Postdoctoral Research Assistant
My current research focuses on MRI data collection, organisation and analysis of two clinical cohorts currently being recruited in the Oxford Parkinson’s Disease Centre (OPDC) and the Stroke Prevention Research Unit (SPRU, OxVasc study).
I am particularly interested in structural and functional MRI.
Regarding structural MRI, I am currently involved in the development of methodological approaches for automated lesions segmentation and the assessment of the relationship between white matter hyperintensities, cardiovascular risk factors and cognition.
Regarding functional MRI I work on resting state functional connectivity and the development of methodological approaches for artefact removal and the evaluation of rfMRI as potential clinical biomarker through reproducibility assessments of MRI-derived measures.
I am involved in post-graduate teaching and supervision, and the development and support of the FSL image analysis software package.
Basal ganglia dysfunction in idiopathic REM sleep behaviour disorder parallels that in early Parkinson's disease.
Rolinski M. et al, (2016), Brain, 139, 2224 - 2234
Challenges in the reproducibility of clinical studies with resting state fMRI: An example in early Parkinson's disease.
Griffanti L. et al, (2016), Neuroimage, 124, 704 - 713
Validation of automated segmentation of white matter hyperintensities on MRI: Correlation with cognitive function after TIA and stroke
Griffanti L. et al, (2015), INTERNATIONAL JOURNAL OF STROKE, 10, 62 - 62
Association between macroscopic and microstructural white matter damage and cognition in vascular cognitive impairment
Zamboni G. et al, (2015), INTERNATIONAL JOURNAL OF STROKE, 10, 381 - 381
Effective artifact removal in resting state fMRI data improves detection of DMN functional connectivity alteration in Alzheimer's disease.
Griffanti L. et al, (2015), Front Hum Neurosci, 9
Long-term cerebral white and gray matter changes after preeclampsia.
Siepmann T. et al, (2017), Neurology, 88, 1256 - 1264
Classification and characterization of periventricular and deep white matter hyperintensities on MRI: A study in older adults.
Griffanti L. et al, (2017), Neuroimage
Hand classification of fMRI ICA noise components.
Griffanti L. et al, (2016), Neuroimage
Multimodal population brain imaging in the UK Biobank prospective epidemiological study.
Miller KL. et al, (2016), Nat Neurosci, 19, 1523 - 1536
BIANCA (Brain Intensity AbNormality Classification Algorithm): A new tool for automated segmentation of white matter hyperintensities.
Griffanti L. et al, (2016), Neuroimage, 141, 191 - 205