Abnormal characterization of dynamic functional connectivity in Alzheimer's disease

• Published in: Neural regeneration research Vol. 17; no. 9; pp. 2014 - 2021
• Main Authors: Zhao, Cui, Huang, Wei-Jie, Feng, Feng, Zhou, Bo, Yao, Hong-Xiang, Guo, Yan-E, Wang, Pan, Wang, Lu-Ning, Shu, Ni, Zhang, Xi
• Format: Journal Article
• Language: English
• Published: India Wolters Kluwer India Pvt. Ltd 01.09.2022; Medknow Publications & Media Pvt. Ltd; Beijing Key Laboratory of Brain Imaging and Connectomics,Beijing Normal University,Beijing,China%Department of Neurology,First Medical Center,Chinese PLA General Hospital,Beijing,China; Department of Neurology,PLA Rocket Force Characteristic Medical Center,Beijing,China%Department of Neurology,Second Medical Center,National Clinical Research Center for Geriatric Disease,Chinese PLA General Hospital,Beijing,China%Department of Radiology,Second Medical Center,Chinese PLA General Hospital,Beijing,China%Department of Neurology,Tianjin Huanhu Hospital,Tianjin,China; Department of Neurology,Second Medical Center,National Clinical Research Center for Geriatric Disease,Chinese PLA General Hospital,Beijing,China; Department of Geriatrics,Affiliated Hospital of Chengde Medical University,Chengde,Hebei Province,China%State Key Laboratory of Cognitive Neuroscience and Learning,Beijing Normal University,Beijing,China; Center for Collaboration and Innovation in Brain and Learning Sciences,Beijing Normal University,Beijing,China; Wolters Kluwer - Medknow; Wolters Kluwer Medknow Publications
• Subjects: Alzheimer's disease; alzheimer’s disease; amnestic mild cognitive impairment; blood oxygen level-dependent; default mode network; dynamic functional connectivity; frontoparietal network; resting-state functional magnetic resonance imaging; support vector machine; resting-state functional magnetic resonance imaging; dynamic functional connectivity; support vector machine; Alzheimer’s disease; blood oxygen level-dependent; frontoparietal network; amnestic mild cognitive impairment; default mode network; Alzheimer's disease
• ISSN: 1673-5374; 1876-7958
• DOI: 10.4103/1673-5374.332161

Numerous studies have shown abnormal brain functional connectivity in individuals with Alzheimer's disease (AD) or amnestic mild cognitive impairment (aMCI). However, most studies examined traditional resting state functional connections, ignoring the instantaneous connection mode of the whole brain. In this case-control study, we used a new method called dynamic functional connectivity (DFC) to look for abnormalities in patients with AD and aMCI. We calculated dynamic functional connectivity strength from functional magnetic resonance imaging data for each participant, and then used a support vector machine to classify AD patients and normal controls. Finally, we highlighted brain regions and brain networks that made the largest contributions to the classification. We found differences in dynamic function connectivity strength in the left precuneus, default mode network, and dorsal attention network among normal controls, aMCI patients, and AD patients. These abnormalities are potential imaging markers for the early diagnosis of AD.