Dr. John Griffiths is a scientist at the Krembil Centre for Neuroinformatics at the Centre for Addiction and Mental Health (CAMH), where he leads a team focused on whole-brain and multi-scale neurophysiological modelling. He is a cognitive and computational neuroscientist by trade, with particular research interests in mathematical modelling of large-scale neural dynamics, multimodal neuroimaging data analysis methods, and brain stimulation in the context of neuropsychiatric and neurological disease. Dr. Griffiths is also an assistant professor in the University of Toronto Department of Psychiatry.
He obtained his PhD in cognitive neuroscience from the University of Cambridge, and subsequently held postdoctoral positions at the University of Sydney School of Physics, and then in Toronto at the Rotman Research Institute (Baycrest Hospital) and Krembil Research Institute (UHN Toronto Western Hospital)
Area of Research
In the Whole Brain Modelling Group at the Krembil Centre for Neuroinformatics (KCNI), we take a “bird’s-eye” approach to understanding brain organization and how it is affected in neuropsychiatric and neurological disease. We work extensively with structural and functional neuroimaging data (sMRI, fMRI, DWI, MEG, EEG), employing the latest cutting-edge analysis methods to study connectivity, oscillations, and their modification by brain stimulation (esp. TMS) and drugs. This information is used to construct and constrain computational models of brain dynamics that combine meso-scale mathematical descriptions of neural population activity with whole-brain network structure. This framework strikes a balance between granularity (level of physiological detail) and coverage (number of brain regions included), that is well-matched to the type of information that can be obtained from modern in-vivo neuroimaging techniques. Together with colleagues in the KCNI microcircuit modelling and computational genomics groups, we are also developing multi-scale modelling approaches that bridge cellular-level and population-level descriptions of neural activity. Our long-term goal is the development simultaneously detailed and holistic in-silico computational and theoretical accounts of brain function, cognition, and their pathologies.