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On the origins of the ‘global signal’ determined by functional magnetic resonance imaging in the resting state

Overview of attention for article published in Journal of Neural Engineering, December 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

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Article details
Title
On the origins of the ‘global signal’ determined by functional magnetic resonance imaging in the resting state
Published in
Journal of Neural Engineering, December 2015
DOI 10.1088/1741-2560/13/1/016012
Pubmed ID
Authors
Abstract

Functional magnetic resonance imaging blood oxygen level dependent (BOLD) determinations of correlations between 'resting-state' neuronal activity in different regions of cortex have generated much interest. Determination of these correlations requires regressing out signals that are correlated in all parts of the cortex and are taken to be artefactual, such as those due to movement, respiration and cardiovascular activity. However when these are removed there still remains a 'global signal' (GS), which is taken to be of unknown physiological origin, and is regressed out by some researchers but not by others. We have investigated the origin of this GS using cortical models consisting of coupled networks of modules representing regions of interest. We show that the GS has an amplitude that is linearly related to the average correlation between the modules/voxels in the network over a large range of such correlations. The GS arises as a consequence of feedback between the modules/voxels leading to correlations in their BOLD signals. Given the relationship between the GS and the average correlations it might be anticipated that regressing out the GS during preprocessing will significantly modify the correlations subsequently determined. This is shown to be the case when comparing the connections of individual modules with that predicted by the correlations. The present model shows that such correlations can arise as a consequence of the intermodular feedback connectivity without recourse to imposing a GS independent of the connectivity. Our model indicates that the GS reflects the extent of feedback pathways provided by the intermodular/inter-regional connections and hence the average correlation between modules or regions of cortex. However the model has not been used to elucidate the possible contributions of a GS independent of the connectivity, which might indeed contribute to the GS of the cortex.

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
United States 2 6%
Germany 1 3%
Unknown 28 90%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 10 32%
Researcher 6 19%
Professor > Associate Professor 4 13%
Student > Bachelor 3 10%
Professor 2 6%
Other 4 13%
Unknown 2 6%
Readers by discipline
Readers by discipline Count As %
Neuroscience 9 29%
Psychology 6 19%
Medicine and Dentistry 4 13%
Engineering 4 13%
Agricultural and Biological Sciences 2 6%
Other 4 13%
Unknown 2 6%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 December 2015.
All research outputs
#4,752,816
of 27,776,330 outputs
Outputs from Journal of Neural Engineering
#302
of 1,865 outputs
Outputs of similar age
#65,237
of 386,776 outputs
Outputs of similar age from Journal of Neural Engineering
#6
of 30 outputs
Altmetric has tracked 27,776,330 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,865 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.2. This one has done well, scoring higher than 83% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 386,776 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 30 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.