Normative Modelling

Serena Verdi
Last updated on Dec 11, 2020
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We are applying normative models to dementia patient data, to map the individualised neurobiological fingerprints.

Machine Learning Dementia Neuroimaging
Serena Verdi
Serena Verdi
Research Fellow

My research interests include translational neuroscience, normative modelling, ageing and dementia

Publications

Revealing Individual Neuroanatomical Heterogeneity in Alzheimer Disease Using Neuroanatomical Normative Modeling
Here we employ a novel neuroanatomical normative modelling approach to index individual patterns of brain structure in patients with Alzheimer’s disease or mild cognitive impairment. By comparing patients to a large independent dataset (n>33,000), our analysis provides evidence that i) patterns of cortical thickness differ markedly between individual patients with Alzheimer’s disease, ii) these individual cortical ‘outlier’ patterns are associated with cognitive performance and CSF measures, and iii) individualised cortical atrophy measures can predict conversion from the MCI stage to diagnosed Alzheimer’s disease.
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A neuroimaging measure to capture heterogeneous patterns of atrophy in Parkinson’s disease and dementia with Lewy bodies

Authors: R Bhome, S Verdi, SA Martin, N Hannaway, I Dobreva, NP Oxtoby, Castro Leal G, S Rutherford, AF Marquand, RS Weil, JH Cole

DOI: https://doi.org/10.1101/2023.08.01.23293480

Project DOI
Beyond the average patient: how neuroimaging models can address heterogeneity in dementia
Review of heterogeneity in dementia and how neuroimaging statistical techniques enable modelling of heterogeneity in the brain. We propose that the application of normative modelling methods to dementia neuroimaging studies as a promising avenue to mapping regional variations at the individual level
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