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
文献类型：期刊论文
| 作者 | Liu, Zhenyu1 ; Zhang, Yumei2; Bai, Lijun1; Yan, Hao3; Dai, Ruwei1; Zhong, Chongguang1; Wang, Hu1; Wei, Wenjuan1; Xue, Ting4; Feng, Yuanyuan1
|
| 刊名 | NMR IN BIOMEDICINE
 |
| 出版日期 | 2012-12-01 |
| 卷号 | 25期号:12页码:1311-1320 |
| 关键词 | Alzheimer's disease resting state functional MRI effective connectivity independent components analysis multivariate Granger causality analysis |
| 英文摘要 | 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. |
| WOS标题词 | Science & Technology ; Life Sciences & Biomedicine ; Technology |
| 类目[WOS] | Biophysics ; Radiology, Nuclear Medicine & Medical Imaging ; Spectroscopy |
| 研究领域[WOS] | Biophysics ; Radiology, Nuclear Medicine & Medical Imaging ; Spectroscopy |
| 关键词[WOS] | DEFAULT-MODE NETWORK ; HUMAN BRAIN ; FMRI ; CORTEX ; SYSTEMS ; SCHIZOPHRENIA ; ATTENTION ; DEMENTIA ; TASK ; ICA |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000310237600002 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/4100]  |
| 专题 | 自动化研究所_中国科学院分子影像重点实验室 |
| 通讯作者 | Tian Jie |
| 作者单位 | 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 |
| 推荐引用方式 GB/T 7714 | Liu, Zhenyu,Zhang, Yumei,Bai, Lijun,et al. 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[J]. NMR IN BIOMEDICINE,2012,25(12):1311-1320. |
| APA | Liu, Zhenyu.,Zhang, Yumei.,Bai, Lijun.,Yan, Hao.,Dai, Ruwei.,...&Tian Jie.(2012).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.NMR IN BIOMEDICINE,25(12),1311-1320. |
| MLA | Liu, Zhenyu,et al."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".NMR IN BIOMEDICINE 25.12(2012):1311-1320. |
入库方式： OAI收割
来源：自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。