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功率谱揭示了白质中不同的血氧水平依赖静息态时间进程。

Power spectra reveal distinct BOLD resting-state time courses in white matter.

作者信息

Li Muwei, Gao Yurui, Ding Zhaohua, Gore John C

机构信息

Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN 37232;

Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232.

出版信息

Proc Natl Acad Sci U S A. 2021 Nov 2;118(44). doi: 10.1073/pnas.2103104118.

Abstract

Accurate characterization of the time courses of blood-oxygen-level-dependent (BOLD) signal changes is crucial for the analysis and interpretation of functional MRI data. While several studies have shown that white matter (WM) exhibits distinct BOLD responses evoked by tasks, there have been no comprehensive investigations into the time courses of spontaneous signal fluctuations in WM. We measured the power spectra of the resting-state time courses in a set of regions within WM identified as showing synchronous signals using independent components analysis. In each component, a clear separation between voxels into two categories was evident, based on their power spectra: one group exhibited a single peak, and the other had an additional peak at a higher frequency. Their groupings are location specific, and their distributions reflect unique neurovascular and anatomical configurations. Importantly, the two categories of voxels differed in their engagement in functional integration, revealed by differences in the number of interregional connections based on the two categories separately. Taken together, these findings suggest WM signals are heterogeneous in nature and depend on local structural-vascular-functional associations.

摘要

准确表征血氧水平依赖(BOLD)信号变化的时间过程对于功能磁共振成像(fMRI)数据的分析和解释至关重要。虽然多项研究表明白质(WM)在任务诱发下表现出独特的BOLD反应,但尚未对白质中自发信号波动的时间过程进行全面研究。我们使用独立成分分析测量了在一组被确定为显示同步信号的白质区域内静息状态时间过程的功率谱。在每个成分中,基于体素的功率谱,明显可将其清晰地分为两类:一类表现为单峰,另一类在更高频率处有额外的峰。它们的分组具有位置特异性,其分布反映了独特的神经血管和解剖结构。重要的是,基于这两类分别进行区域间连接数量的差异显示,这两类体素在功能整合中的参与程度有所不同。综上所述,这些发现表明白质信号本质上是异质性的,并且依赖于局部结构 - 血管 - 功能关联。

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