功能磁共振成像中的全局信号：干扰因素还是信息？
The global signal in fMRI: Nuisance or Information?
作者信息
Liu Thomas T, Nalci Alican, Falahpour Maryam
机构信息
Center for Functional MRI, University of California San Diego, 9500 Gilman Drive MC 0677, La Jolla, CA 92093, United States; Departments of Radiology, Psychiatry, and Bioengineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, United States.
Center for Functional MRI, University of California San Diego, 9500 Gilman Drive MC 0677, La Jolla, CA 92093, United States; Department of Electrical and Computer Engineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, United States.
出版信息
Neuroimage. 2017 Apr 15;150:213-229. doi: 10.1016/j.neuroimage.2017.02.036. Epub 2017 Feb 16.
The global signal is widely used as a regressor or normalization factor for removing the effects of global variations in the analysis of functional magnetic resonance imaging (fMRI) studies. However, there is considerable controversy over its use because of the potential bias that can be introduced when it is applied to the analysis of both task-related and resting-state fMRI studies. In this paper we take a closer look at the global signal, examining in detail the various sources that can contribute to the signal. For the most part, the global signal has been treated as a nuisance term, but there is growing evidence that it may also contain valuable information. We also examine the various ways that the global signal has been used in the analysis of fMRI data, including global signal regression, global signal subtraction, and global signal normalization. Furthermore, we describe new ways for understanding the effects of global signal regression and its relation to the other approaches.
在功能磁共振成像（fMRI）研究分析中，全局信号被广泛用作回归变量或归一化因子，以消除全局变化的影响。然而，由于在将其应用于任务相关和静息态fMRI研究分析时可能引入潜在偏差，其使用存在相当大的争议。在本文中，我们更深入地研究全局信号，详细考察可能对该信号有贡献的各种来源。在很大程度上，全局信号一直被视为一个干扰项，但越来越多的证据表明它可能也包含有价值的信息。我们还考察了全局信号在fMRI数据分析中被使用的各种方式，包括全局信号回归、全局信号减法和全局信号归一化。此外，我们描述了理解全局信号回归的影响及其与其他方法关系的新方式。
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