Department of Biophysics, Medical College of Wisconsin, Milwaukee, Wisconsin 53226, USA.
Magn Reson Med. 2012 Dec;68(6):1828-35. doi: 10.1002/mrm.24201. Epub 2012 Feb 14.
In resting-state functional MRI studies, the global signal (operationally defined as the global average of resting-state functional MRI time courses) is often considered a nuisance effect and commonly removed in preprocessing. This global signal regression method can introduce artifacts, such as false anticorrelated resting-state networks in functional connectivity analyses. Therefore, the efficacy of this technique as a correction tool remains questionable. In this article, we establish that the accuracy of the estimated global signal is determined by the level of global noise (i.e., non-neural noise that has a global effect on the resting-state functional MRI signal). When the global noise level is low, the global signal resembles the resting-state functional MRI time courses of the largest cluster, but not those of the global noise. Using real data, we demonstrate that the global signal is strongly correlated with the default mode network components and has biological significance. These results call into question whether or not global signal regression should be applied. We introduce a method to quantify global noise levels. We show that a criteria for global signal regression can be found based on the method. By using the criteria, one can determine whether to include or exclude the global signal regression in minimizing errors in functional connectivity measures.
在静息态功能磁共振成像研究中，全局信号（操作上定义为静息态功能磁共振时间序列的全局平均值）通常被认为是一种干扰效应，并在预处理中经常被去除。这种全局信号回归方法可能会引入伪影，例如在功能连接分析中出现虚假的负相关静息态网络。因此，该技术作为一种校正工具的效果仍然存在疑问。在本文中，我们确定了估计全局信号的准确性取决于全局噪声的水平（即对静息态功能磁共振信号具有全局影响的非神经噪声）。当全局噪声水平较低时，全局信号类似于最大簇的静息态功能磁共振时间序列，但与全局噪声不同。使用真实数据，我们证明了全局信号与默认模式网络成分强烈相关，具有生物学意义。这些结果引发了是否应该应用全局信号回归的问题。我们引入了一种量化全局噪声水平的方法。我们表明，可以根据该方法找到用于全局信号回归的标准。通过使用该标准，可以确定在最小化功能连接测量误差时是否包含或排除全局信号回归。
