Neural Field Theory & Brain Network Modelling @ OHBM 2025
This OHBM 2025 Educational Course offers a hands-on introduction to Neural Field Theory (NFT) and its application to connectome-based brain modelling.
The course focuses on the simulation of brain dynamics across large-scale networks using biophysically grounded field models, with comparisons to traditional neural mass approaches.
๐ Topics include
Theoretical foundations of Neural Field Theory
Differences between Neural Mass Models (NMMs) and NFT
Integration with empirical structural connectomes
Practical coding sessions using Python and Colab
๐ Details
Date: June 24, 2025
Location: Brisbane Convention and Exhibition Centre
Format: In-person interactive tutorials
๐ง Organizers
Davide Momi (Stanford University)
John Griffiths (Krembil Centre for Neuroinformatics)
Title: Whole-brain, Connectome-based Models of Brain Dynamics: From Principles to Applications
OHBM 2024 โ Seoul
Title: Connectome-based Models of Whole-brain Dynamics: From Theoretical Principle to Practical Application
02-Speakers
Distinguished Researchers
Our course brings together leading experts in Neural Field Theory, computational neuroscience, and brain modeling from around the world.
Peter Robinson, PhD
University of Sydney Talk:Mathematical Foundations and Corticothalamic Neural Field Theory
Dr. Robinson is a foundational contributor to neural field theory, particularly in corticothalamic system modeling and brain activity eigenmodes. His work encompasses the mathematical derivation of neural field equations from physiological principles, development of the NFTsim simulation package, and groundbreaking research on brain rhythms including alpha, mu, and tau oscillations. His contributions include demonstrating how just four corticothalamic eigenmodes can explain key features of cortical rhythms, and establishing connections between brain geometry, connectivity, and dynamics. Professor Robinson is based at the University of Sydney’s School of Physics and Center for Integrative Brain Function, where his extensive research spans over two decades focusing on continuum approaches to brain modeling, corticothalamic dynamics, and the mathematical foundations underlying brain oscillations and connectivity.
Michael Breakspear, PhD
University of Newcastle Talk:Neural Field Theory: Mathematical Foundations and Cortical Rhythms
Dr. Breakspear is a distinguished researcher and group leader of the Systems Neuroscience Group at the University of Newcastle. He holds a Doctor of Philosophy degree from the University of Sydney, where he also obtained a Bachelor of Science (Medical) (Honours), a Bachelor of Arts, and a Bachelor of Medicine and Bachelor of Surgery. His expertise spans computational neuroscience and translational neuroimaging. In computational neuroscience, his contributions focus on dynamic models of large-scale brain activity, toolbox development, and detection of nonlinear dynamics in empirical data. His translational imaging work encompasses healthy aging, dementia, bipolar disorder, and schizophrenia, with particular emphasis on connectomics and risk prediction. Alongside his research career, Michael has pursued training in psychiatry, combining clinical sessions in adult psychiatry with research on recovery-focused treatment of mood disorders, psychosis, and addiction. His multifaceted expertise bridges theoretical models and real-world applications, advancing understanding of brain function while improving mental health outcomes.
Viktor Jirsa, PhD
Institut de Neurosciences des Systรจmes, Marseille Talk:From Theory to Applications: Virtual Brain Twins in Clinical Neuroscience
Dr. Jirsa brings a unique perspective combining theoretical physics and computational neuroscience to understand how network structure constrains functional dynamics. Originally trained in Theoretical Physics and Philosophy in the 1990s, he has made fundamental contributions to understanding how network structure constrains the emergence of functional dynamics using methods from nonlinear dynamic system theory and computational neuroscience. His pioneering work has earned international recognition, including the Franรงois Erbsmann Prize (2001), NASPSPA Early Career Distinguished Scholar Award (2004), and Grand Prix de Recherche de Provence (2018). As one of the Lead Scientists in the Human Brain Project and The Virtual Brain initiative, he serves on multiple editorial boards and has published over 150 scientific articles and book chapters, including co-editing several influential works such as the Handbook of Brain Connectivity.
Richa Phogat, PhD
University of Newcastle Talk:Cortico-Hippocampal Interactions: Eigenmodes and Neural Field Modeling
Dr. Phogat is a Computational Neuroscience Fellow at the University of Newcastle, NSW. Her current research focuses on developing a physically principled framework of cortico-hippocampal interactions. This framework helps understand how dynamic coupling and mode mixing drive healthy brain rhythms and how their disruption leads to more pathological brain activity. Her work combines theoretical neural field modeling with practical implementations to advance our understanding of complex brain dynamics.
