Title:  Dynamic weighting of multi-sensory representations in the superior colliculus of the Egyptian Fruit Bat

To navigate a complex world, animals must continuously merge information from different senses, such as sight and hearing, to make fast and accurate decisions. While past research has carefully characterized sensory responses of neurons in controlled, stationary settings, we do not fully understand how the brain's internal sensory maps update in real-time as an animal moves freely through its environment.
This research focuses on a remarkable navigator: the Egyptian fruit bat. This bat species has well developed vision and tongue-click echolocation. It switches between vision or echolocation-guided behaviors with light levels and their immediate goals, such as finding a place to land. By studying the activity of midbrain neurons in free-flying bats, this project seeks to uncover the brain mechanisms that maintain a stable sense of space in changing environments and behavioral modes.
Using advanced wireless technology to record brain activity while bats fly, I will investigate the way that individual neurons and large neural networks prioritize different senses to guide behavior. I will also explore whether we can "decode" the bat's internal behavioral goals by analyzing its brain signals before it selects an action.
The impact of this work is twofold: it provides a window into the fundamental principles of how brains, including our own, integrate multisensory information to make decisions in dynamic environments. Furthermore, this project will reveal efficient biological "algorithms" these bats use to navigate, which can inspire adaptive and resilient autonomous systems and sensory-processing technologies. Importantly, this research moves beyond studies of passive sensory coding in stationary subjects to reveal the dynamic neural maps that support natural behaviors in a multisensory world.