic systems that must operate autonomously in remote and challenging environments such as disaster relief or exploration.Read moreRead less
Comparative analysis of sensor noise for target detection in dragonfly eyes. Dragonflies hunt tiny prey in the low-light conditions of late dusk, a signal-to-noise problem that challenges any engineered system. Using a comparative approach across dragonfly species, we aim to use novel optical and physiological measures to determine how sensors with noise underlie target-detection, in varying scene brightness. The project outcomes will be a comparative characterisation of signal-to-noise measures ....Comparative analysis of sensor noise for target detection in dragonfly eyes. Dragonflies hunt tiny prey in the low-light conditions of late dusk, a signal-to-noise problem that challenges any engineered system. Using a comparative approach across dragonfly species, we aim to use novel optical and physiological measures to determine how sensors with noise underlie target-detection, in varying scene brightness. The project outcomes will be a comparative characterisation of signal-to-noise measures of dragonfly eye optics (including eye size) and early sensory neurons. We will match detection thresholds with downstream target-detecting neurons and dragonfly behaviour. This will provide insight into signal detection, which is a ubiquitous problem across information processing, computer vision and autonomous systems.Read moreRead less