Neurosalience

We sit down with four of the people who made OHBM 2026 happen to get the inside scoop on what to expect! Joining us are Christian Beckman (Program Chair-Elect), Nicola Palomero-Gallagher (Program Chair), Rosanna Olsen (Education Chair), and Michel Thiebaut de Schotten (Local Organizing Committee Chair). With 2,500+ neuroscientists descending on Bordeaux, France from June 14–18, this year's meeting is shaping up to be a big one. We dig into the sessions, keynotes, awards, and why Bordeaux is such a perfect backdrop for the conference — plus great tips for getting the most out of your time there and the newly improved meeting app to help you plan your schedule. Whether you're heading to Bordeaux or just curious about what's in store, this one's a great listen!We hope you enjoy this episode!Chapters:00:00 - Introduction to OHBM 202605:21 - The Success of OHBM: Community and Content10:05 - Methods and Applications in Neuroimaging15:28 - Educational Courses: Structure and Selection18:37 - Keynote Speakers and Program Design23:56 - Symposia vs. Roundtable Discussions30:50 - Brain Hacks: Collaborative Innovation32:40 - Choosing the Right Venue for Conferences37:17 - Exploring Bordeaux: A City of Wine and Culture38:48 - Challenges in Conference Planning46:35 - The Future of Poster Presentations54:24 - Awards and Recognition in the Community58:28 - Enhancing Conference Value and Engagement01:02:02 - Social Aspects of the ConferenceResources:https://www.humanbrainmapping.org/OHBM2026/Episode producers:Xuqian Michelle Li

"Registered reports foster clarity upfront…"Dr. Oscar Esteban is a professor at Lausanne University Hospital whose lab develops open neuroimaging infrastructure, best known for tools like fMRIPrep and MRIQC. Dr. Mallar Chakravarty is Director of the Brain Imaging Center at the Douglas Research Centre at McGill University and co-editor-in-chief of Aperture Neuro.In this conversation, Peter, Mallar, and Oscar unpack what registered reports are and why they emerged as a response to the file drawer problem and publication bias toward positive results. Drawing on Oscar’s firsthand experience using registered reports in his own lab, the discussion explores how front-loading peer review can sharpen experimental design, protect researchers pursuing high-risk science, and give trainees meaningful early career credit. But the conversation doesn’t shy away from harder questions: Can any publication mechanism truly fix an incentive-driven culture? Where does the natural, iterative cycle of exploratory science fit in? And are registered reports the right tool for every type of science or just some of it?We hope you enjoy this episode!Chapters:06:12 - Understanding Registered Reports10:48 - The Origin and Motivation Behind Registered Reports15:03 - Concerns and Challenges of Registered Reports21:08 - Exploratory vs. Confirmatory Research30:50 - The Role of Registered Reports in Training Researchers42:15 - The Role of Pre-registration in Scientific Rigor53:59 - The Systemic Challenges in Scientific Publishing01:06:29 - Concluding Thoughts on Registered ReportsResources:01:02:37 - About PCI Registered Reports - Peer Community In https://rr.peercommunityin.org/aboutEpisode producers:Xuqian Michelle Li

