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

Neurosalience • December 29, 2025 • Solo Episode

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“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

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