Resting-state Neural Networks and Granger Causal Connectivity for Patients with Cognitive Impairment Associated with Leukoaraiosis
10.3969/j.issn.1006-9771.2019.03.005
- VernacularTitle:脑白质疏松相关认知障碍患者的静息态脑网络及格兰杰因果连接
- Author:
Qing-li SHI
1
,
2
;
Yu-mei ZHANG
1
,
2
;
Hong-yan CHEN
1
,
2
;
Li-jun BAI
3
Author Information
1. Department of Neurology
2. b. Department of Neuroimaging, Beijing Tiantan Hospital, Capital Medical University, Beijing 100050, China
3. Institute of Automation, Chinese Academy of Sciences, Beijing 100069, China
- Publication Type:Research Article
- Keywords:
leukoaraiosis;
resting-state functional magnetic resonance imaging;
Granger causality analysis;
independent component analysis;
resting state networks
- From:
Chinese Journal of Rehabilitation Theory and Practice
2019;25(3):271-278
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To compare the difference in resting state networks among leukoaraiosis (LA) patients with or without mild cognitive impairment, and healthy controls, as well as the functional connectivity under Granger causality analysis (GCA). Methods:Subjects aged 40 to 80 years, including 34 LA-MCI patients, 15 LA patients with normal cognition and 33 healthy controls, accepted resting-state functional magnetic resonance imaging. Independent component analysis was used to separate functional brain networks, and difference of activation was determined with two sample t-test. GCA was used to analyze effective connectivity of these functional networks. Results:Eight resting state networks were obtained, including default mode network, motor network, medial visual network, lateral visual network, right-memory network, left-memory network, auditory network and executive network. Activation was different among three groups. Effective connectivity of RSNs was also different among three groups. Conclusion:Components of the resting state networks keep changing as LA progressing. Activation decreases as patients' cognition impaired. The direction and strength of connections remodel.
