1 Program in Neuroscience, Graduate Division of Biological and Biomedical Sciences, Emory University , Atlanta, Georgia .
2 Department of Biomedical Engineering, Emory/Georgia Institute of Technology , Atlanta, Georgia .
Brain Connect. 2018 Apr;8(3):121-128. doi: 10.1089/brain.2017.0517.
Global signal regression is a controversial processing step for resting-state functional magnetic resonance imaging, partly because the source of the global blood oxygen level-dependent (BOLD) signal remains unclear. On the one hand, nuisance factors such as motion can readily introduce coherent BOLD changes across the whole brain. On the other hand, the global signal has been linked to neural activity and vigilance levels, suggesting that it contains important neurophysiological information and should not be discarded. Any widespread pattern of coordinated activity is likely to contribute appreciably to the global signal. Such patterns may include large-scale quasiperiodic spatiotemporal patterns, known also to be tied to performance on vigilance tasks. This uncertainty surrounding the separability of the global BOLD signal from concurrent neurological processes motivated an examination of the global BOLD signal's spatial distribution. The results clarify that although the global signal collects information from all tissue classes, a diverse subset of the BOLD signal's independent components contribute the most to the global signal. Further, the timing of each network's contribution to the global signal is not consistent across volunteers, confirming the independence of a constituent process that comprises the global signal.
全局信号回归是静息态功能磁共振成像中一个有争议的处理步骤，部分原因是全局血氧水平依赖（BOLD）信号的来源尚不清楚。一方面，诸如运动之类的干扰因素很容易在整个大脑中引入相干的 BOLD 变化。另一方面，全局信号与神经活动和警觉水平有关，这表明它包含重要的神经生理信息，不应被丢弃。任何广泛的协调活动模式都可能对全局信号有很大贡献。这种模式可能包括与警觉任务表现相关的大尺度准周期时空模式。这种与全局 BOLD 信号与并发神经过程的可分离性相关的不确定性促使人们对全局 BOLD 信号的空间分布进行了检查。结果表明，尽管全局信号从所有组织类型中收集信息，但 BOLD 信号的独立分量的一个多样化子集对全局信号的贡献最大。此外，每个网络对全局信号的贡献时间在志愿者之间并不一致，这证实了构成全局信号的组成过程的独立性。
