Core networks and their reconfiguration patterns across cognitive loads
Core networks and their reconfiguration patterns across cognitive loads
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核心网络及其跨认知负载的重新配置模式
DOI：
10.1002/hbm.24193
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发表时间：
2018-04
影响因子：
4.8
通讯作者：
Jiang Tianzi
中科院分区：
文献类型：
--
作者：
Zuo Nianming;Yang Zhengyi;Liu Yong;Li Jin;Jiang Tianzi
不同的认知要求任务会招募全球分布但功能特定的网络。然而，核心网络的配置及其跨认知负荷的重新配置模式仍然不清楚，这些模式是否是认知任务性能的指标。在这项研究中，我们分析了一个由448名受试者组成的大型队列的功能性磁共振成像数据，这些数据是在静息状态下用大脑获得的，并执行N-back工作记忆（WM）任务。我们区分核心网络的功能交互强度和连接的灵活性。结果表明，额顶网络（FPN）和默认模式网络（DMN）是核心网络，但在不同的认知负荷下表现出不同的模式。与静息状态（对照水平）相比，FPN和DMN在低需求状态（0-back）下均显示出增强的内部连接;然而，从低需求状态（0-back）到高需求状态（2-back），与FPN的一些连接减弱并重新连接到DMN（其连接都保持强劲）。值得注意的是，整个大脑和核心网络（但没有其他网络）在不同负荷水平下的更密集的重新配置表明认知性能相对较差。总的来说，这些研究结果表明，FPN和DMN有不同的角色和重新配置模式在认知要求的负载。这项研究推进了我们对核心网络及其跨认知负载的重新配置模式的理解，并提供了一个新的功能来评估和预测认知能力（例如，WM性能）的基础上的大脑网络。
Different cognitively demanding tasks recruit globally distributed but functionally specific networks. However, the configuration of core networks and their reconfiguration patterns across cognitive loads remain unclear, as does whether these patterns are indicators for the performance of cognitive tasks. In this study, we analyzed functional magnetic resonance imaging data of a large cohort of 448 subjects, acquired with the brain at resting state and executing N‐back working memory (WM) tasks. We discriminated core networks by functional interaction strength and connection flexibility. Results demonstrated that the frontoparietal network (FPN) and default mode network (DMN) were core networks, but each exhibited different patterns across cognitive loads. The FPN and DMN both showed strengthened internal connections at the low demand state (0‐back) compared with the resting state (control level); whereas, from the low (0‐back) to high demand state (2‐back), some connections to the FPN weakened and were rewired to the DMN (whose connections all remained strong). Of note, more intensive reconfiguration of both the whole brain and core networks (but no other networks) across load levels indicated relatively poor cognitive performance. Collectively these findings indicate that the FPN and DMN have distinct roles and reconfiguration patterns across cognitively demanding loads. This study advances our understanding of the core networks and their reconfiguration patterns across cognitive loads and provides a new feature to evaluate and predict cognitive capability (e.g., WM performance) based on brain networks.
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影响因子：
5.7
作者：
Van Essen, David C.;Smith, Stephen M.;Barch, Deanna M.;Behrens, Timothy E. J.;Yacoub, Essa;Ugurbil, Kamil
通讯作者：
Ugurbil, Kamil
DOI：
10.1177/1073858411403316
发表时间：
2012-06
期刊：
The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry
影响因子：
--
作者：
Andrews-Hanna JR
通讯作者：
Andrews-Hanna JR
DOI：
10.1109/iscas.2017.8050239
发表时间：
2017-05
期刊：
2017 IEEE International Symposium on Circuits and Systems (ISCAS)
影响因子：
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作者：
Chandrajit Pal;Dwaipayan Biswas;K. Maharatna;A. Chakrabarti
通讯作者：
Chandrajit Pal;Dwaipayan Biswas;K. Maharatna;A. Chakrabarti
影响因子：
10.2
作者：
Red, Veronica;Kelsic, Eric D.;Porter, Mason A.
通讯作者：
Porter, Mason A.
影响因子：
4.8
作者：
Owen, AM;McMillan, KM;Bullmore, ET
通讯作者：
Bullmore, ET