“Shortening scientific loops accelerates discovery”Dr. Satrajit Ghosh is a senior research scientist at the McGovern Institute for Brain Research at MIT and an assistant professor at Harvard Medical School. He has helped advance neuroinformatics, open science, and reproducible neuroimaging through both his research and the development of widely used community tools. His work spans machine learning for neuroimaging, the neural mechanisms of speech, and the use of speech features to inform psychiatric diagnosis and treatment. He earned his bachelor’s degree with honors in computer science from the National University of Singapore and his PhD in cognitive and neural systems from Boston University. He has contributed to influential projects including Nipype, fMRIPrep, and NeuroVault. More recently, he has focused on how shared scientific infrastructure can connect domains, modalities, and scales across neuroscience and help address the field’s growing fragmentation.In this episode, Peter and Satrajit discuss the origins of tools like Nipype and the broader push for reproducible neuroimaging, showing how practical research challenges can inspire infrastructure that benefits the entire field. They also explore functional gradients in the brain and cerebellum, the promise of speech as a scalable biomarker for mental health, and the cautious role AI may play in diagnosis and scientific discovery. A major theme in their conversation is the fragmentation in neuroscience, with knowledge often siloed across methods, scales, and communities. Ghosh argues for a more intelligent scientific infrastructure that connects data, tools, theory, and expertise. He closes with advice to young scientists: experiment often, make mistakes, and learn by discovering where systems fail.We hope you enjoy this episode!Chapters00:00 Introduction to Satra Ghosh and His Work06:46 The Intersection of Control Theory and Speech11:18 Satra’s Academic Journey into Neuroscience20:58 Neuroinformatics and Tool Development34:42 Individual Differences in Brain Structure39:21 Developing tools to augment Experimental Design44:25 Building an Intelligent Infrastructure for Neuroscience58:45 The Role of Theory in Neuroscience01:00:26 Access to Scientific Research Expediting Progress01:06:40 Experience Inherent to Learning 01:09:33 Mapping the Brain’s Functional Gradient01:16:31 AI and Speech Analysis in Mental Health01:29:31 Advice, Fail More, Learn MoreWorks mentioned:34:59 - Marek, S. et al. (2022). Reproducible brain-wide association studies require thousands of individuals. https://doi.org/10.1038/s41586-022-04492-943:44 - Ghosh, Satrajit (2025). An Intelligent Infrastructure as a Foundation for Modern Science.https://doi.org/10.48550/arXiv.2508.1005101:09:33 - Margulies, Daniel S., et al. (2016). Situating the default-mode network along a principal gradient of macroscale cortical organization. https://doi.org/10.1073/pnas.160828211301:10:13 - Xavier Guell, Jeremy D Schmahmann, John DE Gabrieli, Satrajit S Ghosh (2018). Functional gradients of the cerebellum. https://doi.org/10.7554/eLife.36652Tools and resources mentioned:Nipype : an open-source Python framework for building reproducible neuroimaging workflows.https://nipype.readthedocs.io/en/latest/index.htmlfMRIPrep : a robust, analysis-agnostic preprocessing pipeline for functional MRI. https://fmriprep.org/en/stable/OpenScope : an open-science effort for large-scale neuroscience data sharing and analysis.https://www.allenneuraldynamics.org/projects/openscopeDANDI : a platform for publishing, sharing, and processing neurophysiology data. https://about.dandiarchive.org/NeuroVault : A public repository of unthresholded statistical maps, parcellations, and atlases of the brain.https://neurovault.org/Episode producers:Ömer Faruk Gülban, Karthik Sama

