The global signal and observed anticorrelated resting state brain networks.

By Michael D. Fox, Dongyang Zhang, Abraham Z. Snyder, Marcus E. Raichle. Journal of Neurophysiology, 2009

1,908 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/ddfb014761b5293d68914df8a0ad8b2e5af23438

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In Cognitive Neuroscience

Citations in the corpus

The role of physiological noise in resting-state functional connectivity (2012, positive): “…at rest the default mode network (or “task-negative” network) was anti-correlated with other brain regions that generally show increased activity during goal directed tasks (the “task positive” network, encompassing areas involved in attention and various cognitive tasks) (Fox et al., 2005, 2009).”
Functional connectivity of the insula in the resting brain (2011, neutral): “However, the value of anticorrelations in elucidating FC is debated (Fox et al., 2009; Weissenbacher et al., 2009), and these results should be interpreted with caution, particularly when mean signal intensity during the run is removed (Van Dijk et al.”
Global Signal Regression Strengthens Association between Resting-State Functional Connectivity and Behavior (2019, result): “However, consistent with previous work (Murphy et al., 2009; Fox et al., 2009; Weissenbacher et al., 2009), GSR reduces functional connectivity across almost all ROI pairs.”
The effect of machine learning regression algorithms and sample size on individualized behavioral prediction with functional connectivity features (2018, positive): “Notably, the rsFC and rsFCS features in our behavioral/cognitive predictions were extracted after applying global signal regression (GSR), which is a controversial processing step in resting-state functional connectivity analyses (Fox et al., 2009; Murphy et al., 2009; Murphy and Fox, 2017).”
Trouble at Rest: How Correlation Patterns and Group Differences Become Distorted After Global Signal Regression (2012, positive): “Numerous studies since Murphy et al. (2009) have focused on whether or not anticorrelations are solely an artifact of GSReg with conclusions pointing in both directions (Anderson et al., 2011b; Fox et al., 2009; Chai et al., 2012; Chang and Glover, 2009a).”
GRETNA: a graph theoretical network analysis toolbox for imaging connectomics (2015, background): “However, negative correlations may also be introduced by global signal removal, a preprocessing step that is currently controversial (Fox et al., 2009; Murphy et al., 2009; Weissenbacher et al., 2009; Schölvinck et al., 2010).”
Identifying major depression using whole-brain functional connectivity: a multivariate pattern analysis. (2012, methodology): “…this technique is suggested to improve the specificity of positive correlations and can remove specific confounds from the data to facilitate the evaluation of neurophysiological relationships (Fox et al., 2009), so the results with global signal regression are more readily or reliably interpreted.”
REST: A Toolkit for Resting-State Functional Magnetic Resonance Imaging Data Processing (2011, background): “It should be noted that removal of the global mean signal is still controversial in RS-fMRI [32,33].”
The Development of Human Amygdala Functional Connectivity at Rest from 4 to 23 Years: a cross-sectional study (2014, positive): “…of modeling physiological noise that requires removal from the data, but whose sources (heart rate and respiration) were not possible to measure directly in this study or parse out with programs like PESTICA (designed to model adult physiological noise) (Chang and Glover, 2009; Fox et al., 2009).”
The Global Signal in fMRI: Nuisance or Information? (2017, positive): “The application of GSR has been found to greatly improve the functional specificity of restingstate correlation maps (Fox et al., 2009; He and Liu, 2012).”
Toward reliable characterization of functional homogeneity in the human brain: Preprocessing, scan duration, imaging resolution and computational space (2012, background): “Global signal regression is more controversial due to potential introduction of negative correlations and potential to artifactually impact inter-individual differences in connectivity (Chai et al., 2012; Fox et al., 2009; Murphy et al., 2009; Saad et al., 2012).”
Temporal dynamics of spontaneous MEG activity in brain networks (2010, background): “The two networksareanticorrelatedafter removal of a global signal before seedbased correlation mapping (12).”
How Visual Is the Visual Cortex? Comparing Connectional and Functional Fingerprints between Congenitally Blind and Sighted Individuals (2015, background): “…previous studies have suggested that global signal should be removed because it is associated with non-neuronal activity such as respiration (e.g., Fox et al., 2009), this procedure introduces widespread negative functional connectivities and may alter the intrinsic brain network structure (e.g.,…”
Network modelling methods for FMRI (2011, neutral): “, whether it is primarily valid neural-related signal, or uninteresting non-neural physiological confound) and whether it should be subtracted before any further analyses (Fox et al., 2009).”
Sources and implications of whole-brain fMRI signals in humans (2016, methodology): “1053-8119/ Published by Elsevier Inc. MARK Zarahn et al., 1997), whereas others report that the global signal is found primarily in gray matter and not in white matter (Fox et al., 2009) (Fig.”