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动态连接调制默认模式网络核心区域的局部活动。

Dynamic connectivity modulates local activity in the core regions of the default-mode network.

机构信息

Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129;

Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA 02129.

出版信息

Proc Natl Acad Sci U S A. 2017 Sep 5;114(36):9713-9718. doi: 10.1073/pnas.1702027114. Epub 2017 Aug 21.

DOI:10.1073/pnas.1702027114
PMID:28827337
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5594646/
Abstract

Segregation and integration are distinctive features of large-scale brain activity. Although neuroimaging studies have been unraveling their neural correlates, how integration takes place over segregated modules remains elusive. Central to this problem is the mechanism by which a brain region adjusts its activity according to the influence it receives from other regions. In this study, we explore how dynamic connectivity between two regions affects the neural activity within a participating region. Combining functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) in the same group of subjects, we analyzed resting-state data from the core of the default-mode network. We observed directed influence from the posterior cingulate cortex (PCC) to the anterior cingulate cortex (ACC) in the 10-Hz range. This time-varying influence was associated with the power alteration in the ACC: strong influence corresponded with a decrease of power around 13-16 Hz and an increase of power in the lower (1-7 Hz) and higher (30-55 Hz) ends of the spectrum. We also found that the amplitude of the 30- to 55-Hz activity was coupled to the phase of the 3- to 4-Hz activity in the ACC. These results characterized the local spectral changes associated with network interactions. The specific spectral information both highlights the functional roles of PCC-ACC connectivity in the resting state and provides insights into the dynamic relationship between local activity and coupling dynamics of a network.

摘要

分离和整合是大脑大规模活动的显著特征。尽管神经影像学研究已经揭示了它们的神经相关性,但整合是如何在分离的模块中发生的仍然难以捉摸。这个问题的核心是大脑区域根据其从其他区域接收到的影响来调整其活动的机制。在这项研究中,我们探讨了两个区域之间的动态连接如何影响参与区域内的神经活动。我们在同一组受试者中结合功能磁共振成像(fMRI)和脑磁图(MEG),分析了默认模式网络核心的静息态数据。我们观察到在后扣带回皮层(PCC)到前扣带回皮层(ACC)的 10Hz 范围内存在有方向的影响。这种时变的影响与 ACC 中的功率变化有关:强影响对应于大约 13-16Hz 处的功率下降和频谱低端(1-7Hz)和高端(30-55Hz)处的功率增加。我们还发现,30-55Hz 活动的幅度与 ACC 中 3-4Hz 活动的相位耦合。这些结果描述了与网络相互作用相关的局部频谱变化。特定的频谱信息不仅突出了 PCC-ACC 连接在静息状态下的功能作用,而且为局部活动与网络耦合动力学之间的动态关系提供了深入的了解。