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在 10000 名英国生物银行参与者中,特征化的默认模式节点的亚专业化。

Subspecialization within default mode nodes characterized in 10,000 UK Biobank participants.

机构信息

Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, 52072 Aachen, Germany.

Department of Electrical and Computer Engineering, Clinical Imaging Research Centre, Singapore Institute for Neurotechnology and Memory Networks Program, National University of Singapore (NUS), 117575 Singapore, Singapore.

出版信息

Proc Natl Acad Sci U S A. 2018 Nov 27;115(48):12295-12300. doi: 10.1073/pnas.1804876115. Epub 2018 Nov 12.

Abstract

The human default mode network (DMN) is implicated in several unique mental capacities. In this study, we tested whether brain-wide interregional communication in the DMN can be derived from population variability in intrinsic activity fluctuations, gray-matter morphology, and fiber tract anatomy. In a sample of 10,000 UK Biobank participants, pattern-learning algorithms revealed functional coupling states in the DMN that are linked to connectivity profiles between other macroscopical brain networks. In addition, DMN gray matter volume was covaried with white matter microstructure of the fornix. Collectively, functional and structural patterns unmasked a possible division of labor within major DMN nodes: Subregions most critical for cortical network interplay were adjacent to subregions most predictive of fornix fibers from the hippocampus that processes memories and places.

摘要

人类的默认模式网络(DMN)与多种独特的心理能力有关。在这项研究中,我们测试了 DMN 中大脑区域间的内在活动波动、灰质形态和纤维束解剖的种群变异性是否可以产生。在一个由 10000 名英国生物银行参与者组成的样本中,模式学习算法揭示了 DMN 中的功能耦合状态,这些状态与其他宏观大脑网络之间的连接模式有关。此外,DMN 的灰质体积与穹窿的白质微观结构相关。总的来说,功能和结构模式揭示了 DMN 主要节点内的一种可能的分工:对皮质网络相互作用最关键的亚区与最能预测从海马体到穹窿纤维的亚区相邻,而海马体是处理记忆和位置的区域。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b214/6275484/47cde041d1ea/pnas.1804876115fig01.jpg

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