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采用视觉Oddball 范式评估三重静息态网络中任务诱发的自发脑活动和功能连接的调制动力学。

Dynamics of task-induced modulation of spontaneous brain activity and functional connectivity in the triple resting-state networks assessed using the visual oddball paradigm.

机构信息

Institute of Neuroscience and Medicine, INM-4, Forschungszentrum Jülich GmbH, Jülich, Germany.

Department of Medical Imaging, Arab-American University Palestine, AAUP, Jenin, Palestine.

出版信息

PLoS One. 2021 Nov 4;16(11):e0246709. doi: 10.1371/journal.pone.0246709. eCollection 2021.

Abstract

The default mode network (DMN), the salience network (SN), and the central executive network (CEN) are considered as the core resting-state brain networks (RSN) due to their involvement in a wide range of cognitive tasks. Despite the large body of knowledge related to their regional spontaneous activity (RSA) and functional connectivity (FC) of these networks, less is known about the dynamics of the task-associated modulation on these parameters and the task-induced interaction between these three networks. We have investigated the effects of the visual-oddball paradigm on three fMRI measures (amplitude of low-frequency fluctuations for RSA, regional homogeneity for local FC, and degree centrality for global FC) in these three core RSN. A rest-task-rest paradigm was used and the RSNs were identified using independent component analysis (ICA) on the resting-state data. The observed patterns of change differed noticeably between the networks and were tightly associated with the task-related brain activity and the distinct involvement of the networks in the performance of the single subtasks. Furthermore, the inter-network analysis showed an increased synchronization of CEN with the DMN and the SN immediately after the task, but not between the DMN and SN. Higher pre-task inter-network synchronization between the DMN and the CEN was associated with shorter reaction times and thus better performance. Our results provide some additional insights into the dynamics within and between the triple RSN. Further investigations are required in order to understand better their functional importance and interplay.

摘要

默认模式网络 (DMN)、突显网络 (SN) 和中央执行网络 (CEN) 被认为是核心静息态脑网络 (RSN),因为它们参与了广泛的认知任务。尽管与这些网络的区域自发性活动 (RSA) 和功能连接 (FC) 相关的知识很多,但对于这些参数的任务相关调制的动力学以及这三个网络之间的任务诱导相互作用知之甚少。我们研究了视觉Oddball 范式对三个 fMRI 测量指标(RSA 的低频波动幅度、局部 FC 的局部一致性和全局 FC 的度数中心性)的影响。使用静息态数据的独立成分分析 (ICA) 识别 RSN。观察到的变化模式在网络之间有明显的差异,与与任务相关的大脑活动以及网络在执行单个子任务中的不同参与密切相关。此外,网络间分析显示,任务后 CEN 与 DMN 和 SN 的同步性增加,但 DMN 和 SN 之间没有。任务前 DMN 和 CEN 之间更高的网络间同步性与更短的反应时间相关,从而表现更好。我们的结果为三重 RSN 内和之间的动力学提供了一些额外的见解。需要进一步的研究才能更好地理解它们的功能重要性和相互作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10e0/8568109/981f84e13a74/pone.0246709.g001.jpg

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