《Chinese Journal of Rehabilitation Theory and Practice》 ›› 2019, Vol. 25 ›› Issue (3): 271-278.doi: 10.3969/j.issn.1006-9771.2019.03.005

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Resting-state Neural Networks and Granger Causal Connectivity for Patients with Cognitive Impairment Associated with Leukoaraiosis

SHI Qing-li1,3,4,5,6, ZHANG Yu-mei1,3,4,5, CHEN Hong-yan2, BAI Li-jun7   

  1. 1.Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100050, China
    2. Department of Neuroimaging,Beijing Tiantan Hospital, Capital Medical University, Beijing 100050, China
    3. Department of Neuroimaging, Beijing Tiantan Hospital, Capital Medical University, Beijing 100050, China
    4.China National Clinical Research Center for Neurological Diseases NCRC-ND, Beijing 100050, China
    5.Beijing Key Laboratory of Translational Medicine for Cerebrovascular Disease, Beijing 100050, China
    6.Department of Neurology, Beijing Pinggu Hospital, Capital Medical University, Beijing 101200, China
    7.Institute of Automation, Chinese Academy of Sciences, Beijing 100069, China
  • Received:2018-07-11 Revised:2018-11-13 Published:2019-03-25 Online:2019-04-02
  • Contact: ZHANG Yu-mei, Email: zhangyumei95@aliyun.com
  • Supported by:
    National Natural Science Foundation of China (No. 813712011014883)

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.

Key words: leukoaraiosis, resting-state functional magnetic resonance imaging, Granger causality analysis, independent component analysis, resting state networks

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