Neurosalience

OHBM

The Neurosalience podcast is supported by the Organization for Human Brain Mapping (OHBM). Dr. Peter Bandettini interviews neuroscientists who measure, map, and model brain function and structure and delves into latest advancements, challenges, controversies, and controversies. He engages young and old and strives to add insight and perspective wherever the conversation goes.

  1. JAN 8

    Neurosalience #S6E5 with Ahmed Khalil - BOLD delay mapping for stroke perfusion imaging

    Dr. Ahmed Khalil is an MD-PhD currently serving his residency in radiology at the Institute of Neuroradiology at Charité University Hospital in Berlin. Originally from Sudan, he has been doing pioneering work on resting-state BOLD latency mapping, a technique that reveals flow deficits in the brain associated with stroke. His research demonstrates that this approach compares favorably with the current clinical gold standard of dynamic susceptibility contrast imaging using gadolinium, while capturing useful data in as little as two minutes. In this episode, Peter and Ahmed discuss his work translating advanced MRI techniques into clinical practice. They explore how BOLD latency mapping can detect perfusion deficits and compare with both traditional gadolinium-based methods and DTI for identifying stroke lesions. The conversation delves into the broader challenge faced by all promising research methods: what does it actually take to move from successful proof-of-concept to daily clinical practice on scanners around the world? Ahmed and Peter also talk about the cultural gap between research-level image processing and the clinical preference for minimally processed, interpretable data and how AI might help bridge that divide. Along the way, Ahmed shares valuable advice for MD-PhD students on the importance of collaboration, learning from diverse experts, and maintaining curiosity across disciplines. We hope you enjoy this episode! Chapters: 00:00 - Introduction to Ahmed Khalil and His Work 05:02 - Journey into Medicine and Radiology 12:10 - The Challenges of Methods Development in Clinical Applications 22:15 - Research on Resting State BOLD Latency 37:27 - Clinical Implications of Perfusion Imaging in Stroke 43:52 - Challenges in Clinical Implementation of New Imaging Techniques 47:50 - The Role of AI in Radiology and Imaging Interpretation 52:42 - Future Aspirations and Research Directions in Imaging 01:01:03 - Collaborative Efforts in Physiologic MRI Book Project 01:03:25 - Advice for Aspiring MD-PhD Students Works mentioned: 22:48 - https://pubmed.ncbi.nlm.nih.gov/23378326/ (Lv et al., 2013 - First paper showing BOLD delay in stroke with Arno Villinger) 23:08 - https://www.ahajournals.org/doi/10.1161/STROKEAHA.116.015566 (Khalil et al., 2017 - Stroke paper, Relationship between BOLD delay and DSC-MRI) 23:08 - https://pubmed.ncbi.nlm.nih.gov/30334657/ (Khalil et al., 2018 - JCBFM paper, Longitudinal changes in BOLD delay) 39:00 - https://pubmed.ncbi.nlm.nih.gov/34323339/ (Hu et al., 2021 - Human Brain Mapping paper with Daniel Margulies - ICA approach) Episode producers: Ömer Faruk Gülban, Xuqian Michelle Li

    1h 6m
  2. 12/29/2025

    Neurosalience #S6E4 with Juan Helen Zhou - Revolutionizing brain imaging with AI

    “What makes certain brain networks vulnerable to disease—and can AI help us predict what comes next?” Dr. Juan Helen Zhou is a computational neuroscientist at the National University of Singapore, where she is an Associate Professor and Director of the Center for Translational Magnetic Resonance Research at the Yong Loo Lin School of Medicine. She leads the Multimodal Neuroimaging in Neuropsychiatric Disorders Laboratory, integrating multimodal brain imaging and machine learning to study network vulnerability in aging and neuropsychiatric disorders, including dementia, psychosis, and ADHD. In this episode, Peter and Helen discuss her path from computer science to neuroscience and how that background shaped her approach to brain imaging and AI. They explore her work on dementia, including the role of cerebral vascular disease, why different forms of dementia must be understood as distinct network-level disorders, and how selective brain network vulnerabilities can predict cognitive decline. The discussion also covers recent advances from Dr. Zhou’s lab in reconstructing images from brain activity using generative AI and self-supervised learning, highlighting both the promise and challenges of these approaches. Along the way, Helen reflects on the importance of collaboration in neuroscience and shares advice for early-career researchers on persistence, communication, and navigating interdisciplinary science. We hope you enjoy this episode! Chapters: 00:00 - Introduction to Helen Zhou and Her Background 03:28 - Journey from Computer Science to Neuroscience 11:13 - The Center for Translational MR Research 12:59 - Involvement with OHBM and Community Growth 23:44 - Research Focus on Dementia and Brain Networks 28:05 - Exploring Cerebral Vasculitis and Dementia Stages 44:02 - Functional Specialization and Cognitive Performance 45:34 - AI-Based Interventions for Cognitive Health 58:30 - Utilizing Large Datasets for Brain Research 01:08:53 - Advice for Aspiring Neuroscientists Works mentioned: 25:18 - https://www.cell.com/neuron/fulltext/S0896-6273(09)00249-9 25:18 - https://www.cell.com/neuron/fulltext/S0896-6273(12)00227-9 26:55 - https://www.neurology.org/doi/10.1212/WNL.0000000000008315 38:33 - https://www.neurology.org/doi/10.1212/wnl.0000000000207401 41:00 - https://www.sciencedirect.com/science/article/abs/pii/S1053811916002342 42:33 - https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0079419 47:46 - https://openaccess.thecvf.com/content/CVPR2023/html/Chen_Seeing_Beyond_the_Brain_Conditional_Diffusion_Model_With_Sparse_Masked_CVPR_2023_paper.html 55:11 - https://www.nature.com/articles/s41586-022-04554-y Episode producers: Karthik Sama, Xuqian Michelle Li

