Test-retest reliability of resting-state connectivity network characteristics using fMRI and graph theoretical measures
Abstract
Characterizing the brain connectome using neuroimaging data and measures derived from graph theory emerged as a new approach that has been applied to brain maturation, cognitive function and neuropsychiatric disorders. For a broad application of this method especially for clinical populations and longitudinal studies, the reliability of this approach and its robustness to confounding factors need to be explored. Here we investigated test-retest reliability of graph metrics of functional networks derived from functional magnetic resonance imaging (fMRI) recorded in 33 healthy subjects during rest. We constructed undirected networks based on the Anatomic-Automatic-Labeling (AAL) atlas template and calculated several commonly used measures from the field of graph theory, focusing on the influence of different strategies for confound correction. For each subject, method and session we computed the following graph metrics: clustering coefficient, characteristic path length, local and global efficiency, assortativity, modularity, hierarchy and the small-worldness scalar. Reliability of each graph metric was assessed using the intraclass correlation coefficient (ICC). Overall ICCs ranged from low to high (0 to 0.763) depending on the method and metric. Methodologically, the use of a broader frequency band (0.008-0.15 Hz) yielded highest reliability indices (mean ICC=0.484), followed by the use of global regression (mean ICC=0.399). In general, the second order metrics (small-worldness, hierarchy, assortativity) studied here, tended to be more robust than first order metrics. In conclusion, our study provides methodological recommendations which allow the computation of sufficiently robust markers of network organization using graph metrics derived from fMRI data at rest.
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Multiple studies have found evidence for limited test-retest reliability using a multitude of conventional rs-fcMRI network characteristics and analytic approaches.
“Multiple studies have found evidence for limited test-retest reliability using a multitude of conventional rs-fcMRI network characteristics and analytic approaches (Braun et al., 2012; Wang et al., 2011; Wisner et al., 2013; Zuo et al., 2010; Zuo and Xing, 2014).”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Braun et al., 2012
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“Multiple studies have found evidence for limited test-retest reliability using a multitude of conventional rs-fcMRI network characteristics and analytic approaches (Braun et al., 2012; Wang et al., 2011; Wisner et al., 2013; Zuo et al., 2010; Zuo and Xing, 2014).”
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- Authors
- Braun, U., Plichta, M. M., Esslinger, C., Sauer, C., Haddad, L., Grimm, O., Mier, D., Mohnke, S., Heinz, A., Erk, S., Walter, H., Seiferth, N., Kirsch, P., & Meyer-Lindenberg, A.
- Affiliations
- Heidelberg University (DE)
- Charité – Universitätsmedizin Berlin (DE)
- Corresponding author
- Plichta, Michael M.
- ORCID
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2012-01
- Volume
- 59
- Issue
- 2
- Pages
- 1404-1412
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2036146354
- Cited by
- 424
- References
- 62
- Citations by year
- 2026: 6 · 2025: 17 · 2024: 26 · 2023: 26 · 2022: 27 · 2021: 34 · 2020: 33 · 2019: 34 · 2018: 40 · 2017: 43 · 2016: 30 · 2015: 44 · 2014: 19 · 2013: 28 · 2012: 16
- FWCI
- 10.36
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Funders
- NEWMEDS (115008)
- BMBF
- DFG (SFB 636-B7)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Keywords
- test-retest reliability, resting-state functional connectivity, brain connectome, network metrics, small-worldness, network hierarchy, assortativity, clustering coefficient, average path length, network efficiency, modularity, frequency band selection, intraclass correlation coefficient, AAL atlas
- MeSH terms
- Adult, Algorithms, Brain, Female, Humans, Image Enhancement, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Male, Nerve Net, Pattern Recognition, Automated, Rest, Sensitivity and Specificity, Reproducibility of Results, Young Adult
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