01-About the Course

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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.


๐Ÿ“š 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

๐Ÿ“ Details

  • Date: June 24, 2025
  • Location: Brisbane Convention and Exhibition Centre
  • Format: In-person interactive tutorials

๐Ÿง  Organizers

  • Davide Momi (Stanford University)
  • John Griffiths (Krembil Centre for Neuroinformatics)
  • Richa Phogat (University of Newcastle)
  • Joana Cabral (University of Minho)

๐Ÿ“‚ Access course materials here โ†’


๐Ÿ•ฐ๏ธ Previous Editions

OHBM 2023 โ€“ Montreal

Title: Whole-brain, Connectome-based Models of Brain Dynamics: From Principles to Applications

OHBM 2023 Montreal

OHBM 2024 โ€“ Seoul

Title: Connectome-based Models of Whole-brain Dynamics: From Theoretical Principle to Practical Application

OHBM 2024 Seoul

02-Speakers

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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

Peter Robinson

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

Michael Breakspear

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

Viktor Jirsa

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

Richa Phogat

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

Davide Momi

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

John Griffiths

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

Huifang Wang

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

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Course Program

Tuesday, June 24, 2025
Room M3 (Mezzanine Level), Brisbane Convention & Exhibition Centre


Morning Session: Foundations

TimeSessionSpeaker
08:00-08:40โ˜• Morning Coffee & GreetsNetworking & Registration
08:40-09:00๐ŸŽฏ Introduction & Workshop OverviewDavide Momi
09:00-09:40๐Ÿ“š History & Biological Rationale of NFTJohn Griffiths
09:40-10:20๐Ÿงฎ Mathematical FrameworksMichael Breakspear
10:20-11:00๐Ÿง  Connectomes of Neural FieldsViktor Jirsa

11:00-11:10 โ˜• Coffee Break

TimeSessionParticipants
11:10-11:30๐Ÿ’ฌ Panel DiscussionChair: Davide Momi Panelists: John Griffiths, Michael Breakspear, Viktor Jirsa
11:30-12:15๐Ÿ’ป Hands-on Session 1Fundamental NFT ImplementationsDavide Momi

12:15-13:00 ๐Ÿฝ๏ธ Lunch Break


Afternoon Session: Applications

TimeSessionSpeaker
13:00-13:40๐ŸŒŠ NFT & Brain RhythmsPeter Robinson
13:40-14:20โšก NFT & NeurostimulationHuifang Wang
14:20-15:00๐Ÿงฉ NFT & Cortico-Hippocampal InteractionsRicha Phogat

15:00-15:10 โ˜• Coffee Break

TimeSessionParticipants
15:10-15:30๐Ÿ’ฌ Panel DiscussionChair: John Griffiths Panelists: Peter Robinson, Huifang Wang, Richa Phogat
15:30-16:10๐Ÿ’ป Hands-on Session 2Advanced Applications & Brain RhythmsDavide Momi
16:10-16:20๐ŸŽŠ Conclusions & Next StepsAll Faculty

Session Highlights

๐ŸŒ… Morning Focus: Theoretical Foundations

  • Historical Context: From 1940s origins to modern applications
  • Mathematical Rigor: Core equations and derivations
  • Network Integration: Connecting theory to brain connectivity

๐ŸŒ† 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

๐Ÿ’ป Hands-on Sessions

  • Interactive Python Notebooks via Google Colab
  • Real Neuroimaging Data for practical experience
  • Take-home Materials for continued learning

๐Ÿ’ฌ 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:

โœ… Understand the mathematical foundations of Neural Field Theory
โœ… Implement basic NFT models using Python
โœ… Apply NFT to real neuroimaging data
โœ… Integrate NFT with brain connectivity data
โœ… 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

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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.


๐Ÿง  Essential Background Knowledge

Neuroscience Foundations

Participants should be comfortable with basic neurophysiological and anatomical concepts:

  • Neural dynamics: Action potentials, synaptic transmission, membrane dynamics
  • Brain anatomy: Cortical layers, thalamus, cortico-thalamic loops
  • Network neuroscience: Structural/functional connectivity, graph representations
  • Neuroimaging: Principles of EEG, MEG, fMRI signals

Mathematical Prerequisites

The course involves modeling and systems analysis:

  • Differential equations: ODEs, PDEs, stability, and time-domain behavior
  • Linear algebra: Eigenvalues, eigenvectors, matrix operations
  • Signal processing: Fourier analysis, filters, spectral methods
  • Dynamical systems: Phase portraits, bifurcations, nonlinear phenomena

Programming Competency

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

โš™๏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.


๐Ÿ“˜ 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), 1296โ€“1313.
  • 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), 189โ€“201.

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), 3065โ€“3074.
  • Jirsa, V.K., et al. (2017). The virtual brain: a simulator of primate brain network dynamics. Frontiers in Neuroinformatics, 11, 10.

Mathematical Foundations

  • Ermentrout, G.B., Terman, D.H. (2010). Mathematical Foundations of Neuroscience. Chapters 1โ€“3, 8โ€“9
  • Dayan, P., Abbott, L.F. (2001). Theoretical Neuroscience. Chapters 5โ€“7, 15

Computational Methods


If you have questions about preparation or access, please contact the organizers via the Contact page.

05-Organizers

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Course Organizers

Meet the dedicated team behind the OHBM 2025 Neural Field Theory Educational Course.


Davide Momi, PhD

Stanford University
Lead Organizer & Course Director

Davide Momi

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

Richa Phogat

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

John Griffiths

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

Joana Cabral

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:

๐ŸŽฏ Accessibility - Making advanced computational concepts understandable for researchers from diverse backgrounds

๐Ÿ”ฌ Scientific Rigor - Maintaining high academic standards while ensuring practical applicability

๐Ÿค Open Science - Providing all materials freely through public repositories

๐Ÿ’ป Hands-on Learning - Emphasizing practical implementation alongside theoretical understanding

๐ŸŒ Community Building - Fostering connections within the neural field theory research community


Course Legacy

Building on the success of previous OHBM educational courses:

Each course has been designed to advance the field while maintaining our commitment to open science and educational excellence.


For questions about the course organization or content, please contact the organizing team through the official OHBM channels.

06-Contact

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๐Ÿ“ฌ Contact & Community

Stay connected with the NFT course community during and after OHBM.


๐Ÿง  Join the Slack Workspace

To ask questions, get updates, or share your experience, join our course Slack:

๐Ÿ‘‰ Click here to join Slack
(Youโ€™ll be added to channels like #welcome, #questions, #social, and #colab-help)


๐Ÿ“ก Connect with the Organizer