Dr. Mario Senden is an assistant professor in the Department of Cognitive Neuroscience at Maastricht University in the Netherlands, where he has spent his entire academic career. He received his bachelor's in psychology in 2009 and his PhD in cognitive computational neuroscience in 2016, both from Maastricht. A pioneer in biophysics-aware deep learning, Mario is known for his work on how large-scale brain networks support communication, integration, and perception. His research spans mesoscale laminar microcircuits to the macro-scale connectome, and his functional whole-brain modeling framework combines large-scale anatomical structure with local dynamics and goal-driven computation — asking not just whether a dynamical regime is biologically plausible, but whether it actually supports perceptual and cognitive function.In this episode, Peter and Mario explore the cutting edge of computational neuroscience and whole-brain modeling. They discuss Mario's influential work on rich club networks, which showed how highly connected cortical hubs dynamically gate information flow during tasks, as well as the principles behind oscillatory behavior in neural systems. A central focus of the conversation is Mario's most recent paper, "The Evolving Landscape of Neuroscience," submitted to Aperture Neuro — a sweeping meta-scientific analysis of roughly half a million neuroscience articles published between 1999 and 2023. Using text embeddings, semantic clustering, and large language models, Mario mapped the structural organization of the field and identified emerging trends and future directions. The conversation also touches on the promise of interdisciplinary approaches, the growing role of AI tools in neuroscience research, and the broader challenge of integrating theories and data across scales and domains to truly understand the brain.We hope you enjoy this episode!Chapters:00:00 - Introduction to Dr. Mario Senden05:11 - Journey from Psychology to Computational Neuroscience10:01 - Understanding Cognitive Computational Neuroscience14:09 - Limits of Current Models in Cognitive Computational Neuroscience20:44 - Exploring the Rich Club Concept in Brain Networks29:22 - The Interplay of Cortex and Subcortex42:44 - Oscillatory Behavior and Network Coordination48:41 - Multi-Scale Modeling in Neuroscience57:49 - Exploring the Evolving Landscape of Neuroscience01:21:08 - Advice for Young ScientistsWorks mentioned:42:19 - Senden et al. (2017). Cortical rich club regions can organize state-dependent functional network formation by engaging in oscillatory behavior. https://doi.org/10.1016/j.neuroimage.2016.10.04448:27 - Pronold et al. (2024). Multi-scale spiking network model of human cerebral cortex. https://doi.org/10.1093/cercor/bhae40948:27 - Senden et al. (2024). Modular-integrative modeling: a new framework for building brain models that blend biological realism and functional performance. https://doi.org/10.1093/nsr/nwad31857:50 - Senden, M. (2025). The Evolving Landscape of Neuroscience. https://doi.org/10.1101/2025.02.13.638094Episode producers:Ömer Faruk Gülban, Xuqian Michelle Li

“Naturalistic stimuli open up new exploration…”Dr. Christopher Baldassano is an associate professor at Columbia University and leads the Dynamic Perception and Memory Lab. With a background in electrical engineering from Princeton and a PhD in computer science from Stanford, Chris has pioneered innovative approaches to understanding memory and cognition. Following a postdoc at Princeton with Uri Hasson and Ken Norman, he joined Columbia in 2018. His research focuses on how the brain processes, stores, and retrieves events using naturalistic stimuli, hidden Markov models, and multivariate analysis techniques.In this episode, Peter and Chris explore the fascinating world of event structures and memory. They discuss Chris’s pioneering work on event scripts, neural frameworks that act as cognitive scaffolds for autobiographical memories. The conversation covers how the brain segments continuous experience into discrete events, the role of event boundaries in memory encoding, and the critical function of the hippocampus in organizing these temporal structures. Chris explains his use of naturalistic stimuli and hidden Markov models to reveal the subtle dynamics of how we combine recurring information to respond more efficiently to future experiences. Along the way, Chris shares valuable insights on the evolution of neuroscience research and offers thoughtful advice for aspiring scientists navigating the field.We hope you enjoy this episode!Chapters:00:00 - Introduction07:37 - Transitioning from Computer Science to Neuroscience13:01 - Exploring Naturalistic Stimuli in Neuroscience18:11 - Hidden Markov Models in Narrative Perception22:46 - Event Boundaries and Memory Encoding27:49 - The Role of the Hippocampus in Memory33:01 - Implications for Mental Health and Memory Disorders38:19 - Enhancing Memory Techniques41:11 - Contextualization in Memory46:19 - Understanding Brain States49:01 - AI and Contextual Knowledge53:29 - Infant Cognition and Event Structures01:01:31 - Future Directions in ResearchWorks mentioned:2:28 - https://www.youtube.com/watch?v=jPLWOBmaLkY(Baldassano talk at NIH workshop on naturalistic stimuli)14:42 - https://pubmed.ncbi.nlm.nih.gov/28772125/(Baldassano et al., 2017 - Neuron - "Discovering Event Structure in Continuous Narrative Perception and Memory")15:02 - https://pubmed.ncbi.nlm.nih.gov/30249790/(Baldassano et al., 2018 - Journal of Neuroscience - "Representation of Real-world Event Schemas During Narrative Perception")18:24 - https://pubmed.ncbi.nlm.nih.gov/29087305/(Vidaurre, Smith & Woolrich, 2017 - PNAS - "Brain network dynamics are hierarchically organized in time" - using Markov models in a different way)19:41 - https://pubmed.ncbi.nlm.nih.gov/17338600/(Zacks et al., 2007 - Psychological Bulletin - "Event perception: A mind-brain perspective" - foundational work on event boundary processes)27:04 - https://pubmed.ncbi.nlm.nih.gov/27121839/(Huth et al., 2016 - Nature - "Natural speech reveals the semantic maps that tile human cerebral cortex" - semantic information stored throughout the brain)37:15 - https://pubmed.ncbi.nlm.nih.gov/22982082/(LePort et al., 2012 - Neurobiology of Learning and Memory - Jim McGaugh's study on highly superior autobiographical memory)53:01 - https://pubmed.ncbi.nlm.nih.gov/36252007/(Yates et al., 2022 - PNAS - "Neural event segmentation of continuous experience in human infants")Episode producers:Xuqian Michelle Li

