The impact of global signal regression on resting state correlations: are anti-correlated networks introduced?
Open accessAbstract
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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Physiological noises such as cardiac and respiratory rates can alias into the low-frequency domain of functional MRI signals.
“Some physiological noises, such as cardiac and respiratory rates, can alias into the low-frequency domain of functional MRI signals (Strother, 2006;Murphy et al., 2009).”
From Identifying major depression using whole-brain functional connectivity: a multivariate pattern analysis (2012) · cites this paper as Murphy et al., 2009
Negative connections in functional data may be purely a statistical artifact.
“The interpretation of negative correlations is especially controversial because they only become strongly evident after regressing out the global signal; therefore some argue that negative connections in functional data may be purely a statistical artifact (Murphy et al., 2009).”
From Characterizing heterogeneity in children with and without ADHD based on reward system connectivity (2015) · cites this paper as Murphy et al., 2009
Some experts suggested that global regression techniques might introduce spurious negative correlations when whole-brain signals are regressed out.
“Some experts have suggested that these techniques might introduce spurious negative correlations upon regressing out whole brain signals (Murphy et al, 2009;Van Dijk et al, 2009).”
From Understanding the Effects of Stimulant Medications on Cognition in Individuals with Attention-Deficit Hyperactivity Disorder: A Decade of Progress (2011) · cites this paper as Murphy et al, 2009
Depression commonly co-occurs with PTSD in veteran populations, with estimates up to 80%.
“Though depression commonly co-occurs with PTSD in veteran populations (up to 80% by some estimations70)”
From Altered resting-state amygdala functional connectivity in men with posttraumatic stress disorder (2012) · cites this paper as [70]
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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.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2009-02
- Volume
- 44
- Issue
- 3
- Pages
- 893-905
- ISSN
- 1053-8119 (ISSN-L)
- 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
- 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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