Building patient-personalized brain simulations to improve interpretation of neuroimaging and neurostimulation data


Neuroscience as a field is very good at measuring things and poking things. It has an impressive armoury of experimental techniques using electricity, light, acoustics, biochemistry, and more to measure and modulate neural activity in everything from a blob of cells on a dish to a conscious human in a surgical theatre or an MRI scanner.

What neuroscience is less good at, for the most part, is theory; i.e. understanding the sources of the patterns we see in our measurements, and what is actually happening in the brain when we poke it with electrical stimulation and the like. The sub-field that deals with developing theoretical mechanistic understanding of brain processes is known as computational neuroscience. It does this by building mathematical models that allow us to simulate and study brain activity “in-silico”.

In our research we bring the tools of computational neuroscience to the domains of neuroimaging and brain stimulation. The paradigm we use for this, whole-brain modelling, blends elements from neurophysiology, cognitive neuroscience, neuroanatomy, connectomics, complex networks, dynamical systems, machine learning, and biophysics.

We combine whole-brain computational modelling of network dynamics, oscillations, plasticity, and cognitive function with experimental and data analytic work across multiple neuroimaging and neurostimulation modalities (EEG, MEG, s/d/fMRI, fNIRS, TMS, TES). This unique theoretical-experimental approach is applied to questions on both basic principles of brain organization, as well as how it is affected in neuropsychiatric and neurological disease.

Schematic of whole-brain modelling approach (Griffiths et al. 2022)

Research Areas

The core research activites of the group consist of applying whole-brain modelling techniques to a variety of research questions relating to brain stimulation, brain rhythms, and brain networks. Most projects involve intersections of 2 or 3 of these, and have both basic science and clinical application components, such as therapeutic brain stimulation for depression. We also have a number of additional ongoing projects involving mobile EEG, fNIRS, sleep, neuroinformatics, and computational modelling methodology. See below for more info on each of these, as well as links to relevant publications and reproducible code.

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Selected Publications

More publications here

Functional magnetic resonance imaging (fMRI) has long been a cornerstone in the study of brain activity, but its high operational …

Alpha rhythms are a robust phenomenon prominently observed in posterior resting state electroencephalogram (EEG) that has been shown to …

Resting-state brain activity, as observed via functional magnetic resonance imaging (fMRI), displays non-random fluctuations whose …

Recent developments in mathematical modelling of EEG data enable estimation and tracking of otherwise-inaccessible neurophysiological …

The human brain exhibits a modular and hierarchical structure, spanning low-order sensorimotor to high-order cognitive/affective …

A major question in systems and cognitive neuroscience is to what extent neurostimulation responses are driven by recurrent activity. …

Connectome-based neural mass modelling is the emerging computational neuroscience paradigm for simulating large-scale network dynamics …

Transcranial magnetic stimulation (TMS) is an emerging alternative to existing treatments for major depressive disorder (MDD). The …

Whole-Brain Modelling is a scientific field with a short history and a long past. Its various disciplinary roots and conceptual …

Rhythmic activity in the brain fluctuates with behaviour and cognitive state, through a combination of coexisting and interacting …

Rhythmic, collective activity is a fundamental feature of neural systems. As a result of this, many of the challenges and opportunities …

Talks & Teaching

A selection of slides, videos, and code from recent talks and tutorial workshops on a variety of topics.

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JG’s New Books in Neuroscience podcast interview with GB in his new book

JG’s New Books in Neuroscience podcast interview with NC in his new book

JG’s New Books in Neuroscience podcast interview with RDF in his new book

JG’s New Books in Neuroscience podcast interview with RQQ in his new book

JG’s New Books in Neuroscience podcast interview with CH in his new book

Using human connectome project (HCP) data

Tutorial session given at Rotman Research Institute, Baycrest (jointly given with Dr. Erin Dickie)

The spherical harmonic structure of the human connectome

Invited talk at the ‘Large scale trends in cortical organization’ workshop, Leipzig

Modelling brain dynamics at rest: practical tools and theoretical perspectives

Guest (inaugral) lecture given for the Krembil Computational Neuroscience (KCN) Events series

First of the two lectures given at the Banff International Research Station (BIRS) workshop on Topological Methods in Brain Network Analysis

Second of the two lectures given at the Banff International Research Station (BIRS) workshop on Topological Methods in Brain Network Analysis

Analysis of fMRI data: principles & techniques

Lecture given by JG at the Canadian Association for Neuroscience Meeting Satellite workshop: Neural signal and image processing: quantitative analysis of neural activity

Introduction to diffusion-weighted MRI

Workshop given by JG at Rotman Research Institute

JG & CH discuss the seminal paper by Oh et al.

John Griffiths & Christopher Harris discuss an interesting but troubled corner of modern philosophy of mind

Contact

  • john.griffiths@camh.ca
  • Krembil Centre for Neuroinformatics (KCNI); Centre for Addiction and Mental Health (CAMH): 250 College Street (Floor 12), Toronto ON