“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 Background03:28 - Journey from Computer Science to Neuroscience11:13 - The Center for Translational MR Research12:59 - Involvement with OHBM and Community Growth23:44 - Research Focus on Dementia and Brain Networks28:05 - Exploring Cerebral Vasculitis and Dementia Stages44:02 - Functional Specialization and Cognitive Performance45:34 - AI-Based Interventions for Cognitive Health58:30 - Utilizing Large Datasets for Brain Research01:08:53 - Advice for Aspiring NeuroscientistsWorks mentioned:25:18 - https://www.cell.com/neuron/fulltext/S0896-6273(09)00249-925:18 - https://www.cell.com/neuron/fulltext/S0896-6273(12)00227-926:55 - https://www.neurology.org/doi/10.1212/WNL.000000000000831538:33 - https://www.neurology.org/doi/10.1212/wnl.000000000020740141:00 - https://www.sciencedirect.com/science/article/abs/pii/S105381191600234242:33 - https://journals.plos.org/plosone/article?id=10.1371/journal.pone.007941947:46 - https://openaccess.thecvf.com/content/CVPR2023/html/Chen_Seeing_Beyond_the_Brain_Conditional_Diffusion_Model_With_Sparse_Masked_CVPR_2023_paper.html55:11 - https://www.nature.com/articles/s41586-022-04554-yEpisode producers:Karthik Sama, Xuqian Michelle Li

"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 Neuroscience14:25 - Neural Bases of Early Childhood Theory of Mind21:58 - False Belief Task and Theory of Mind25:11 - Attention Schema for Consciousness27:14 - Primary Areas Involved in Theory of Mind31:24 - Impact of Neuro Deficits on Social Cognition33:57 - Role of Environment and Timing on Social Cognition37:11 - Implicit and Explicit Mechanisms of Social Development45:02 - Social Cognition Across Species47:37 - Connecting Neural Code to Social Cognition49:56 - Temporal Progression in Theory of Mind Tasks54:54 - Future Research Directions in Understanding Social Cognition01:00:08 - Infant Learning Inspires AI Development01:04:50 - Advice for Aspiring ScientistsWorks mentioned:14:31 - White matter maturation is associated with the emergence of Theory of Mind in early childhood37:20 - Two systems for thinking about others’ thoughts in the developing brain49:50 - Timing matters: disentangling the neurocognitive sequence of mentalizingEpisode producers:Xuqian Michelle Li, Karthik Sama

Early career researchers give their perspectives on being an academic today. With Arshiya Sangchooli, Natasha L. Taylor, Ashlea Segal, Stefano Moia, Jiajia Yang, and Peter Bandettini Episode ProducersOmer Faruk GulbanXuqian Michelle Li