Davide Momi, PhD
Stanford University Talk:Hands-on Neural Field Theory: From Theory to Implementation
Dr. Momi is a computational neuroscientist at Stanford University, specializing in brain stimulation, neural field theory, and hands-on education in computational neuroscience. Building on the success of previous OHBM educational courses, he leads comprehensive hands-on sessions that bridge theoretical concepts with practical applications using interactive Python notebooks. His expertise includes developing educational frameworks that make complex computational neuroscience concepts accessible to researchers from diverse backgrounds, with a strong commitment to open science and reproducible research practices.
John Griffiths, PhD
University of Toronto & Centre for Addiction and Mental Health Talk:Historical Overview and Conceptual Foundations of Neural Field Theory
Dr. Griffiths is an esteemed cognitive and computational neuroscientist and director of GriffLab. He has held various prestigious research positions, including a post-doctoral fellowship at the University of Sydney School of Physics, where he collaborated with Professor Peter Robinson. He subsequently moved to Toronto, Canada, conducting research at the Rotman Research Institute with Dr. Randy McIntosh and the Krembil Research Institute with Dr. Jeremie Lefebvre. In January 2019, Dr. Griffiths joined the Krembil Centre for Neuroinformatics at CAMH and the University of Toronto as a Scientist and Assistant Professor. With strong technical expertise in multimodal neuroimaging data analysis, scientific computing, and numerical simulations of large-scale brain dynamics, Dr. Griffiths is an active contributor to the scientific, software development, and educational endeavors of the Virtual Brain Project.
Huifang Wang, PhD
Institut de Neurosciences des Systรจmes, Aix Marseille Universitรฉ Talk:Virtual Brain Twins: From Basic Science to Clinical Applications
Dr. Wang specializes in personalized whole-brain modeling through virtual brain twins, bridging basic neuroscience and clinical applications. Her research encompasses the development of virtual epileptic patient pipelines aimed at improving diagnosis and treatment outcomes. As leader of the DEPTH (Digital Epileptic and Psychiatric Twins for Health) research group, she advances virtual brain twin technologies for multiple brain disorders including epilepsy and psychiatric conditions, demonstrating the clinical translation potential of neural field theory approaches. Dr. Wang is a neuroscientist at the Institut de Neurosciences des Systรจmes (INS), part of Aix-Marseille University and INSERM, France, where her research focuses on personalized whole-brain modeling ranging from basic science to clinical applications.
Course Structure & Integration
The course combines theoretical depth with practical application:
Morning Session: Historical foundations and mathematical derivations
Afternoon Session: Applications and hands-on implementations
Interactive Elements: Google Colab notebooks with real neuroimaging data
Open Science: All materials freely available through public repositories
This combination of foundational contributors to NFT and researchers applying these methods to contemporary brain mapping challenges makes the course particularly valuable for bridging mathematical theory and empirical neuroscience.
03-Program
Course Program
Tuesday, June 24, 2025 Room M3 (Mezzanine Level), Brisbane Convention & Exhibition Centre
Morning Session: Foundations
Time
Session
Speaker
08:00-08:40
โ Morning Coffee & Greets
Networking & Registration
08:40-09:00
๐ฏ Introduction & Workshop Overview
Davide Momi
09:00-09:40
๐ History & Biological Rationale of NFT
John Griffiths
09:40-10:20
๐งฎ Mathematical Frameworks
Michael Breakspear
10:20-11:00
๐ง Connectomes of Neural Fields
Viktor Jirsa
11:00-11:10 โ Coffee Break
Time
Session
Participants
11:10-11:30
๐ฌ Panel Discussion
Chair: Davide Momi Panelists: John Griffiths, Michael Breakspear, Viktor Jirsa
Historical Context: From 1940s origins to modern applications
Mathematical Rigor: Core equations and derivations
Network Integration: Connecting theory to brain connectivity
๐ Afternoon Focus: Real-World Applications
Clinical Relevance: Neurostimulation and therapeutic applications
Biological Insights: Brain rhythms and cortico-hippocampal dynamics
Hands-on Practice: Interactive coding with real data
๐ป Hands-on Sessions
Interactive Python Notebooks via Google Colab
Real Neuroimaging Data for practical experience
Take-home Materials for continued learning
๐ฌ Panel Discussions
Q&A with Experts on cutting-edge research
Future Directions in Neural Field Theory
Integration Opportunities for your research
Learning Outcomes
By the end of this course, participants will:
โ Understand the mathematical foundations of Neural Field Theory โ Implement basic NFT models using Python โ Apply NFT to real neuroimaging data โ Integrate NFT with brain connectivity data โ Explore clinical applications and future directions
All materials will be made freely available through our public GitHub repository following OHBM’s commitment to open science.
