Rest-task modulation of fMRI-derived global signal topography is mediated by transient co-activation patterns

Recent resting-state fMRI studies have revealed that the global signal
(GS) exhibits a non-uniform spatial distribution across the gray matter.
Whether this topography is informative remains largely unknown. We
therefore tested rest-task modulation of global signal topography by
analyzing static global signal correlation and dynamic co-activation
patterns in a large sample of fMRI dataset (n=837) from the Human
Connectome Project. The GS topography in the resting-state and in seven
different tasks was first measured by correlating the global signal with
the local timeseries (GSCORR). In the resting state, high GSCORR was
observed mainly in the primary sensory and motor regions, while low GSCORR
was seen in the association brain areas. This pattern changed during the
seven tasks, with mainly decreased GSCORR in sensorimotor cortex.
Importantly, this rest-task modulation of GSCORR could be traced to
transient co-activation patterns at the peak period of global signal
(GS-peak). By comparing the topography of GSCORR and respiration effects,
we observed that the topography of respiration mimicked the topography of
global signal in the resting-state whereas both differed during the task
states; due to such partial dissociation, we assume that GSCORR could not
be equated with a respiration effect. Finally, rest-task modulation of GS
topography could not be exclusively explained by other sources of
physiological noise. Together, we here demonstrate the informative nature
of global signal topography by showing its rest-task modulation, the
underlying dynamic co-activation patterns, and its partial dissociation
from respiration effects during task states.

近期的静息态功能磁共振成像（resting-state fMRI）研究表明，全局信号（global signal, GS）在灰质内呈现非均匀的空间分布。该全局信号的空间拓扑结构是否具备信息价值，目前仍不甚明确。为此，我们依托人类连接组计划（Human Connectome Project）的大样本功能磁共振成像数据集（n=837），通过分析静态全局信号相关性与动态共激活模式，检验了全局信号拓扑结构的静息态-任务态调制效应。

首先，我们通过计算全局信号与局部时间序列的相关性（GSCORR），分别测量了静息态以及7种不同任务态下的GS拓扑结构。在静息态下，高GSCORR主要分布于初级感觉与运动皮层，而低GSCORR则见于联合皮层区域。这一模式在7种任务态中发生了改变：感觉运动皮层的GSCORR整体呈现下降趋势。

重要的是，GSCORR的这种静息态-任务态调制效应，可追溯至全局信号峰值期（GS-peak）的瞬时共激活模式。通过对比GSCORR与呼吸效应的拓扑结构，我们发现静息态下呼吸效应的拓扑结构与全局信号的拓扑结构相似，但在任务态下二者出现部分解离；基于这一现象，我们认为GSCORR不能等同于呼吸效应。

最后，全局信号拓扑结构的静息态-任务态调制效应，无法完全由其他生理噪声来源解释。

综上，本研究通过阐明全局信号拓扑结构的静息态-任务态调制特性、其背后的动态共激活模式，以及任务态下其与呼吸效应的部分解离关系，证实了全局信号拓扑结构确实具备信息承载能力。