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Investigation of the effective connectivity of resting state networks in Alzheimer's disease: a functional MRI study combining independent components analysis and multivariate Granger causality analysis

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机构: [1]Chinese Acad Sci, Inst Automat, Intelligent Med Res Ctr, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China; [2]Capital Med Univ, Dept Neurol, Beijing Tiantan Hosp, Beijing 100050, Peoples R China; [3]Shaanxi Normal Univ, Sch Psychol, Xian 710062, Peoples R China; [4]Xidian Univ, Life Sci Res Ctr, Sch Life Sci & Technol, Xian 710071, Shaanxi, Peoples R China; [5]Chinese Acad Sci, Inst Automat, Intelligent Med Res Ctr, State Key Lab Management & Control Complex Syst, POB 2728, Beijing 100190, Peoples R China
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关键词: Alzheimer's disease resting state functional MRI effective connectivity independent components analysis multivariate Granger causality analysis

摘要:
Recent neuroimaging studies have shown that the cognitive and memory decline in patients with Alzheimer's disease (AD) is coupled with abnormal functions of focal brain regions and disrupted functional connectivity between distinct brain regions, as well as losses in small-world attributes. However, the causal interactions among the spatially isolated, but functionally related, resting state networks (RSNs) are still largely unexplored. In this study, we first identified eight RSNs by independent components analysis from resting state functional MRI data of 18 patients with AD and 18 age-matched healthy subjects. We then performed a multivariate Granger causality analysis (mGCA) to evaluate the effective connectivity among the RSNs. We found that patients with AD exhibited decreased causal interactions among the RSNs in both intensity and quantity relative to normal controls. Results from mGCA indicated that the causal interactions involving the default mode network and auditory network were weaker in patients with AD, whereas stronger causal connectivity emerged in relation to the memory network and executive control network. Our findings suggest that the default mode network plays a less important role in patients with AD. Increased causal connectivity of the memory network and self-referential network may elucidate the dysfunctional and compensatory processes in the brain networks of patients with AD. These preliminary findings may provide a new pathway towards the determination of the neurophysiological mechanisms of AD. Copyright (c) 2012 John Wiley & Sons, Ltd.

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出版当年[2011]版:
大类 | 2 区 医学
小类 | 2 区 核医学 2 区 光谱学 3 区 生物物理
最新[2023]版:
大类 | 4 区 医学
小类 | 3 区 生物物理 3 区 光谱学 4 区 核医学
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出版当年[2010]版:
Q1 SPECTROSCOPY Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Q2 BIOPHYSICS
最新[2023]版:
Q1 SPECTROSCOPY Q2 BIOPHYSICS Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

影响因子: 最新[2023版] 最新五年平均 出版当年[2010版] 出版当年五年平均 出版前一年[2009版] 出版后一年[2011版]

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第一作者机构: [1]Chinese Acad Sci, Inst Automat, Intelligent Med Res Ctr, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China;
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通讯机构: [1]Chinese Acad Sci, Inst Automat, Intelligent Med Res Ctr, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China; [4]Xidian Univ, Life Sci Res Ctr, Sch Life Sci & Technol, Xian 710071, Shaanxi, Peoples R China; [5]Chinese Acad Sci, Inst Automat, Intelligent Med Res Ctr, State Key Lab Management & Control Complex Syst, POB 2728, Beijing 100190, Peoples R China
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