Michele Guerreri – CMIC/WEISS joint seminar series

Speaker: Michele Guerreri

Pitch: Ariane Bollack

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

Abstract: 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 a recent revised version of NODDI model to examine cortical MD changes obtained in a spatial navigation task.

Speaker: Chris Parker

Title: Reducing estimation bias in regional NODDI metrics using tissue-weighted mean'

Abstract: White matter microstructure metrics derived from diffusion MRI can be averaged in a region of interest (ROI) to provide surrogate measures of their neural organisation and information processing capacity. These have been used to investigate the role of different brain regions in normal brain function and in neurodegenerative disease. The regional average is typically computed as a mean over ROI voxels. However, for some NODDI metrics, this approach produces biased estimates in the presence of cerebrospinal fluid partial volume. Our work addresses this by introducing a tissue-weighted alternative. We compare the proposed mean to its conventional counterpart for periventricular and non-periventricular ROIs in healthy subjects and patients with young onset Alzheimer’s disease (YOAD). Results show the conventional mean overestimates orientation dispersion index and inflates inter-subject variation, particularly for periventricular ROIs and the YOAD cohort. This technique may improve detection of true regional effects in future group studies of neurodegenerative diseases. 

Chair: Gary Zhang

Link to the Moodle page here: https://moodle.ucl.ac.uk/course/view.php?id=19613 

Please enrol with key: CMIC