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Resting-State Coupling between Core Regions within the Central-Executive and Salience Networks Contributes to Working Memory Performance
Fang, Xiaojing1; Zhang, Yuanchao1; Zhou, Yuan2,3; Cheng, Luqi1; Li, Jin4; Wang, Yulin5; Friston, Karl J.6; Jiang, Tianzi1,4,7,8,9
2016-02-25
Source PublicationFRONTIERS IN BEHAVIORAL NEUROSCIENCE
ISSN1662-5153
SubtypeArticle
Volume10Issue:0Pages:1-11
AbstractPrevious studies investigated the distinct roles played by different cognitive regions and suggested that the patterns of connectivity of these regions are associated with working memory pm). However, the specific causal mechanism through which the neuronal circuits that involve these brain regions contribute to WM is still unclear. Here, in a large sample of healthy young adults, we first identified the core WM regions by linking WM accuracy to resting-state functional connectivity with the bilateral dorsolateral prefrontal cortex (dLPFC: a principal region in the central -executive network, CEN). Then a spectral dynamic causal modeling (spDCM) analysis was performed to quantify the effective connectivity between these regions. Finally, the effective connectivity was correlated with WM accuracy to characterize the relationship between these connections and WM performance. We found that the functional connections between the bilateral dLPFC and the dorsal anterior cingulate cortex (dACC) and between the right dLPFC and the left orbital fronto-insular cortex (FIG) were correlated with WM accuracy. Furthermore, the effective connectivity from the dACC to the bilateral dLPFC and from the right dLPFC to the left FIG could predict individual differences in WM. Because the dACC and FIG are core regions of the salience network (SN), we inferred that the inter-and causal connectivity between core regions within the CEN and SN is functionally relevant for WM performance. In summary, the current study identified the dLPFC-related resting state effective connectivity underlying WM and suggests that individual differences in cognitive ability could be characterized by resting-state effective connectivity.
Keywordworking memory dorsolateral prefrontal cortex resting state fMRI functional connectivity effective connectivity spectral dynamic causal modeling
DOI10.3389/fnbeh.2016.00027
Indexed BySCI
Language英语
Funding OrganizationNational Key Basic Research and Development Program (973)(2011CB707800) ; Strategic Priority Research Program of the Chinese Academy of Sciences(XDB02030300) ; National Natural Science Foundation of China(91132301 ; 91432302 ; 81101000)
WOS Research AreaBehavioral Sciences ; Neurosciences & Neurology
WOS SubjectBehavioral Sciences ; Neurosciences
WOS IDWOS:000371090400001
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine
WOS KeywordINTRINSIC FUNCTIONAL CONNECTIVITY ; ANTERIOR CINGULATE CORTEX ; LATERAL FRONTAL-CORTEX ; VON ECONOMO NEURONS ; PREFRONTAL CORTEX ; INDIVIDUAL-DIFFERENCES ; COGNITIVE CONTROL ; BRAIN ACTIVATION ; FMRI ; SCHIZOPHRENIA
Citation statistics
Cited Times:13[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.psych.ac.cn/handle/311026/19589
Collection中国科学院行为科学重点实验室
Affiliation1.Univ Elect Sci & Technol China, Sch Life Sci & Technol, Key Lab Neuroinformat, Minist Educ, Chengdu 610054, Peoples R China
2.Chinese Acad Sci, Inst Psychol, Key Lab Behav Sci, Beijing 100101, Peoples R China
3.Chinese Acad Sci, Inst Psychol, Magnet Resonance Imaging Res Ctr, Beijing 100101, Peoples R China
4.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China
5.Southwest Univ, Sch Psychol, Minist Educ, Key Lab Cognit & Personal, Chongqing, Peoples R China
6.UCL, Inst Neurol, Wellcome Trust Ctr Neuroimaging, London, England
7.Chinese Acad Sci, Inst Automat, Brainnetome Ctr, Beijing, Peoples R China
8.Chinese Acad Sci, Inst Automat, CAS Ctr Excellence Brain Sci, Beijing, Peoples R China
9.Univ Queensland, Queensland Brain Inst, Brisbane, Qld, Australia
Recommended Citation
GB/T 7714
Fang, Xiaojing,Zhang, Yuanchao,Zhou, Yuan,et al. Resting-State Coupling between Core Regions within the Central-Executive and Salience Networks Contributes to Working Memory Performance[J]. FRONTIERS IN BEHAVIORAL NEUROSCIENCE,2016,10(0):1-11.
APA Fang, Xiaojing.,Zhang, Yuanchao.,Zhou, Yuan.,Cheng, Luqi.,Li, Jin.,...&Jiang, Tianzi.(2016).Resting-State Coupling between Core Regions within the Central-Executive and Salience Networks Contributes to Working Memory Performance.FRONTIERS IN BEHAVIORAL NEUROSCIENCE,10(0),1-11.
MLA Fang, Xiaojing,et al."Resting-State Coupling between Core Regions within the Central-Executive and Salience Networks Contributes to Working Memory Performance".FRONTIERS IN BEHAVIORAL NEUROSCIENCE 10.0(2016):1-11.
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