Share:
Share this content in WeChat
X
Clinical Article
The effect of global signal correction on the functional connectivity of resting brain networks
ZHANG Hong-ying  CHEN Wen-xin  TIAN Tong-tong  YE Jing  LI Jie  YIN Yi-li  WU Jing-tao 

DOI:10.12015/issn.1674-8034.2016.12.002.


[Abstract] Objective: To examine the effect of global signal correction on the functional connectivity in resting-state magnetic resonance imaging network analysis.Materials and Methods: Twenty-three healthy subjects underwent 5 minutes resting-state BOLD fMRI scanning. A method of time-series correlation analysis based on seed regions of posterior cingulate cortex (PCC) and left dorsal lateral prefrontal cortex (dLPFC) was employed to extract default mode network and executive control network. The resulting functional connectivity was compared between with and without global signal correction, while the other preprocessing conditions were identical.Results: The seeds correlation methods could extract default mode network and executive control network which coincided with previous studies, and could also acquire their negative correlated networks. Paired two-sample t test under P<0.005 statistic level with alphasim correction indicated that there were significant increased positive correlations at almost whole brain level.Conclusion: These results from this study show characteristic differences between the networks with and without global signal correction. The correlation coefficients were positively biased in the methods without the whole brain signal correction, so more attention should be paid to the issue of global signal.
[Keywords] Brain;Magnetic resonance imaging;Functional connectivity;Global signal;Magnetic resonance imaging, functional

ZHANG Hong-ying Department of Radiology, Su-bei People's Hospital, Yangzhou 225001, China

CHEN Wen-xin Department of Radiology, Su-bei People's Hospital, Yangzhou 225001, China

TIAN Tong-tong Department of Radiology, Su-bei People's Hospital, Yangzhou 225001, China

YE Jing Department of Radiology, Su-bei People's Hospital, Yangzhou 225001, China

LI Jie Department of Radiology, Su-bei People's Hospital, Yangzhou 225001, China

YIN Yi-li Department of Radiology, Su-bei People's Hospital, Yangzhou 225001, China

WU Jing-tao* Department of Radiology, Su-bei People's Hospital, Yangzhou 225001, China

*Correspondence to: Wu JT, E-mail: wujingtaodoctor@126.com

Conflicts of interest   None.

ACKNOWLEDGMENTS  This work was part of National Natural Science Foundation of China No. 81471624, 81571652
Received  2016-05-20
Accepted  2016-08-01
DOI: 10.12015/issn.1674-8034.2016.12.002
DOI:10.12015/issn.1674-8034.2016.12.002.

[1]
Vincent JL, Kahn I, Snyder AZ, et al. Evidence for a frontoparietal control system revealed by intrinsic functional connectivity. J Neurophysiol, 2008, 100(6): 3328-3342.
[2]
Uddin LQ, Kelly AM, Biswal BB, et al. Functional connectivity of default mode network components: correlation, anticorrelation, and causality. Hum Brain Mapp, 2009, 30(2): 625-637.
[3]
He H, Liu TT. Ageometric view of global signal confounds in resting-state functional MRI. Neuroimage, 2012, 59(3): 2339-2348.
[4]
季公俊,廖伟,张志强,等.全面强直阵挛癫痫静息态功能连接脑网络研究.磁共振成像, 2013, 4(1): 8-12.
[5]
Fox MD, Zhang D, Snyder AZ, et al. The global signal and observed anticorrelated resting state brain networks. J Neurophysiol, 2009, 101(6): 3270-3283.
[6]
Chang C, Glover GH. Effects of model-based physiological noise correction on default mode network anticorrelations and correlations. Neuroimage, 2009, 47(4): 1448-1459.
[7]
Murphy K, Birn RM, Handwerker DA, et al. The impact of global signal regression on resting state correlations: are anti-correlated networks introduced?. Neuroimage, 2009, 44(3): 893-905.
[8]
Anderson JS, Druzgal TJ, Lopez-Larson M, et al. Network anticorrelations, global regression, and phase-shifted soft tissue correction. Hum Brain Mapp, 2011, 32(6): 919-934.
[9]
Zhang HY, Chen WX, Jiao Y, et al. Selective vulnerability related to aging in large-scale resting brain networks. PLos One, 2014, 9(10): e108807.
[10]
Hayasaka S. Functional connectivity networks with and without global signal correction. Front Hum Neurosci, 2013, 7(7): 880.
[11]
Yan CG, Craddock RC, Zuo XN, et al. Standardizing the intrinsic brain: towards robust measurement of inter-individual variation in 1000 functional connectomes. Neuroimage, 2013, 80(20): 246-262.

PREV The 2016 World Health Organization classification of tumors of the central nervous system: A summary
NEXT Measurement of fat content in vertebral body by magnetic resonance water fat separation
  



Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn