Stamatios Sotiropoulos
Honorary Research Fellow, FMRIB Analysis
- Associate Professor, Sir Peter Mansfield Imaging Centre, University of Nottingham
Research Summary
I develop tools for the analysis of diffusion MRI data of the brain. I am interested in biophysical modelling of brain connections at different scales, both for resolving tissue microstructural patterns and long-range brain connectivity. I develop computational methods for inferring this information in-vivo and I am particularly interested in data fusion approaches for combining strengths and bridging the gaps across structural modalities (for instance, diffusion MRI at different k/q-space acquisitions, histology, microscopy). I am also heavily involved with the design and implementation of new technologies that aim to improve the spatial and angular resolution of diffusion MRI acquisitions.
More specifically, I am currently involved in the following projects:
- The recently funded EPSRC project on "Anatomy-Driven Brain Connectivity Mapping".
- The Human Connectome Project (funded by the US NIH)
- The developing Human Connectome Project (funded by ERC)
- The UK Biobank Imaging Study
Key publications
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Advances in diffusion MRI acquisition and processing in the Human Connectome Project
Journal article
Sotiropoulos SN. et al, (2013), NeuroImage, 80, 125 - 143
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Fusion in diffusion MRI for improved fibre orientation estimation: An application to the 3T and 7T data of the Human Connectome Project.
Journal article
Sotiropoulos SN. et al, (2016), Neuroimage, 134, 396 - 409
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Measuring macroscopic brain connections in vivo.
Journal article
Jbabdi S. et al, (2015), Nat Neurosci, 18, 1546 - 1555
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Ball and rackets: Inferring fiber fanning from diffusion-weighted MRI.
Journal article
Sotiropoulos SN. et al, (2012), Neuroimage, 60, 1412 - 1425
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Model-based analysis of multishell diffusion MR data for tractography: how to get over fitting problems.
Journal article
Jbabdi S. et al, (2012), Magn Reson Med, 68, 1846 - 1855
Recent publications
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Non-reversibility outperforms functional connectivity in characterisation of brain states in MEG data.
Journal article
Tewarie PKB. et al, (2023), Neuroimage, 276
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Mapping brain endophenotypes associated with idiopathic pulmonary fibrosis genetic risk.
Journal article
Mohammadi-Nejad A-R. et al, (2022), EBioMedicine, 86
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Concurrent mapping of brain ontogeny and phylogeny within a common space: Standardized tractography and applications.
Journal article
Warrington S. et al, (2022), Sci Adv, 8
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Predicting time-resolved electrophysiological brain networks from structural eigenmodes.
Journal article
Tewarie P. et al, (2022), Hum Brain Mapp
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The association between inadequate sleep and accelerated brain ageing.
Journal article
Ramduny J. et al, (2022), Neurobiol Aging, 114, 1 - 14