Abnormal characterization of dynamic functional connectivity in Alzheimer's disease

被引:33
作者
Zhao, Cui [1 ,2 ]
Huang, Wei-Jie [3 ,4 ,5 ]
Feng, Feng [6 ,7 ]
Zhou, Bo [1 ]
Yao, Hong-Xiang [8 ]
Guo, Yan-E [1 ]
Wang, Pan [9 ]
Wang, Lu-Ning [1 ]
Shu, Ni [3 ,4 ,5 ]
Zhang, Xi [1 ]
机构
[1] Chinese Peoples Liberat Army Gen Hosp, Med Ctr 2, Natl Clin Res Ctr Geriatr Dis, Dept Neurol, Beijing, Peoples R China
[2] Chengde Med Univ, Affiliated Hosp, Dept Geriatr, Chengde, Hebei, Peoples R China
[3] Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing, Peoples R China
[4] Beijing Normal Univ, Ctr Collaborat & Innovat Brain & Learning Sci, Beijing, Peoples R China
[5] Beijing Normal Univ, Beijing Key Lab Brain Imaging & Connect, Beijing, Peoples R China
[6] Chinese Peoples Liberat Army Gen Hosp, Med Ctr 1, Dept Neurol, Beijing, Peoples R China
[7] PLA Rocket Force Characterist Med Ctr, Dept Neurol, Beijing, Peoples R China
[8] Chinese Peoples Liberat Army Gen Hosp, Med Ctr 2, Dept Radiol, Beijing, Peoples R China
[9] Tianjin Huanhu Hosp, Dept Neurol, Tianjin, Peoples R China
基金
中国国家自然科学基金;
关键词
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; MILD COGNITIVE IMPAIRMENT; MENTAL-STATE-EXAMINATION; DEFAULT-MODE; BRAIN; NETWORK; DIAGNOSIS; SYSTEMS; FMRI; TAU; CLASSIFICATION;
D O I
10.4103/1673-5374.332161
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
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.
引用
收藏
页码:2014 / 2021
页数:8
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