Test-retest reliabilities of resting-state FMRI measurements in human brain functional connectomics: a systems neuroscience perspective

Xi-Nian Zuo; Xiu-Xia Xing

doi:10.1016/j.neubiorev.2014.05.009

Test-retest reliabilities of resting-state FMRI measurements in human brain functional connectomics: a systems neuroscience perspective

Neurosci Biobehav Rev. 2014 Sep:45:100-18. doi: 10.1016/j.neubiorev.2014.05.009. Epub 2014 May 27.

Authors

Xi-Nian Zuo¹, Xiu-Xia Xing²

Affiliations

¹ Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China; Laboratory for Functional Connectome and Development, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China; Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China. Electronic address: zuoxn@psych.ac.cn.
² College of Applied Sciences, Beijing University of Technology, Beijing 100124, China. Electronic address: xingxx@bjut.edu.cn.

PMID: 24875392
DOI: 10.1016/j.neubiorev.2014.05.009

Abstract

Resting-state functional magnetic resonance imaging (RFMRI) enables researchers to monitor fluctuations in the spontaneous brain activities of thousands of regions in the human brain simultaneously, representing a popular tool for macro-scale functional connectomics to characterize normal brain function, mind-brain associations, and the various disorders. However, the test-retest reliability of RFMRI remains largely unknown. We review previously published papers on the test-retest reliability of voxel-wise metrics and conduct a meta-summary reliability analysis of seven common brain networks. This analysis revealed that the heteromodal associative (default, control, and attention) networks were mostly reliable across the seven networks. Regarding examined metrics, independent component analysis with dual regression, local functional homogeneity and functional homotopic connectivity were the three mostly reliable RFMRI metrics. These observations can guide the use of reliable metrics and further improvement of test-retest reliability for other metics in functional connectomics. We discuss the main issues with low reliability related to sub-optimal design and the choice of data processing options. Future research should use large-sample test-retest data to rectify both the within-subject and between-subject variability of RFMRI measurements and accelerate the application of functional connectomics.

Keywords: Brain connectome; Functional connectomics; Reproducibility; Resting state fMRI; Test-retest reliability.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Review

MeSH terms

Brain / physiology*
Connectome / methods*
Humans
Magnetic Resonance Imaging / methods*
Neural Pathways / physiology
Reproducibility of Results
Signal Processing, Computer-Assisted

Abstract

Publication types

MeSH terms

Grants and funding