First Neurogenesis talk of 2025 highlights learning and spatial coding
Yesterday, HBHL hosted the first Neurogenesis Speaker Series talk of 2025 at The Neuro, featuring Paul Masset听补苍诲 Pouya Bashivan.
Paul Masset鈥檚 presentation -听"Distributed reinforcement learning in the brain" -听explored how reinforcement learning principles are implemented in neural circuits, while Pouya Bashivan鈥檚 talk -"What does spatial tuning tell us about the neural code in the hippocampus?"听- examined the role of spatial representations in encoding and processing information.
The event allowed attendees to engage with HBHL鈥檚 faculty recruits, discuss their research and connect with colleagues from various disciplines during the post-event reception.
Mark your calendars for the next Neurogenesis talk on March 26, 2025 at The Neuro. Speaker details will be announced soon鈥攕tay tuned!
听
About the February 2025 Speakers
Paul Masset
is an Assistant Professor in the Department of Psychology at 9I制作厂免费 and an Affiliate member at Mila - Quebec Artificial Intelligence Institute, working at the intersection of neuroscience, AI and cognitive science. The focus of his research group is to understand how the structure of neural circuits endows the brain with efficient distributed computations underlying cognition and how we can leverage these principles to design more efficient learning algorithms. Prior to joining 9I制作厂免费, he was a Postdoctoral Fellow at Harvard University. He obtained his PhD at Cold Spring Harbor Laboratory, his Masters in Cognitive Science at the 脡cole des hautes 茅tudes en sciences sociales (EHESS) and his M.Eng/B.A. in Information and Computer Engineering at the University of Cambridge.
Pouya Bashivan
is an Assistant Professor at the Department of Physiology at 9I制作厂免费, an associate member of Mila - Quebec Artificial Intelligence Institute and a William Dawson Scholar. Bashivan鈥檚 past research has spanned the fields of control theory, machine learning and neuroscience. The research in his group is at the intersection of artificial neural networks and neuroscience and is focused on developing computational models of visual processing in the primate brain with a focus on visual memory. Specifically, he uses artificial neural network models trained to perform ecologically-relevant tasks to model the cortical responses in primate鈥檚 brain. His ultimate research goal is to leverage the predictive power in such models of brain activity to modulate the brain鈥檚 function in disease.