Abstract
The neurobiology of Alzheimer’s disease (AD) has been extensively studied by applying network analysis techniques to activation patterns in fMRI images. However, the structure of the directed networks representing the activation patterns, and their differences in healthy and Alzheimer’s people remain poorly understood. In this paper, we aim to identify the differences in fMRI activation network structure for patients with AD, late mild cognitive impairment (LMCI) and early mild cognitive impairment (EMCI). We use a directed graph theoretical approach combined with entropic measurements to distinguish subjects falling into these three categories and the normal healthy control (HC) group. We explore three methods. The first is based on applying linear discriminant analysis to vectors representing the in and out degree statistics of different anatomical regions. The second uses an entropic measure of node assortativity to gauge the asymmetries in the node with in and out degree. The final approach selects the most salient anatomical brain regions and uses the degree statistics of the connecting directed edges.
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