CASIA OpenIR
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
Source PublicationHUMAN BRAIN MAPPING
ISSN1065-9471
2019-06-15
Volume40Issue:9Pages:2800-2812
Corresponding AuthorZuo, Nianming(nmzuo@nlpr.ia.ac.cn) ; Jian, Tianzi(jiangtz@nlpr.ia.ac.cn)
AbstractWorking 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.
Keywordassociation cognitive performance functional activation functional magnetic resonance imaging (fMRI) working memory
DOI10.1002/hbm.24561
WOS KeywordDYNAMIC FUNCTIONAL CONNECTIVITY ; FRONTOPARIETAL CONTROL NETWORK ; DEFAULT MODE NETWORK ; WORKING-MEMORY ; DORSAL ATTENTION ; BRAIN NETWORKS ; AGE-DIFFERENCES ; TASK ; ORGANIZATION ; FMRI
Indexed BySCI
Language英语
Funding ProjectBeijing 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]
Funding OrganizationBeijing Brain Initiative of Beijing Municipal Science & Technology Commission ; Special Projects of Brain Science of Beijing Municipal Science & Technology Commission ; Major Research Plan of the National Natural Science Foundation of China ; International Cooperation and Exchange of the National Natural Science Foundation of China
WOS Research AreaNeurosciences & Neurology ; Radiology, Nuclear Medicine & Medical Imaging
WOS SubjectNeurosciences ; Neuroimaging ; Radiology, Nuclear Medicine & Medical Imaging
WOS IDWOS:000467570300018
PublisherWILEY
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/24572
Collection中国科学院自动化研究所
Corresponding AuthorZuo, Nianming; Jian, Tianzi
Affiliation1.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
First Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Corresponding Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
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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