Neurosalience
Neurosalience
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Neurosalience #S6E3 with Kendrick Kay - Philosophy, deep sampling, and the advancing tide of AI
1 hour 26 minutes Posted Dec 15, 2025 at 8:08 am.
Introduction to Kendrick Kay and His Work04:51 - Philosophy’s Influence on Neuroscience17:17 - How Far Will fMRI Take Us?23:27 - Understanding Attention in Neuroscience30:00 - Science as a Process34:17 - The Role of Large Language Models (LLMs) in Scientific Progress38:29 - Why Humans Should Stay in the Equation40:30 - Creativity vs. AI in Scientific Research54:48 - Dr. Kay’s Natural Scenes Dataset (NSD)01:00:27 - Deep Sampling: Considerations and Implications01:08:00 - Accounting for biological variation in Brain Scans: Differences and Similarities01:13:00 - Separating Hemodynamic Effects from Neural Effects01:16:00 - Areas of Hope and Progress in the field01:21:00 - How Should We Benchmark Progress?01:22:59 - Advice for Aspiring ScientistsWorks mentioned:54:48 -  https://www.nature.com/articles/s41593-021-00962-x54:50 - https://www.sciencedirect.com/science/article/pii/S0166223624001838?via%3DihubEpisode producers:Xuqian Michelle Li, Naga Thovinakere
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“What does it actually mean to understand the brain?”Dr. Kendrick Kay is a computational neuroscientist and neuroimaging expert at the University of Minnesota’s Center for Magnetic Resonance Research, where he is an Associate Professor in the Department of Radiology. With training spanning philosophy and neuroscience, from a bachelor’s degree in philosophy at Harvard University to a PhD in neuroscience from UC Berkeley, Dr. Kay’s work bridges deep theoretical questions with cutting-edge neuroimaging methods.In this conversation, Peter Bandettini and Kendrick Kay explore the evolving landscape of neuroscience at the intersection of fMRI, philosophy, and artificial intelligence. They reflect on the limits of current neuroimaging methodologies, what fMRI can and cannot tell us about brain mechanisms, and why creativity and human judgment remain central to scientific progress. The discussion also dives into Dr. Kay’s landmark contributions to fMRI decoding and the Natural Scenes Dataset, a high-resolution resource that has become foundational for computational neuroscience and neuro AI research.Along the way, they examine deep sampling in neuroimaging, individual variability in brain data, and the challenges of separating neural signals from hemodynamic effects. Framed by broader questions about understanding benchmarking progress, and the growing role of LLM’s in neuroscience, this wide-ranging conversation offers a thoughtful look at where the field has been and where it may be headed.We hope you enjoy this episode!Chapters:00:00 - Introduction to Kendrick Kay and His Work04:51 - Philosophy’s Influence on Neuroscience17:17 - How Far Will fMRI Take Us?23:27 - Understanding Attention in Neuroscience30:00 - Science as a Process34:17 - The Role of Large Language Models (LLMs) in Scientific Progress38:29 - Why Humans Should Stay in the Equation40:30 - Creativity vs. AI in Scientific Research54:48 - Dr. Kay’s Natural Scenes Dataset (NSD)01:00:27 - Deep Sampling: Considerations and Implications01:08:00 - Accounting for biological variation in Brain Scans: Differences and Similarities01:13:00 - Separating Hemodynamic Effects from Neural Effects01:16:00 - Areas of Hope and Progress in the field01:21:00 - How Should We Benchmark Progress?01:22:59 - Advice for Aspiring ScientistsWorks mentioned:54:48 -  https://www.nature.com/articles/s41593-021-00962-x54:50 - https://www.sciencedirect.com/science/article/pii/S0166223624001838?via%3DihubEpisode producers:Xuqian Michelle Li, Naga Thovinakere