Evidence map›Paper›PMID 28213118›Full record

ArticleNeuroImage2017

The global signal in fMRI: Nuisance or Information?

Thomas T Liu, Alican Nalci, Maryam Falahpour

Abstract read
In one paragraph

Article in NeuroImage, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 252 papers.

0numbers the graph read from it
0cells of the map it votes in
252citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

252 citing papers in PubMed.

  1. Altered resting-state functional connectivity in lung cancer patients with comorbid depressive symptoms.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
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  6. Human cerebral cortex organization characterized by functional PET-FDG "Metabolic Connectivity".European journal of nuclear medicine and molecular imaging · 2026
    Article
  7. Article
  8. Article
  9. Article
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  12. Global Signal Removal (GSR) as graph spatial filtering.bioRxiv : the preprint server for biology · 2026
    Article
  13. Review
  14. Article
  15. Article
  16. Sleep deprivation exhibits an age-dependent effect on infraslow global brain activity.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  17. Article
  18. Article
  19. Article
  20. Article

192 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Thomas T LiuCenter 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. Electronic address: ttliu@ucsd.edu.
Alican NalciCenter 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. Electronic address: analci@ucsd.edu.
Maryam FalahpourCenter for Functional MRI, University of California San Diego, 9500 Gilman Drive MC 0677, La Jolla, CA 92093, United States. Electronic address: mfalahpour@ucsd.edu.

Funding

Assessing vigilance with resting-state fMRIR21MH112155 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI LIU, THOMAS T · 2017 to 2018
$426k
Global Signal Correction in Resting State fMRIR21MH096495 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI LIU, THOMAS T · 2012 to 2013
$418k
NIMH NIH HHS R21 MH096495NIMH NIH HHS R21 MH112155
6 · The paper itself

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.

Indexed as

ArtifactsBrain MappingHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingfMRIGeneral linear modelGlobal signalMotionPhysiological noiseVigilance

Identifiers

PMID28213118
PMCPMC5406229

What OpenQuestion holds

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LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.