Bayesian Network Analysis Reveals Alterations to Default Mode Network Connectivity in Individuals at Risk for Alzheimer's Disease

	Bayesian Network Analysis Reveals Alterations to Default Mode Network Connectivity in Individuals at Risk for Alzheimer's Disease
	Li, Rui1,2 ; Yu, Jing1,3 ; Zhang, Shouzi 4; Bao, Feng 5; Wang, Pengyun1,2 ; Huang, Xin 1,2; Li, Juan1,2 ; Li, J (reprint author), Chinese Acad Sci, Inst Psychol, Key Lab Mental Hlth, Ctr Aging Psychol, Beijing 100101, Peoples R China.
心理所单位排序	1
摘要	Alzheimer's disease (AD) is associated with abnormal functioning of the default mode network (DMN). Functional connectivity (FC) changes to the DMN have been found in patients with amnestic mild cognitive impairment (aMCI), which is the prodromal stage of AD. However, whether or not aMCI also alters the effective connectivity (EC) of the DMN remains unknown. We employed a combined group independent component analysis (ICA) and Bayesian network (BN) learning approach to resting-state functional MRI (fMRI) data from 17 aMCI patients and 17 controls, in order to establish the EC pattern of DMN, and to evaluate changes occurring in aMCI. BN analysis demonstrated heterogeneous regional convergence degree across DMN regions, which were organized into two closely interacting subsystems. Compared to controls, the aMCI group showed altered directed connectivity weights between DMN regions in the fronto-parietal, temporo-frontal, and temporo-parietal pathways. The aMCI group also exhibited altered regional convergence degree in the right inferior parietal lobule. Moreover, we found EC changes in DMN regions in aMCI were correlated with regional FC levels, and the connectivity metrics were associated with patients' cognitive performance. This study provides novel sights into our understanding of the functional architecture of the DMN and adds to a growing body of work demonstrating the importance of the DMN as a mechanism of aMCI.
学科领域	Medical Psychology
	2013
语种	英语
发表期刊	PLOS ONE
ISSN	1932-6203
卷号	8 期号:12
期刊论文类型	期刊论文
收录类别	SCI
项目简介	This work was supported by the National Natural Science Foundation of China (31271108, 31200847, 30911120494 and 31070916), the Knowledge Innovation Project of the Chinese Academy of Sciences (KSCX2-EW-J-8), the CAS/SAFEA International Partnership Program for Creative Research Team (Y2CX131003), and Scientific Foundation of Institute of Psychology, Chinese Academy of Sciences (Y1CX251005). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
WOS关键词	MILD COGNITIVE IMPAIRMENT ; RESTING-STATE NETWORKS ; INTRINSIC FUNCTIONAL CONNECTIVITY ; INDEPENDENT COMPONENT ANALYSIS ; HUMAN BRAIN ; AUTOBIOGRAPHICAL MEMORY ; CINGULATE CORTEX ; MRI ; FMRI ; SELF
WOS标题词	Science & Technology
WOS研究方向	Science & Technology - Other Topics
WOS类目	Multidisciplinary Sciences
WOS记录号	WOS:000328566700060
资助机构	National Natural Science Foundation of China [31271108, 31200847, 30911120494, 31070916] ; Knowledge Innovation Project of the Chinese Academy of Sciences [KSCX2-EW-J-8] ; CAS/SAFEA International Partnership Program for Creative Research Team [Y2CX131003] ; Scientific Foundation of Institute of Psychology, Chinese Academy of Sciences [Y1CX251005]
引用统计	被引频次：26[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.psych.ac.cn/handle/311026/10820
专题	中国科学院心理健康重点实验室
通讯作者	Li, J (reprint author), Chinese Acad Sci, Inst Psychol, Key Lab Mental Hlth, Ctr Aging Psychol, Beijing 100101, Peoples R China.
作者单位	1.Chinese Acad Sci, Inst Psychol, Key Lab Mental Hlth, Ctr Aging Psychol, Beijing 100101, Peoples R China 2.Chinese Acad Sci, Inst Psychol, Magnet Resonance Imaging Res Ctr, Beijing 100101, Peoples R China 3.Southwest Univ, Sch Psychol, Chongqing, Peoples R China 4.Beijing Geriatr Hosp, Beijing, Peoples R China 5.Capital Med Univ, Beijing Anding Hosp, Beijing, Peoples R China
第一作者单位	中国科学院心理健康重点实验室; 管理支撑系统
推荐引用方式 GB/T 7714	Li, Rui,Yu, Jing,Zhang, Shouzi,et al. Bayesian Network Analysis Reveals Alterations to Default Mode Network Connectivity in Individuals at Risk for Alzheimer's Disease[J]. PLOS ONE,2013,8(12).
APA	Li, Rui.,Yu, Jing.,Zhang, Shouzi.,Bao, Feng.,Wang, Pengyun.,...&Li, J .(2013).Bayesian Network Analysis Reveals Alterations to Default Mode Network Connectivity in Individuals at Risk for Alzheimer's Disease.PLOS ONE,8(12).
MLA	Li, Rui,et al."Bayesian Network Analysis Reveals Alterations to Default Mode Network Connectivity in Individuals at Risk for Alzheimer's Disease".PLOS ONE 8.12(2013).

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