This OHBM preview podcast offers an in-depth look at how the OHBM Annual Meeting is organized, along with reflections on the unique character of the meeting and the broader OHBM community. Peter Bandettini hosts Jean Chen, Marta Garrido, and Lena Oestreich, with Kevin Sitek serving as co-host. Michael Breakspear joins the discussion in the final 20 minutes. The conversation covers both logistical and thematic aspects of the meeting, providing valuable context for attendees and those interested in the field.Episode ProducersXuqian Michelle LiKarthik Sama

Join host Peter Bandettini as he interviews Michael Milham, a pioneer in functional brain imaging and big data neuroscience. In this episode, Dr. Milham shares insights from his groundbreaking work on large-scale fMRI datasets, deep phenotyping, and the future of precision psychiatry.Topics include: - Challenges and opportunities in big data MRI - Individual variability in brain imaging - Resting-state fMRI and pipeline reliability - Integrating multimodal and real-world data - AI, machine learning, and biomarkers in psychiatryDr. Milham is Chief Science Officer at the Child Mind Institute and a leader behind major initiatives like the creation of large, open-access datasets (e.g., ADHD-200, Healthy Brain Network) to enable population-level studies. Tune in for a deep dive into the evolving landscape of neuroimaging research and its clinical potential.We hope you enjoy this episode!Episode ProducersAlfie WearnOmer Faruk Gulban

This episode features Dr. Sepideh Sadaghiani directing the CONNECTlab at Beckman Institute for Advanced Science & Technology, University of Illinois at Urbana-Champaign. Dr. Sadaghiani’s lab explores large-scale brain networks, focusing on cognitive control, attention, and spontaneous neural activity. Using fMRI, EEG, and genetics, they uncover how brain connectivity shapes perception and behavior. Tune in for cutting-edge insights into the brain’s dynamic communication.Episode ProducersOmer Faruk GulbanKarthik Sama

Join Peter Bandettini as he sits down with Seiji Ogawa, the visionary scientist behind the discovery of BOLD (blood oxygenation level-dependent) contrast fMRI. In this insightful conversation, Dr. Ogawa reflects on his groundbreaking work, the evolution of neuroimaging, and the challenges of translating fMRI into clinical practice. 1. Ogawa’s Early Journey – From Stanford to Bell Labs, and the influences that shaped his career. 2. The Discovery of BOLD fMRI – How experiments with hemoglobin oxygenation laid the foundation for modern neuroimaging. 3. Impact on Neuroscience – Why fMRI became a cornerstone in understanding brain function. 4. Challenges in Clinical Translation – Variability and reliability in single-subject analyses. 5. Scientific Reflections – Ogawa’s thoughts on curiosity, persistence, and the art of discovery. 6. Future Directions – Exploring brain interactions, neurovascular coupling, and innovations in imaging techniques. Notable Quotes: “If you can look into your brain without opening your skull… that’s a great thing.” “The important thing is to know what is important.” “Many phenomena don’t last long, but fMRI has proven to be enduringly significant.” Seiji Ogawa’s contributions have left an indelible mark on neuroscience, inspiring researchers worldwide. Don’t miss this fascinating exploration of his life, work, and ongoing curiosity about the mysteries of the human brain. Episode Producers Omer Faruk Gulban Nagashree Thovinakere

This episode is unique in the sense that it’s actually a talk Peter gave during the OHBM 2024 meeting, specifically during the education session on communicating science. Peter wanted to share this talk because it focuses on the podcast and his own approach to creating it. He discusses his philosophy, heuristics, what he considers important about podcasting, and why he enjoys doing it. The talk emphasizes the value of conversation and explains how the podcast showcases the human side of scientific investigators and the stories behind their research. We hope you enjoy it! Episode producers: Omer Faruk Gulban Xuqian Michelle Li