PSYCH OpenIR  > 中国科学院心理健康重点实验室
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, Shouzi4; Bao, Feng5; Wang, Pengyun1,2; Huang, Xin1,2; Li, Juan1,2; Li, J (reprint author), Chinese Acad Sci, Inst Psychol, Key Lab Mental Hlth, Ctr Aging Psychol, Beijing 100101, Peoples R China.
2013
Source PublicationPLOS ONE
ISSN1932-6203
Subtype期刊论文
Volume8Issue:12
Contribution Rank1
AbstractAlzheimer'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.
Subject AreaMedical Psychology
Indexed BySCI
Language英语
Funding OrganizationNational 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]
Project Intro.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 Research AreaScience & Technology - Other Topics
WOS SubjectMultidisciplinary Sciences
WOS IDWOS:000328566700060
WOS HeadingsScience & Technology
WOS KeywordMILD COGNITIVE IMPAIRMENT ; RESTING-STATE NETWORKS ; INTRINSIC FUNCTIONAL CONNECTIVITY ; INDEPENDENT COMPONENT ANALYSIS ; HUMAN BRAIN ; AUTOBIOGRAPHICAL MEMORY ; CINGULATE CORTEX ; MRI ; FMRI ; SELF
Citation statistics
Cited Times:19[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.psych.ac.cn/handle/311026/10820
Collection中国科学院心理健康重点实验室
Corresponding AuthorLi, J (reprint author), Chinese Acad Sci, Inst Psychol, Key Lab Mental Hlth, Ctr Aging Psychol, Beijing 100101, Peoples R China.
Affiliation1.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
Recommended Citation
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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