Temporal and instantaneous connectivity of default mode network estimated using Gaussian Bayesian network frameworks
文献类型：期刊论文
| 作者 | Li, Juan1 ; Li, Rui5; Chen, Kewei1,3,4; Yao, Li1,2; Wu, Xia1,2
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| 刊名 | NEUROSCIENCE LETTERS
 |
| 出版日期 | 2012-03-28 |
| 卷号 | 513期号:1页码:62-66 |
| 关键词 | Default mode network (DMN) Effective connectivity Instantaneous connectivity Temporal connectivity Bayesian networks (BN) Posterior cingulate cortex (PCC) |
| ISSN号 | 0304-3940 |
| 产权排序 | 4 |
| 通讯作者 | Wu, X (reprint author), Beijing Normal Univ, Coll Informat Sci & Technol, Xin Jie Kou Wai St 19, Beijing 100875, Peoples R China. |
| 英文摘要 | By probing its functional anatomy, the default mode network (DMN) can be considered consisting of two interacting hub and non-hub subsystems. The hub subsystem includes posterior cingulate cortex (PCC), medial prefrontal cortex (MPFC) and bilateral inferior parietal cortex (IPC). The non-hub subsystem contains inferior temporal cortex (ITC) and (para) hippocampus (HC). In this study, Gaussian Bayesian Network (BN) and Gaussian Dynamic Bayesian Network (DBN) were applied separately to detect the instantaneous and temporal connection relationship within each and between the two DMN subsystems. It was found that the directional instantaneous interactions between the two subsystems were primarily "from non-hub to hub". The temporal interactions between hub and non-hub regions, on the other hand, are less presented between the two subsystems. The hub subsystem demonstrated both strong instantaneous and temporal interactions among the hub regions, while the non-hub regions were only strongly inter-connected instantaneously but temporally isolated with each other. In addition, one of the hub regions, PCC, appears to be a confluent node and important in the functional integration within the network. (c) 2012 Elsevier Ireland Ltd. All rights reserved. |
| 学科主题 | Cognitive neuroscience |
| 收录类别 | SCI |
| 项目简介 | Thanks to the anonymous reviewers for their insightful views and constructive suggestions on the model interpretation. This work was supported by the Key Program (No.60931003), General Program (No.60905063) of National Natural Science Foundation of China and Scientific Foundation of Institute of Psychology, Chinese Academy of Sciences (No. Y1CX251005). |
| 语种 | 英语 |
| WOS记录号 | WOS:000302512800013 |
| 源URL | [http://ir.psych.ac.cn/handle/311026/13278]  |
| 专题 | 心理研究所_中国科学院心理健康重点实验室 |
| 作者单位 | 1.Beijing Normal Univ, Coll Informat Sci & Technol, Beijing 100875, Peoples R China 2.Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing 100875, Peoples R China 3.Banner Alzheimers Inst BAI, Phoenix, AZ 85006 USA 4.Banner Good Samaritan PET Ctr, Phoenix, AZ 85006 USA 5.Chinese Acad Sci, Inst Psychol, Key Lab Mental Hlth, Ctr Aging Psychol, Beijing 100875, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Juan,Li, Rui,Chen, Kewei,et al. Temporal and instantaneous connectivity of default mode network estimated using Gaussian Bayesian network frameworks[J]. NEUROSCIENCE LETTERS,2012,513(1):62-66. |
| APA | Li, Juan,Li, Rui,Chen, Kewei,Yao, Li,&Wu, Xia.(2012).Temporal and instantaneous connectivity of default mode network estimated using Gaussian Bayesian network frameworks.NEUROSCIENCE LETTERS,513(1),62-66. |
| MLA | Li, Juan,et al."Temporal and instantaneous connectivity of default mode network estimated using Gaussian Bayesian network frameworks".NEUROSCIENCE LETTERS 513.1(2012):62-66. |
入库方式： OAI收割
来源：心理研究所
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