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Principal Investigator  
Principal Investigator's Name: Arianna Menardi
Institution: University of Padova
Department: Neuroscience
Proposed Analysis: The rs-fMRI data of available subjects will undergo preprocessing for the removal of noise components from the physiological signal. On these data, both volumetric and surface-based analyses will be conducted to extrapolate the individual connectivity gradients. For each individual and time point, we will compute a measure of whole brain and regional dispersion of the connectivity gradient. This measure of dispersion will then be mapped on the individual brain at every time point to be compared longitudinally with the data of the same subject, as well as across groups, to compare the amount of dispersion between healthy controls, MCI and AD patients. Simultaneously, we will process and analyze s-MRI and DTI data to derive measures of cortical thickness and of structural connectedness (fractional anisotropy and number of fiber bundles connecting each region of the brain), respectively. Both indices will be derived from the available data in ADNI. To test the effectiveness of gradient dispersion in predicting individual risk of progression to AD dementia, we will correlate the measure of functional dispersion with the delta changes (T2-T1) observed in atrophy, structural connectivity and cognitive scores.
Additional Investigators