Cited by 2,387Functional Brain Connectivity StudiesAdvanced MRI Techniques and ApplicationsAdvanced Neuroimaging Techniques and Applications

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The impact of global signal regression on resting state correlations: Are anti-correlated networks introduced?

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Murphy, Kevin, Birn, Rasmus M., Handwerker, Daniel A., Jones, Tyler B., Bandettini, Peter A.·2009·NeuroImage

DOI 10.1016/j.neuroimage.2008.09.036PMC PMC2750906

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Abstract

Low-frequency fluctuations in fMRI signal have been used to map several consistent resting state networks in the brain. Using the posterior cingulate cortex as a seed region, functional connectivity analyses have found not only positive correlations in the default mode network but negative correlations in another resting state network related to attentional processes. The interpretation is that the human brain is intrinsically organized into dynamic, anti-correlated functional networks. Global variations of the BOLD signal are often considered nuisance effects and are commonly removed using a general linear model (GLM) technique. This global signal regression method has been shown to introduce negative activation measures in standard fMRI analyses. The topic of this paper is whether such a correction technique could be the cause of anti-correlated resting state networks in functional connectivity analyses. Here we show that, after global signal regression, correlation values to a seed voxel must sum to a negative value. Simulations also show that small phase differences between regions can lead to spurious negative correlation values. A combination breath holding and visual task demonstrates that the relative phase of global and local signals can affect connectivity measures and that, experimentally, global signal regression leads to bell-shaped correlation value distributions, centred on zero. Finally, analyses of negatively correlated networks in resting state data show that global signal regression is most likely the cause of anti-correlations. These results call into question the interpretation of negatively correlated regions in the brain when using global signal regression as an initial processing step.

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Authors: Murphy, K., Birn, R. M., Handwerker, D. A., Jones, T. B., & Bandettini, P. A.
Affiliations: National Institutes of Health (US)
Corresponding author: Bandettini, Peter A.
ORCID: Murphy, Kevin
Birn, Rasmus M.
Handwerker, Daniel A.
Bandettini, Peter A.
Venue: NeuroImage
Publisher: Elsevier BV
Published: 2009-02
Volume: 44
Issue: 3
Pages: 893-905
ISSN: 1053-8119 (ISSN-L)
DOI: 10.1016/j.neuroimage.2008.09.036
PMC: PMC2750906
OpenAlex: W2169787465
Cited by: 2,387
References: 64
Citations by year: 2026: 118 · 2025: 104 · 2024: 109 · 2023: 78 · 2022: 121 · 2021: 133 · 2020: 173 · 2019: 157 · 2018: 166 · 2017: 204 · 2016: 187 · 2015: 188 · 2014: 181 · 2013: 168 · 2012: 114
FWCI: 31.87
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations: NeuroImage (publishedVersion)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
Funders: National Institutes of Health
National Institute of Mental Health (Z01MH002783)
Topics: Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
Keywords: global signal regression, resting-state functional connectivity, default mode network, attentional networks, posterior cingulate cortex, phase difference, breath-holding, visual task, seed-based correlation analysis
MeSH terms: Biological Clocks, Brain, Computer Simulation, Humans, Magnetic Resonance Imaging, Male, Models, Neurological, Nerve Net, Regression Analysis, Rest, Statistics as Topic, Young Adult

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The impact of global signal regression on resting state correlations: Are anti-correlated networks introduced?

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