Functional MRI Modelling
FMRI is capable of measuring changes in local blood oxygenation, and this enables it to detect changes in neuronal activity. To begin with fMRI experiments analysed changes related to task-induced activity within subjects, but more recently the intrinsic spontaneous fluctuations seen in resting-state fMRI have become of great interest for investigating connectivity. Our research in FMRI Modelling and Analysis covers both task-based and resting-state fMRI.
Much of our current work in this area is focussed on resting-state network modelling, looking at new ways to identify complex (e.g., overlapping and dynamic) functionally-meaningful networks. This includes voxel-wise methods (MELODIC, dual-regression), network models (NETMATS) and investigations into non-stationary network modelling (Temporal Functional Modes). Much of this work is shared with work in the Connectivity Modelling area.
We work closely with our collaborators at the OHBA Analysis Group and with the Statistical Imaging Neuroscience group at the Donders, Nijmegen.
Our team
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Stephen Smith
Professor of Biomedical Engineering
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Timothy Behrens
Professor of Computational Neuroscience
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Saad Jbabdi
Professor of Biomedical Engineering
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Sean Fitzgibbon
Postdoctoral Researcher
Collaborators
OHBA
- Sam Harrison
- Giles Colclough
- Diego Vidaurre
Donders
- Christian Beckmann
- Koen Haak
Warwick
- Tom Nichols
FSL Tools
- GLM-based Analysis (FEAT)
- ICA-based Analysis (MELODIC)
- Constrained Basis-functions (FLOBS)
ASL Tools (within FSL)
- FABBER
- BASIL
- VERBENA