Delong Zhang1, Bo Liu2, 3, Jun Chen2, 3, Xiaoling Peng1, Xian Liu2, 3, Ruiwang Huang1
1Center for Studies of Psychological Application, Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China; 2Department of Radiology, Guangdong Province Hospital of Traditional Chinese Medicine, Guangzhou, China; 3Department of Radiology, Guangzhou University of Traditional Chinese Medicine, Guangzhou, China
Here we used support vector machines (SVM) method to predict the Vascular Dementia (VaD), one of the most common types of dementia, from the functional brain scans according to the whole-brain functional networks, and compared the detection efficiency at different frequency bandwidths, slow-5 (0.01~0.27 Hz), slow-4 (0.027~0.073 Hz), and whole band (0.01~0.073 Hz). The result suggested that whole-brain functional connectivity contain adequate information about neurobiological changes in VaD patients, and the detection efficiency related to the slow-5 was more prominent. These contribute to the understanding of VaD and may facilitate discovery of biomarkers for the diagnosis of individual VaD patient.
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