Will Dorrell

Will Dorrell is a Ph.D. student at the Gatsby Computational Neuroscience Unit in London, currently working on biological structure learning and neural networks. He was a physics undergraduate at the University of Cambridge, where he ran a weekly discussion group. He then moved to Harvard University, initially as a condensed matter physicist working on metamaterials, before becoming a theoretical neuroscientist working with Cengiz Pehlevan on olfaction. Finally, he spent much of the pandemic on the subtropical island of Okinawa working with Erik de Schutter on bio-plausible hierarchical reinforcement learning.

Principal Investigator: Peter Latham

Fellow: Maria Yuffa

Project: Sensory systems are marvels, turning a sea of noisy inputs into useful knowledge. Olfaction is no exception, enabling navigation and memory recall from only the soup of ambient volatile chemicals. This project will explore consequences of a recent experimental pre-print. Olfaction has long been thought unique among sensory systems due to its lack of structure — higher-order olfactory neurons randomly sample from sensory input neurons. However, recent electron microscopy work has mapped the connectivity of the fly olfactory system and found something previously overlooked: certain input regions are oversampled vs random. This project will use mathematical and computational approaches to ask, ‘what role does this new-found structure play?’ More broadly, findings could be relevant to processing high-dimensional data (previous olfactory research has inspired nearest-neighbor search algorithms). Further, this project could lead to novel, and much-needed, uses of connectivity data.