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Our work focuses on translating imaging analysis methods to better understand processes such as brain maturation and ageing, and with a particular emphasis on neurodegenerative disorders (Alzheimer's, Parkinson's, Huntington's, ALS) and Big Data (UK Biobank, Lifespan HCP).

Alzheimer's, Huntington's, ALS: cutting-edge analysis methodology (e.g., multi-modal approach, probabilistic tractography, Bayesian causal modelling) contributes to a better understanding of the pathophysiological process and effect of treatment.
Alzheimer's, Huntington's, ALS: cutting-edge analysis methodology (e.g., multi-modal approach, probabilistic tractography, Bayesian causal modelling) contributes to a better understanding of the pathophysiological process and effect of treatment.

Our research stems from the strong conviction that multidisciplinary research benefits from researchers truly working at the interface between the different disciplines involved. This holds particularly true when imaging is used to further our understanding of normal and abnormal brain processes.

For instance, we developed in FSL, the brain imaging analysis software developed in the FMRIB Analysis group, a specific tool that makes it possible to assess cross-sectionally or longitudinally the localised grey matter volume differences or changes between populations. This was used to demonstrate anatomically-related grey and white matter abnormalities in early-onset schizophrenia, and the interplay of the disease with brain maturation (Brain 2007, Brain 2009), but has also been extensively used in >200 published studies. We developed a novel method to integrate structural and functional connectivity information related to a specific disease process and used it to reveal a possible failure of GABA interneurons in ALS, suggesting new therapeutic target for this devastating disease (Brain 2011). Another "bench to bedside" example is that, by using our FSL tool and the latest methods in Bayesian causal modelling, we have established the beneficial effect of vitamin B to drastically reduce grey matter atrophy in MCI subjects (PNAS 2013). By using multi-modal, data-driven approaches, we were also able to find not only a grey matter network - that BBC dubbed the "Achille's hill of the brain" - that is related to protracted development, early age-related degeneration, schizophrenia and Alzheimer's disease (PNAS 2014), but also a fine-grained structure-function correspondence pointing at evo-devo neurotrophic events (J Neurosci 2019).

This multidisciplinary, multi-modal approach is applied to our high-resolution 7T project, which focuses on the basal ganglia circuitry in health and movement disorders, structures that are wired together and process information in a highly computational manner. Failure in this very complex system can lead, for instance, to movement disorders such as Parkinson's or Huntington's. For more details, please see my personal webpage. We also leverage the same techniques to explore Big Data such as the UK Biobank (Nature 2018, Brain 2019).

Our team

Selected publications