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人类静息态脑活动中的全脑传播模式。

Whole-brain propagating patterns in human resting-state brain activities.

机构信息

Computational Brain Dynamics Team, RIKEN Center for Advanced Intelligence Project, 2-2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0288, Japan; Department of Computational Brain Imaging, ATR Neural Information Analysis Laboratories, 2-2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0288, Japan.

Department of Computational Brain Imaging, ATR Neural Information Analysis Laboratories, 2-2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0288, Japan.

出版信息

Neuroimage. 2021 Dec 15;245:118711. doi: 10.1016/j.neuroimage.2021.118711. Epub 2021 Nov 16.

Abstract

Repetitive propagating activities in resting-state brain activities have been widely observed in various species and regions. Because they resemble the preceding brain activities during tasks, they are assumed to reflect past experiences embedded in neuronal circuits. "Whole-brain" propagating activities may also reflect a process that integrates information distributed over the entire brain, such as visual and motor information. Here we reveal whole-brain propagating activities from human resting-state magnetoencephalography (MEG) and electroencephalography (EEG) data. We simultaneously recorded the MEGs and EEGs and estimated the source currents from both measurements. Then using our recently proposed algorithm, we extracted repetitive spatiotemporal patterns from the source currents. The estimated patterns consisted of multiple frequency components, each of which transiently exhibited the frequency-specific resting-state networks (RSNs) of functional MRIs (fMRIs), such as the default mode and sensorimotor networks. A simulation test suggested that the spatiotemporal patterns reflected the phase alignment of the multiple frequency oscillators induced by the propagating activities along the anatomical connectivity. These results argue that whole-brain propagating activities transiently exhibited multiple RSNs in their multiple frequency components, suggesting that they reflected a process to integrate the information distributed over the frequencies and networks.

摘要

在各种物种和区域中,广泛观察到静息态脑活动中的重复传播活动。由于它们类似于任务期间的先前脑活动,因此它们被认为反映了嵌入神经元回路中的过去经验。“全脑”传播活动也可能反映了整合分布在整个大脑中的信息的过程,例如视觉和运动信息。在这里,我们从人类静息状态脑磁图 (MEG) 和脑电图 (EEG) 数据中揭示了全脑传播活动。我们同时记录了 MEG 和 EEG,并从这两种测量中估计了源电流。然后,我们使用最近提出的算法,从源电流中提取重复的时空模式。估计的模式由多个频率分量组成,每个频率分量都会暂时表现出功能磁共振成像 (fMRI) 的特定静息状态网络 (RSN),例如默认模式和感觉运动网络。模拟测试表明,时空模式反映了沿解剖连接传播活动引起的多个频率振荡器的相位对齐。这些结果表明,全脑传播活动在其多个频率分量中短暂表现出多个 RSN,表明它们反映了整合分布在频率和网络中的信息的过程。

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