Abstract #4965

White matter-engaged multilayer network for evaluation of functional deficits in Alzheimer’s disease

Lyuan Xu^1,2, Zhongliang Zu^1,3, Yurui Gao^1,4, Muwei Li^1,3, Kurt G. Schilling^1,3, Soyoung Choi^1,3, Adam W. Anderson^1,3,4, John C. Gore^1,3,4, and Zhaohua Ding^1,2

¹Vanderbilt University Institute of Imaging Science, Nashville, TN, United States, ²Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, United States, ³Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States, ⁴Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States

Synopsis

Keywords: Functional Connectivity, Alzheimer's Disease

Motivation: The role of white matter (WM) in the functional connectivity within brain networks has not been well studied.

Goal(s): Our goal was to use a high-order graph model to comprehensively analyze brain functional networks that engage WM.

Approach: We constructed multilayer networks and analyzed network parameters in the brains of subjects with Alzheimer’s disease (AD).

Results: Multilayer network analysis showed increased sensitivity for detecting significant deterioration in functional connectivity (FC) in AD.

Impact: Multilayer networks allow more comprehensive understanding of structure-function relations within the whole brain and may provide deeper insight into the pathophysiology of degenerative brain disease.

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