| Weak Higher-Order Interactions in Macroscopic Functional Networks of the Resting Brain | |
Huang, Xuhui1,2,3,4 ; Xu, Kaibin1,2,4,5; Chu, Congying1,2,4,5; Jiang, Tianzi1,2,4,6; Yu, Shan1,2,4,5
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| 发表期刊 | JOURNAL OF NEUROSCIENCE
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| 2017-10-25 | |
| 卷号 | 37期号:43页码:10481-10497 |
| 文章类型 | Article |
| 摘要 | Interactions among different brain regions are usually examined through functional connectivity (FC) analysis, which is exclusively based on measuring pairwise correlations in activities. However, interactions beyond the pairwise level, that is, higher-order interactions (HOIs), are vital in understanding the behavior of many complex systems. So far, whether HOIs exist among brain regions and how they can affect the brain's activities remains largely elusive. To address these issues, here, we analyzed blood oxygenation level-dependent (BOLD) signals recorded from six typical macroscopic functional networks of the brain in 100 human subjects (46 males and 54 females) during the resting state. Through examining the binarized BOLD signals, we found that HOIs within and across individual networks were both very weak regardless of the network size, topology, degree of spatial proximity, spatial scales, and whether the global signal was regressed. To investigate the potential mechanisms underlying the weak HOIs, we analyzed the dynamics of a network model and also found that HOIs were generally weak within a wide range of key parameters provided that the overall dynamic feature of the model was similar to the empirical data and it was operating close to a linear fluctuation regime. Our results suggest that weak HOI may be a general property of brain's macroscopic functional networks, which implies the dominance of pairwise interactions in shaping brain activities at such a scale and warrants the validity of widely used pairwise-based FC approaches. |
| 关键词 | Default Mode Network Frontoparietal Network Functional Connectivity Pairwise Correlation Resting-state Fmri |
| WOS标题词 | Science & Technology ; Life Sciences & Biomedicine |
| DOI | 10.1523/JNEUROSCI.0451-17.2017 |
| 关键词[WOS] | INFORMATION-GEOMETRIC MEASURE ; ALZHEIMERS-DISEASE ; CORTICAL NETWORKS ; DEFAULT-MODE ; NEURONAL AVALANCHES ; NEURAL POPULATION ; CONNECTIVITY MRI ; MOTION ARTIFACT ; GLOBAL SIGNAL ; AWAKE MONKEYS |
| 收录类别 | SCI |
| 语种 | 英语 |
| 项目资助者 | National Key Research and Development Program of China(2017YFA0105203) ; Natural Science Foundation of China(81471368 ; Chinese Academy of Sciences (CAS)(XDB02060003 ; China Postdoctoral Science Foundation(2015T80154) ; CAS ; CAS(QYZDJ-SSW-SMC019) ; Beijing Municipal Science and Technology Commission(Z161100000216139) ; 11505283 ; XDB02030300) ; 91132301 ; 91432302) |
| WOS研究方向 | Neurosciences & Neurology |
| WOS类目 | Neurosciences |
| WOS记录号 | WOS:000413745200018 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.ia.ac.cn/handle/173211/15483 |
| 专题 | 类脑智能研究中心 |
| 通讯作者 | Yu, Shan |
| 作者单位 | 1.Chinese Acad Sci, Brainnetome Ctr, Inst Automat, 95 Zhongguancun East Rd, Beijing 100190, Peoples R China 2.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China 3.Chinese Acad Sci, Inst Automat, Res Ctr Brain Inspired Intelligence, Beijing 100190, Peoples R China 4.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Beijing 100190, Peoples R China 5.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 6.Univ Elect Sci & Technol China, MOE Key Lab Neuroinformat, Chengdu Brain Sci Inst, Clin Hosp, Chengdu 625014, Sichuan, Peoples R China |
| 第一作者单位 | 模式识别国家重点实验室; 中国科学院自动化研究所 |
| 通讯作者单位 | 模式识别国家重点实验室 |
| 推荐引用方式 GB/T 7714 | Huang, Xuhui,Xu, Kaibin,Chu, Congying,et al. Weak Higher-Order Interactions in Macroscopic Functional Networks of the Resting Brain[J]. JOURNAL OF NEUROSCIENCE,2017,37(43):10481-10497. |
| APA | Huang, Xuhui,Xu, Kaibin,Chu, Congying,Jiang, Tianzi,&Yu, Shan.(2017).Weak Higher-Order Interactions in Macroscopic Functional Networks of the Resting Brain.JOURNAL OF NEUROSCIENCE,37(43),10481-10497. |
| MLA | Huang, Xuhui,et al."Weak Higher-Order Interactions in Macroscopic Functional Networks of the Resting Brain".JOURNAL OF NEUROSCIENCE 37.43(2017):10481-10497. |
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