John David Griffiths, PhD
John David Griffiths, PhD
neuroimaging • computational neuroscience • neural dynamics • cognition • open science
neuroimaging • computational neuroscience • neural dynamics • cognition • open science
RESEARCH
A selection of current projects and general research directions
Computational and theoretical models of brain dynamics
A main overarching theme of most of the work I do is meso/macroscopic computational models of neural dynamics. I use mathematical models describing neural population activity on the scale of millimetres to centimetres, together with network structure from macaque histology or diffusion MRI fibre tracking, to simulate (approximately) whole-brain activity measurements of the kind measured by fMRI and M/EEG. These techniques are gradually allowing us to obtain more mechanistic insights into observed patterns in neuroimaging data relating to the resting state, oscillations, and the impact of neurological and neurodegenerative disease.
Much of my work in this area is based around usage and development of the modelling and neuroinformatics software platform the The Virtual Brain (TVB), the brainchild of my boss Randy McIntosh and colleague Vik Jirsa. As a member of the TVB team I provide technical support on the Forum, and also teach at our regular official (and unofficial) TVB workshops.
In a second complementary line of work, I have been working together with Prof. Peter Robinson at the University of Sydney, on macroscopic neural field models for large-scale brain dynamics. These are generally formulated in terms of second-order partial differential (wave) equations that are substantially simpler to work with analytically than the stochastic delay-differential equation numerically integrated in TVB simulations. In particular, we have studied the role of the spherical topology and physical embedding of the cerebral cortex on anatomical structure and dynamics. This, together with the steady-state eigenmode solutions to the Robinson neural field equations, predicts the presence of spherical harmonic-like patterns in fast-timescale activity measurements. Consistent with this, we have recently shown that this spherical harmonic-like spatial eigenmode structure is observed in cortical surface Laplacians, anatomical connectivity (tractography) networks, (MEG) functional connectivity networks, and numerical simulations (Griffiths et al. 2017; Griffiths et al. submitted; Robinson et al. 2016). These results provide new insight into the role of the network topology and geometric embedding of the cerebral hemispheres in shaping brain dynamics, as well as the theoretical and practical utility of macroscopic neural field models with spherical boundary conditions.
Modelling Brain Stimulation
Models of brain stimulation, and particularly how periodic brain stimulation interacts with ongoing neural oscillations, is a major focus of my current work with Dr. Lefebvre. We find that a thalamocortical loop motif consisting of excitatory and inhibitory cortical neuronal populations, and excitatory (relay) and inhibitory (reticular) thalamic nuclei, can reproduce a large amount of the empirical pheonomena measured with resting state M/EEG (Griffiths & Lefebvre, in press). We are now investigating how the topological structure of the cortex interacts with the rhythmogenic properties of this base circuit motif.
Driving this system with periodic electric stimulation produces Arnold Tongues and resonance effects that depend on both the noise and the time delay structure of the underlying neural system, as well as its current state - which (like the EEG) shows endogeneous fluctuations between regimes of synchronous alpha activity and periods of relatively more asynchronous high-frequency activity.
Modelling brain damage
The effects of white matter damage on cognitive and neural function has been a subject of major interest for me for many years. In my PhD work and earlier I studied how different spatial profiles of damage following stroke resulted in differential types of linguistic impairments.
A large part of my current work asks similar questions from a more systems level perspective: what is the impact of a given spatial profile of damage on the topological structure and dynamic behaviour in connectome-based neural mass models? In order to help address questions like this, I have built a software library, ConWhAt, for connectome-based white matter atlas analysis. This allows the construction of 'damaged' brain networks for a given spatial profile of damage, obviating the need to run complicated tractography analyses in individual patients.
CODE
I endeavour to make the code I produce as freely available and easily accessible to others as possible. The principal vehicle for this is github, where the following repositories can be found:
My online, digital lab notebook. Inspired by the pioneering efforts of Carl Boettiger. Entries are generally a mix of text, code, and rich media. I use this for both general notes, and for research project documentation and collaboration; and so the site contains both open-access and password-protected entries. Use the tags on the right hand side to list open access entries; all are welcome to peruse these and use any code goodies they find useful. If you are interested in seeing the content of any password-protected entries, get in touch.
My work involves using and developing the TVB platform. As well as the main trunk, I have extensions for scripting, neuroimaging workflow management (tvb-nipype), and simulation workflow management (tvb-sumatra).
TALKS & TEACHING
Here are some slides, videos, and links to invited talks, guest lectures, and workshops I've recently given:
Introduction to Neuroimaging for Algebraic Topologists
First of the two lectures I gave at the Banff International Research Station (BIRS) Workshop on Topological Methods in Brain Network Analysis
March 2017
Working with Neuroimaging data
(for Algebraic Topologists)
Second of the two lectures I gave at the Banff International Research Station (BIRS) workshop on Topological Methods in Brain Network Analysis
March 2017
Using human connectome project (HCP) data
Tutorial session given at Rotman Research Institute, Baycrest
January 2018
(jointly given with Dr. Erin Dickie)
Reproducible Research Workflows and Hosting a Technical Blog
Hands-on tutorial talk at University of Toronto
February 2018
Analysis of functional magnetic resonance imaging data: principles and techniques
Lecture given at the Canadian Association for Neuroscience Meeting
Satellite workshop: “Neural signal and image processing: quantitative analysis of neural activity”
May 2017
Introduction to diffusion-weighted MRI
Workshop given at Rotman Research Institute
February 2018
Modelling Brain Dynamics at Rest: Practical Tools and Theoretical Perspectives
Guest (inaugral) lecture given for the Krembil Computational Neuroscience (KCN) Events series
April 2017
The spherical harmonic structure of the human connectome
Invited talk at the "Large scale trends in cortical organization" workshop, Leipzig
December 2017
The Virtual Brain Workshops
As a member of the TVB team I provide technical support on the Forum, and also teach regularly at the official TVB Node workshops, as well as similar non-Node events. The next #Node workshop will be at Neuroinformatics Montreal, 2018.
Podcast & blog on neuroscience type matters with esteemed friend and colleague Dr. Christopher Harris of NIH and Backyard Brains.
Discussion on Oh et al. and the Allen mouse brain atlas
Discussion on the philosophy and neuroscience of 'mind uploading'
CONTACT
Any Qs, please do get in touch :)
@neurodidact
j (dot) davidgriffiths (at) gmail.com