    1h 8m
  3. 12/15/2025

    Neurosalience #S6E3 with Kendrick Kay - Philosophy, deep sampling, and the advancing tide of AI

    “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 Work 04:51 - Philosophy’s Influence on Neuroscience 17:17 - How Far Will fMRI Take Us? 23:27 - Understanding Attention in Neuroscience 30:00 - Science as a Process 34:17 - The Role of Large Language Models (LLMs) in Scientific Progress 38:29 - Why Humans Should Stay in the Equation 40:30 - Creativity vs. AI in Scientific Research 54:48 - Dr. Kay’s Natural Scenes Dataset (NSD) 01:00:27 - Deep Sampling: Considerations and Implications 01:08:00 - Accounting for biological variation in Brain Scans: Differences and Similarities 01:13:00 - Separating Hemodynamic Effects from Neural Effects 01:16:00 - Areas of Hope and Progress in the field 01:21:00 - How Should We Benchmark Progress? 01:22:59 - Advice for Aspiring Scientists Works mentioned: 54:48 -  https://www.nature.com/articles/s41593-021-00962-x 54:50 - https://www.sciencedirect.com/science/article/pii/S0166223624001838?via%3Dihub Episode producers: Xuqian Michelle Li, Naga Thovinakere

    1h 27m
  4. 11/13/2025

    Neurosalience #S6E2 with Charlotte Grosse Wiesmann - Inferring white matter connections through developmental milestones

    "AI is really bad at perspective taking…" Dr. Charlotte Grosse Wiesmann is a cognitive neuroscientist exploring how the human social brain takes shape in early life. She is a Professor at the University of Technology Nuremberg and directs the Research Group on Social Brain Development at the Max Planck Institute in Leipzig. Her research blends developmental psychology, brain imaging, and computational modeling to uncover how infants begin to infer other people’s beliefs, intentions and mental states.  In this conversation, Dr. Wiesmann unpacks how children’s brains develop the capacity for social understanding and theory of mind. Drawing on developmental psychology and neuroimaging, she reveals how the brain transforms as children first succeed on false-belief tasks, a fleeting yet powerful window into the emergence of the social mind. Within this context, the conversation explores white matter maturation, environmental influences, and brain plasticity, offering fresh insights into how studying infant development can inform the future of AI. Join the conversation to discover how early brain development is reshaping our understanding of our social minds. We hope you enjoy this episode! Chapters: 00:00 - A Journey from Physics to Neuroscience 14:25 - Neural Bases of Early Childhood Theory of Mind 21:58 - False Belief Task and Theory of Mind 25:11 - Attention Schema for Consciousness 27:14 - Primary Areas Involved in Theory of Mind 31:24 - Impact of Neuro Deficits on Social Cognition 33:57 - Role of Environment and Timing on Social Cognition 37:11 - Implicit and Explicit Mechanisms of Social Development 45:02 - Social Cognition Across Species 47:37 - Connecting Neural Code to Social Cognition 49:56 - Temporal Progression in Theory of Mind Tasks 54:54 - Future Research Directions in Understanding Social Cognition 01:00:08 - Infant Learning Inspires AI Development 01:04:50 - Advice for Aspiring Scientists Works mentioned: 14:31 -  White matter maturation is associated with the emergence of Theory of Mind in early childhood 37:20 -  Two systems for thinking about others’ thoughts in the developing brain 49:50 -  Timing matters: disentangling the neurocognitive sequence of mentalizing Episode producers: Xuqian Michelle Li, Karthik Sama

    1h 9m

Ratings & Reviews

5
out of 5
14 Ratings

About

The Neurosalience podcast is supported by the Organization for Human Brain Mapping (OHBM). Dr. Peter Bandettini interviews neuroscientists who measure, map, and model brain function and structure and delves into latest advancements, challenges, controversies, and controversies. He engages young and old and strives to add insight and perspective wherever the conversation goes.

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