I'm currently working on a new website for my new lab, The Whole Brain Modelling Group (www.grifflab.com), at the Krembil Centre for Neuroinformatics @ CAMH, Toronto. I will then gradually phase out this site. In the meantime however, this is still the best place to learn about my work, so please do read on!
Hi! Welcome to my personal website.
I'm a neuroscientist based at the Rotman and Krembil Research Institutes in Toronto, Canada. My research uses a combination of computational modelling and neuroimaging techniques to study basic principles of brain organization, and the neural and cognitive effects of damage and disease.
Follow the links above to learn more about my current projects, publications, talks and teaching, code and software, and science communication.
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.
Griffiths J D & McIntosh A R (in preparation). Connectome-based white matter atlases for virtual lesion studies.
Griffiths J D & Lefebvre J (in preparation). Estimating conduction delays from tractography and microstructure data – an uncertainty propagation analysis.
Griffiths J D, Lefebvre J, Aquino K M, McIntosh A R, & Robinson P A (in preparation). The spherical harmonic structure of the human connectome.
Griffiths J D & McIntosh A R (in preparation). Multiscale entropy, brain structure, and the factor structure of human cognitive abilities.
Griffiths J D & Lefebvre J (2018). Shaping brain rhythms: dynamic and control-theoretic perspectives on periodic brain stimulation for treatment of neurological disorders. (Chapter to appear in Vassilis et al. Eds. : "Handbook of Multi-Scale Models of Brain Disorders: From Microscopic to Macroscopic Assessment of Brain Dynamics”. Springer. London.)
Park D, Griffiths J D, & Lefebvre J (2018). Persistent entrainment in non-linear neural networks with memory. (submitted to Journal of Applied Mathematics)
Hutt A, Griffiths J D, Herrmann C, & Lefebvre J (2018). Effect of Stimulation Waveform on the Nonlinear Entrainment of Cortical Alpha Oscillations. (Submitted to Frontiers in Computational Neuroscience)
Ryan J, Shen K, Kacollja A, Tian H, Griffiths J D, & McIntosh A R (2018). The functional reach of the hippocampal memory system to the oculomotor system. (Submitted to Neuroimage)
Zimmerman J, Griffiths J D, & McIntosh A R (2018). Subject-specificity of the correlation between large-scale structural and functional connectivity. Network Neuroscience 3.
Zimmerman J, Griffiths J D, & McIntosh (2018). Unique mapping of structural and functional connectivity on cognition. bioRxiv 296913; doi: https://doi.org/10.1101/296913 (submitted to Journal of Neuroscience)
Robinson P A, Zhao X, Aquino K M, Griffiths J D, Sarkar S, & Panderjee, GM (2016). Eigenmodes of brain activity: neural field theory and comparison with experiment. Neuroimage 142: 79-98
Kievit R, Davis S W, Griffiths J D, Correia M M, Cam-CAN, & Henson R N (2016). A watershed model of individual differences in fluid intelligence. Neuropsychologia 91: 186-198
Griffiths J D (2015). Causal influence in neural systems: Reconciling mechanistic-reductionist and statistical perspectives. Physics of Life Reviews, 15:130–132.
Griffiths, J D (2014). The white matter disconnection hypothesis of neurocognitive ageing: bridging the gaps. (PhD Thesis, University of Cambridge).
Griffiths J D, Marslen-Wilson W D, Stamatakis E A, & Tyler L K (2013). Functional organization of the neural language system: dorsal and ventral pathways are critical for syntax. Cerebral Cortex. 23(1):139-47
Papoutsi M, Stamatakis E A, Griffiths J D, Marslen-Wilson W D, & Tyler L K (2011) Is left fronto-temporal connectivity essential for syntax? Effective connectivity, tractography and performance in left-hemisphere damaged patients. Neuroimage. 58(2):656-64
Recent Conference Posters:
Griffiths J D & Lefebvre J (2018). Influence of cortical network topology and delay structure on EEG rhythms in a whole-brain connectome-based thalamocortical neural mass model (Poster to be presented at OCNS Seattle 2018).
Ghahremani A, McIntosh A R, & Griffiths J D (2018). Role of the thalamus in connectome network topology: A virtual brain modelling study (Poster to be presented at Neuroinformatics 2018).
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:
Using human connectome project (HCP) data
Tutorial session given at Rotman Research Institute, Baycrest
(jointly given with Dr. Erin Dickie)
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”
2017 - Present ... Postdoctoral Fellow, Krembil Research Institute, Toronto, Canada
2015 - Present ... Postdoctoral Fellow, Rotman Research Institute, Toronto, Canada
2015 - Present ... Honorary Associate, School of Physics, University of Sydney, Australia
2014 - 2015 ....... Visiting Research Fellow (Endeavour Scholar), School of Physics, University of Sydney, Australia
2015 ......................... PhD Cognitive Neuroimaging, University of Cambridge, UK
2008 - 2010 ....... Research Assistant, University of Cambridge, UK
2007 ......................... MSc Cognitive Neuroscience, University of York, UK
2006 ......................... BSc Psychology & Philosophy (Joint Honours), University of Warwick, UK
Any Qs, please do get in touch :)
j (dot) davidgriffiths (at) gmail.com