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Hierarchical structural mapping for globally optimized estimation of functional networks.

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Department of Psychiatry, University of Illinois, Chicago, IL, USA.


In this study, we propose a framework to map functional MRI (fMRI) activation signals using DTI-tractography. This framework, which we term functional by structural hierarchical (FSH) mapping, models the regional origin of fMRI brain activation to construct "N-step reachable structural maps". Linear combinations of these N-step reachable maps are then used to predict the observed fMRI signals. Additionally, we constructed a utilization matrix, which numerically estimates whether the inclusion of a specific structural connection better predicts fMRI, using simulated annealing. We applied this framework to a visual fMRI task in a sample of body dysmorphic disorder (BDD) subjects and comparable healthy controls. Group differences were inferred by comparing the observed utilization differences against 10,000 permutations under the null hypothesis. Results revealed that BDD subjects under-utilized several key local connections in the visual system, which may help explain previously reported fMRI findings and further elucidate the underlying pathophysiology of BDD.

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