| Literature DB >> 28213118 |
Thomas T Liu1, Alican Nalci2, Maryam Falahpour3.
Abstract
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.Entities:
Keywords: General linear model; Global signal; Motion; Physiological noise; Vigilance; fMRI
Mesh:
Year: 2017 PMID: 28213118 PMCID: PMC5406229 DOI: 10.1016/j.neuroimage.2017.02.036
Source DB: PubMed Journal: Neuroimage ISSN: 1053-8119 Impact factor: 6.556