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Activation-based association profiles differentiate network roles across cognitive loads | |
Zuo, Nianming1,2,3,4; Salami, Alireza5,6,7,8; Yang, Yihong9; Yang, Zhengyi1,2; Sui, Jing1,2,10; Jian, Tianzi1,2,3,10,11,12 | |
发表期刊 | HUMAN BRAIN MAPPING |
ISSN | 1065-9471 |
2019-06-15 | |
卷号 | 40期号:9页码:2800-2812 |
摘要 | Working memory (WM) is a complex and pivotal cognitive system underlying the performance of many cognitive behaviors. Although individual differences in WM performance have previously been linked to the blood oxygenation level-dependent (BOLD) response across several large-scale brain networks, the unique and shared contributions of each large-scale brain network to efficient WM processes across different cognitive loads remain elusive. Using a WM paradigm and functional magnetic resonance imaging (fMRI) from the Human Connectome Project, we proposed a framework to assess the association and shared-association strength between imaging biomarkers and behavioral scales. Association strength is the capability of individual brain regions to modulate WM performance and shared-association strength measures how different regions share the capability of modulating performance. Under higher cognitive load (2-back), the frontoparietal executive control network (FPN), dorsal attention network (DAN), and salience network showed significant positive activation and positive associations, whereas the default mode network (DMN) showed the opposite pattern, namely, significant deactivation and negative associations. Comparing the different cognitive loads, the DMN and FPN showed predominant associations and globally shared-associations. When investigating the differences in association from lower to higher cognitive loads, the DAN demonstrated enhanced association strength and globally shared-associations, which were significantly greater than those of the other networks. This study characterized how brain regions individually and collaboratively support different cognitive loads. |
关键词 | association cognitive performance functional activation functional magnetic resonance imaging (fMRI) working memory |
DOI | 10.1002/hbm.24561 |
关键词[WOS] | DYNAMIC FUNCTIONAL CONNECTIVITY ; FRONTOPARIETAL CONTROL NETWORK ; DEFAULT MODE NETWORK ; WORKING-MEMORY ; DORSAL ATTENTION ; BRAIN NETWORKS ; AGE-DIFFERENCES ; TASK ; ORGANIZATION ; FMRI |
收录类别 | SCI |
语种 | 英语 |
资助项目 | Beijing Brain Initiative of Beijing Municipal Science & Technology Commission[Z181100001518003] ; Special Projects of Brain Science of Beijing Municipal Science & Technology Commission[Z161100000216139] ; Major Research Plan of the National Natural Science Foundation of China[91432302] ; International Cooperation and Exchange of the National Natural Science Foundation of China[31620103905] ; Beijing Brain Initiative of Beijing Municipal Science & Technology Commission[Z181100001518003] ; Special Projects of Brain Science of Beijing Municipal Science & Technology Commission[Z161100000216139] ; Major Research Plan of the National Natural Science Foundation of China[91432302] ; International Cooperation and Exchange of the National Natural Science Foundation of China[31620103905] |
WOS研究方向 | Neurosciences & Neurology ; Radiology, Nuclear Medicine & Medical Imaging |
WOS类目 | Neurosciences ; Neuroimaging ; Radiology, Nuclear Medicine & Medical Imaging |
WOS记录号 | WOS:000467570300018 |
出版者 | WILEY |
七大方向——子方向分类 | 脑网络分析 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/24572 |
专题 | 脑图谱与类脑智能实验室_脑网络组研究 |
通讯作者 | Zuo, Nianming; Jian, Tianzi |
作者单位 | 1.Chinese Acad Sci, Brainnetome Ctr, Inst Automat, Beijing 100190, Peoples R China 2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China 3.Univ Chinese Acad Sci, Beijing, Peoples R China 4.Chinese Inst Brain Res, Beijing, Peoples R China 5.Karolinska Inst, Aging Res Ctr, Stockholm, Sweden 6.Stockholm Univ, Stockholm, Sweden 7.Umea Univ, Umea Ctr Funct Brain Imaging, Umea, Sweden 8.Umea Univ, Wallenberg Ctr Mol Med, Dept Integrat Med Biol, Umea, Sweden 9.Natl Inst Drug Abuse, Neuroimaging Res Branch, NIH, Baltimore, MD USA 10.Chinese Acad Sci, CAS Ctr Excellence Brain Sci & Intelligence Techn, Inst Automat, Beijing, Peoples R China 11.Univ Elect Sci & Technol China, Sch Life Sci & Technol, Key Lab Neurolnformat, Minist Educ, Chengdu, Sichuan, Peoples R China 12.Univ Queensland, Queensland Brain Inst, Brisbane, Qld, Australia |
第一作者单位 | 模式识别国家重点实验室 |
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 | Zuo, Nianming,Salami, Alireza,Yang, Yihong,et al. Activation-based association profiles differentiate network roles across cognitive loads[J]. HUMAN BRAIN MAPPING,2019,40(9):2800-2812. |
APA | Zuo, Nianming,Salami, Alireza,Yang, Yihong,Yang, Zhengyi,Sui, Jing,&Jian, Tianzi.(2019).Activation-based association profiles differentiate network roles across cognitive loads.HUMAN BRAIN MAPPING,40(9),2800-2812. |
MLA | Zuo, Nianming,et al."Activation-based association profiles differentiate network roles across cognitive loads".HUMAN BRAIN MAPPING 40.9(2019):2800-2812. |
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