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Abstract #2044

Quantifying tissue microstructural changes associated with short-term learning using model-based diffusion MRI

Michele Guerreri1, Thomas Villemonteix2,3, Whitney Stee3, Evelyne Balteau4, Philippe Peigneux3,4, and Hui Zhang1
1Computer Science & Centre for Medical Image Computing, University College London, London, United Kingdom, 2Laboratoire de Psychopathologie et Neuropsychologie, Saint Denis, Paris 8 Vincennes - St Denis University, Paris, France, 3Neuropsychology and Functional Neuroimaging Research Group (UR2NF) at the Centre for Research in Cognition and Neurosciences (CRCN), Université Libre de Bruxelles, Brussels, Belgium, 4Cyclotron Research Centre, University of Liège, Liège, Belgium

We use model-based diffusion MRI to assess microstructural changes associated with short-term plasticity. Neuroplasticity changes are the foundation of experience. These mechanisms include microstructural rearrangements which can manifest even after short learning episodes. DTI has proven effective in highlighting such changes. However, the connection with the underlying microstructural processes remains speculative. Biophysical modelling can help interpreting such changes. We use NODDI and CHARMED models to examine MD changes obtained in a spatial navigation task. NODDI’s FWF and CHARMED’s hMD share similar cortical patterns of decrease as MD. FWF exhibited higher sensitivity than MD and hMD to capture microstructural changes.

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