This past November, I had the privilege of directing the 13th Annual Tufts Neuroscience Symposium—a day filled with inspiring talks, lively discussions, and deep engagement across the neuroscience community. This year’s symposium centered around Systems, Computational, and Cognitive Neuroscience, featuring an exceptional lineup of speakers who brought diverse perspectives to our understanding of brain function.
A Day of Insightful Talks
The symposium kicked off with Nao Uchida (Harvard) delivering a thought-provoking keynote on the role of dopamine in reinforcement learning. His talk shed light on circuit motifs underlying reward prediction errors, proposing a mechanism involving feedback and sign reversal of ventral striatal input to midbrain dopamine neurons. This framework offers a compelling way to think about how the brain computes reward-related signals.
Following Uchida, John Murray (Dartmouth) introduced the concept of task generalization through neural kernels—a powerful approach to understanding common frameworks for behavioral and neural generalization across humans and artificial intelligence models. His talk highlighted how computational methods can bridge gaps in our understanding of cognition.
Shantanu Jadhav (Brandeis) then took us on a journey into hippocampal-prefrontal interactions in spatial learning and generalization. He presented compelling evidence that while frontal cortex representations generalize across tasks, the hippocampus maintains environment-specific maps, offering key insights into memory and decision-making processes.
Anne Collins (UC Berkeley) provided a thought-provoking counterpoint to standard reinforcement learning models. Her research suggests that certain human cognitive functions are better explained by a combination of working memory and habitual behaviors rather than classic reinforcement learning frameworks. This perspective challenges prevailing theories and opens new directions for understanding human learning.
Gina Kuperberg (Tufts) brought an exciting cognitive neuroscience perspective, exploring language learning through the lens of modern artificial intelligence. In an era dominated by large language models, her work examines how human linguistic processing aligns (or diverges) from AI-driven models—a particularly relevant topic in today’s rapidly evolving research landscape.
Closing the symposium, Sabine Kastner (Princeton) delivered the Shukart Lecture, offering a fascinating retrospective on her career studying the neural mechanisms of attention. She emphasized the critical role of the higher-order thalamus in attentional control, providing a synthesis of two decades of groundbreaking research.
More Than Just Talks
Beyond the scientific discussions, the symposium fostered community engagement, with students actively introducing speakers, networking opportunities, and valuable interactions with Tufts leadership. These moments underscore the importance of symposia not just as venues for presenting research but also as spaces for fostering collaboration, mentorship, and new ideas.
Looking Ahead
The success of this year’s symposium reaffirms the importance of interdisciplinary dialogue in neuroscience. As we push forward in understanding the brain, these events serve as a catalyst for new questions, collaborations, and discoveries. I look forward to seeing where these conversations lead and to many more engaging symposia in the future.