04-Prerequisites
Course Preparation & Prerequisites
This guide will help you get the most out of the OHBM 2025 Neural Field Theory Educational Course. It covers the background knowledge, pre-course readings, and technical setup necessary for this hands-on experience.
๐ง Essential Background Knowledge
Neuroscience Foundations
Participants should be comfortable with basic neurophysiological and anatomical concepts:
Sessions will be run entirely in Google Colab, so no local installation is required. However, proficiency in Python is expected:
Python basics: Functions, control structures, data types
Scientific computing: NumPy, SciPy, matplotlib
Neuroimaging tools: MNE-Python, Nilearn
Version control: Cloning GitHub repositories
โ๏ธ Technical Setup
You do not need to install any software locally.
All hands-on coding will be done via Google Colab, using pre-configured environments. You only need:
A Google account
A modern browser (Chrome or Firefox recommended)
A laptop and reliable Wi-Fi at the venue
We recommend signing into your Google account beforehand to avoid login issues.
๐ Pre-Course Study Materials
Core NFT Readings
These foundational papers will help orient you to the theory and applications of Neural Field Modeling:
Core Theory
Robinson, P.A., et al. (2001). Prediction of electroencephalographic spectra from neurophysiology. Phys. Rev. E, 63(2), 021903.
Breakspear, M., et al. (2006). A unifying explanation of primary generalized seizures through nonlinear brain modeling and bifurcation analysis. Cerebral Cortex, 16(9), 1296โ1313.
Roberts, J.A., Robinson, P.A. (2008). Modeling absence seizure dynamics: implications for basic mechanisms and measurement of thalamocortical and corticothalamic latencies. J. Theor. Biol., 253(1), 189โ201.
Contemporary Applications
Deco, G., et al. (2018). Whole-brain multimodal neuroimaging model using serotonin receptor maps explains non-linear functional effects of LSD. Current Biology, 28(19), 3065โ3074.
Jirsa, V.K., et al. (2017). The virtual brain: a simulator of primate brain network dynamics. Frontiers in Neuroinformatics, 11, 10.
If you have questions about preparation or access, please contact the organizers via the Contact page.
05-Organizers
Course Organizers
Meet the dedicated team behind the OHBM 2025 Neural Field Theory Educational Course.
Davide Momi, PhD
Stanford University Lead Organizer & Course Director
Dr. Momi serves as the lead organizer and course director, bringing his expertise in computational neuroscience and educational course development. As a computational neuroscientist at Stanford University, he specializes in brain stimulation, neural field theory, and hands-on education in computational neuroscience. His previous success organizing OHBM educational courses, including the highly acclaimed 2024 whole-brain modeling course, demonstrates his commitment to making complex computational concepts accessible to diverse research communities.
Richa Phogat, PhD
University of Newcastle Co-Organizer & Technical Coordinator
Dr. Phogat serves as co-organizer and coordinates the technical aspects of the course. As a Computational Neuroscience Fellow specializing in cortico-hippocampal interactions and neural field modeling, she brings both theoretical expertise and practical implementation experience. Her role ensures seamless execution of the interactive coding sessions and provides technical support to participants during hands-on activities, while contributing to the overall course organization and content development.
John Griffiths, PhD
University of Toronto & Centre for Addiction and Mental Health Co-Organizer & Educational Coordinator
Dr. Griffiths brings extensive experience in educational course organization and computational neuroscience research. As director of GriffLab and an active contributor to the Virtual Brain Project, he has co-organized multiple successful OHBM educational courses. His expertise in multimodal neuroimaging data analysis and large-scale brain dynamics modeling, combined with his educational leadership, ensures the course maintains high academic standards while remaining accessible to participants from diverse backgrounds.
Joana Cabral, PhD
University of Minho Co-Organizer & Scientific Advisory
Dr. Cabral serves as co-organizer and provides scientific oversight for the course. Her expertise in computational neuroscience and brain dynamics modeling brings valuable perspective to the educational program design. As a researcher focused on large-scale brain networks and dynamical systems approaches to neuroscience, she ensures the course content reflects current best practices and cutting-edge developments in the field.
Organizing Philosophy
Our organizing team is committed to:
๐ฏ Accessibility - Making advanced computational concepts understandable for researchers from diverse backgrounds
๐ฌ Scientific Rigor - Maintaining high academic standards while ensuring practical applicability
๐ค Open Science - Providing all materials freely through public repositories