Our goal is to understand the fundamental principles for the function and organization of neural circuits involved in estimating an animal’s own movement, especially in the context of visually guided locomotion. Many basic functions of our brain, from motor control, to more cognitive operations such as navigation, critically depend on self-movement estimation. We investigate which circuits are involved in this representation, and what computations these circuits perform. In addition, we aim to identify the activity dynamics and mechanisms by which these computations are generated.
Our strategy focuses on connecting neural activity dynamics to the locomotive behavior of the fruitfly, Drosophila melanogaster. We employ multiple methods to record and reversible perturb neural activity in behaving flies, to analyze the structure of interconnected neurons, to quantify different aspects of the fly’s locomotive behavior, and to model functional networks. This multidisciplinary approach, together with the ever-expanding genetic toolkit of the fruitfly, allows us to find mechanistic explanations for how multisensory and sensorimotor integration processes in the brain are used to guide adaptive behavior.