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默认模式网络与控制网络之间的相互作用随认知推理复杂性增加的变化情况。

Interactions between default mode and control networks as a function of increasing cognitive reasoning complexity.

作者信息

Hearne Luke, Cocchi Luca, Zalesky Andrew, Mattingley Jason B

机构信息

Queensland Brain Institute, The University of Queensland, Brisbane, Australia.

Melbourne Neuropsychiatry Centre and Melbourne School of Engineering, The University of Melbourne, Melbourne, Australia.

出版信息

Hum Brain Mapp. 2015 Jul;36(7):2719-31. doi: 10.1002/hbm.22802. Epub 2015 Apr 2.

Abstract

Successful performance of challenging cognitive tasks depends on a consistent functional segregation of activity within the default-mode network, on the one hand, and control networks encompassing frontoparietal and cingulo-opercular areas on the other. Recent work, however, has suggested that in some cognitive control contexts nodes within the default-mode and control networks may actually cooperate to achieve optimal task performance. Here, we used functional magnetic resonance imaging to examine whether the ability to relate variables while solving a cognitive reasoning problem involves transient increases in connectivity between default-mode and control regions. Participants performed a modified version of the classic Wason selection task, in which the number of variables to be related is systematically varied across trials. As expected, areas within the default-mode network showed a parametric deactivation with increases in relational complexity, compared with neural activity in null trials. Critically, some of these areas also showed enhanced connectivity with task-positive control regions. Specifically, task-based connectivity between the striatum and the angular gyri, and between the thalamus and right temporal pole, increased as a function of relational complexity. These findings challenge the notion that functional segregation between regions within default-mode and control networks invariably support cognitive task performance, and reveal previously unknown roles for the striatum and thalamus in managing network dynamics during cognitive reasoning.

摘要

具有挑战性的认知任务的成功执行一方面取决于默认模式网络内活动的一致功能分离,另一方面取决于包含额顶叶和扣带回-脑岛区域的控制网络。然而,最近的研究表明,在某些认知控制情境中,默认模式网络和控制网络内的节点实际上可能会合作以实现最佳任务表现。在此,我们使用功能磁共振成像来检查在解决认知推理问题时关联变量的能力是否涉及默认模式区域和控制区域之间连接性的短暂增加。参与者执行了经典沃森选择任务的修改版本,其中试验中要关联的变量数量会系统地变化。正如预期的那样,与无关联试验中的神经活动相比,默认模式网络内的区域随着关联复杂性的增加呈现出参数性失活。关键的是,这些区域中的一些还显示出与任务积极控制区域的连接性增强。具体而言,纹状体与角回之间以及丘脑与右侧颞极之间基于任务的连接性随着关联复杂性的增加而增强。这些发现挑战了默认模式网络和控制网络内区域之间的功能分离总是支持认知任务表现的观点,并揭示了纹状体和丘脑在认知推理过程中管理网络动态方面以前未知的作用。

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