Postdoctoral Research Associate
- FMRIB Analysis group
I develop new approaches that enable functional brain imaging to be used to help answer important clinical questions, such as whether drugs show potential for use in particular medical conditions. Creative analysis approaches are required to ensure that the rich recordings of brain activity we can now acquire can be translated into useful data that clinicians can use with confidence.
Translating brain imaging experiments into clinical practise requires that reliable patterns can be discerned from the extensive and complex results of existing studies. I have developed approaches that automatically synthesise the results of past studies into tools for making predictions from new data. I have presented a proof-of-concept protocol that uses brain imaging to identify signs of promising analgesics, which could potentially be used to determine which compounds are sent to clinical trials. We are now working with drug companies to bring this approach to industry.
I split my time between developing and testing these translational applications and developing novel analytic approaches for characterising functional brain imaging experiments. I work closely with other members of the with other members of FMRIB's analysis methods group, and have designed experimental studies to provide important data for our work. I am involved in post-graduate teaching and supervision, and the development and support of the FSL image analysis software package.
Learning to identify CNS drug action and efficacy using multistudy fMRI data.
Duff EP. et al, (2015), Sci Transl Med, 7
White matter hyperintensities classified according to intensity and spatial location reveal specific associations with cognitive performance.
Melazzini L. et al, (2021), Neuroimage Clin, 30
Challenges and future directions for representations of functional brain organization.
Bijsterbosch J. et al, (2020), Nat Neurosci, 23, 1484 - 1495
The developing Human Connectome Project (dHCP) automated resting-state functional processing framework for newborn infants.
Fitzgibbon SP. et al, (2020), Neuroimage, 223
Modelling subject variability in the spatial and temporal characteristics of functional modes.
Harrison SJ. et al, (2020), Neuroimage, 222
Inferring pain experience in infants using quantitative whole-brain functional MRI signatures: a cross-sectional, observational study.
Duff EP. et al, (2020), Lancet Digit Health, 2, e458 - e467
FMRIB Analysis Group