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静息态网络的频谱特征。

Spectral characteristics of resting state networks.

机构信息

Biomedical Physics Department, King Faisal Specialist Hospital & Research Centre, Riyadh, Saudi Arabia.

出版信息

Prog Brain Res. 2011;193:259-76. doi: 10.1016/B978-0-444-53839-0.00017-X.


DOI:10.1016/B978-0-444-53839-0.00017-X
PMID:21854968
Abstract

Resting state networks (RSNs), as imaged by functional MRI, are distributed maps of areas believed to be involved in the function of the "resting" brain, which appear in both resting and task data. The current dominant view is that such networks are associated with slow (∼0.015Hz), spontaneous fluctuations in the BOLD signal. To date, limited work has investigated the frequency characteristics of RSNs; here we investigate a range of issues relating to their spectral and phase characteristics. Our results indicate that RSNs, although dominated by low frequencies in the raw BOLD signal, are in fact broadband processes that show temporal coherences across a wide frequency spectrum. In addition, we show that RSNs exhibit different levels of phase synchrony at different frequencies. These findings challenge the notion that FMRI resting signals are simple "low frequency" spontaneous signal fluctuations.

摘要

静息态网络(RSNs),如功能磁共振成像所显示的,是分布在被认为与“静息”大脑功能相关的区域的图谱,它们出现在静息和任务数据中。目前占主导地位的观点认为,这种网络与慢(∼0.015Hz)、自发的 BOLD 信号波动有关。迄今为止,有限的工作已经研究了 RSN 的频率特征;在这里,我们研究了与它们的光谱和相位特征有关的一系列问题。我们的结果表明,尽管 RSN 在原始 BOLD 信号中主要由低频主导,但实际上它们是宽带过程,在广泛的频谱范围内表现出时间相干性。此外,我们还表明,RSN 在不同频率下表现出不同程度的相位同步。这些发现挑战了 FMRI 静息信号是简单的“低频”自发信号波动的概念。

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