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Towards a consensus regarding global signal regression for resting state functional connectivity MRI
by
Fox, Michael D.
, Murphy, Kevin
in
Blood
/ Caffeine
/ Carbon dioxide
/ Connectome - methods
/ Consensus
/ Data processing
/ Functional magnetic resonance imaging
/ Humans
/ Image Processing, Computer-Assisted - methods
/ Magnetic Resonance Imaging - methods
/ Neural networks
/ Time series
2017
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Towards a consensus regarding global signal regression for resting state functional connectivity MRI
by
Fox, Michael D.
, Murphy, Kevin
in
Blood
/ Caffeine
/ Carbon dioxide
/ Connectome - methods
/ Consensus
/ Data processing
/ Functional magnetic resonance imaging
/ Humans
/ Image Processing, Computer-Assisted - methods
/ Magnetic Resonance Imaging - methods
/ Neural networks
/ Time series
2017
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Do you wish to request the book?
Towards a consensus regarding global signal regression for resting state functional connectivity MRI
by
Fox, Michael D.
, Murphy, Kevin
in
Blood
/ Caffeine
/ Carbon dioxide
/ Connectome - methods
/ Consensus
/ Data processing
/ Functional magnetic resonance imaging
/ Humans
/ Image Processing, Computer-Assisted - methods
/ Magnetic Resonance Imaging - methods
/ Neural networks
/ Time series
2017
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Towards a consensus regarding global signal regression for resting state functional connectivity MRI
Journal Article
Towards a consensus regarding global signal regression for resting state functional connectivity MRI
2017
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Overview
The number of resting state functional connectivity MRI studies continues to expand at a rapid rate along with the options for data processing. Of the processing options, few have generated as much controversy as global signal regression and the subsequent observation of negative correlations (anti-correlations). This debate has motivated new processing strategies and advancement in the field, but has also generated significant confusion and contradictory guidelines. In this article, we work towards a consensus regarding global signal regression. We highlight several points of agreement including the fact that there is not a single “right” way to process resting state data that reveals the “true” nature of the brain. Although further work is needed, different processing approaches likely reveal complementary insights about the brain's functional organisation.
•Global signal regression is a controversial resting state fMRI pre-processing option.•The debate about GSR has generated significant confusion and contradictory guidelines.•Here, we present our consensus statement on the use of GSR in resting state analyses.•There is no “right” way to pre-process that reveals the “true” nature of the brain.•Different processing approaches reveal complimentary insights about brain function.
Publisher
Elsevier Inc,Elsevier Limited,Academic Press
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