Test–retest reliability of fMRI-based graph theoretical properties during working memory, emotion processing, and resting state
Abstract
The investigation of the brain connectome with functional magnetic resonance imaging (fMRI) and graph theory analyses has recently gained much popularity, but little is known about the robustness of these properties, in particular those derived from active fMRI tasks. Here, we studied the test-retest reliability of brain graphs calculated from 26 healthy participants with three established fMRI experiments (n-back working memory, emotional face-matching, resting state) and two parcellation schemes for node definition (AAL atlas, functional atlas proposed by Power et al.). We compared the intra-class correlation coefficients (ICCs) of five different data processing strategies and demonstrated a superior reliability of task-regression methods with condition-specific regressors. The between-task comparison revealed significantly higher ICCs for resting state relative to the active tasks, and a superiority of the n-back task relative to the face-matching task for global and local network properties. While the mean ICCs were typically lower for the active tasks, overall fair to good reliabilities were detected for global and local connectivity properties, and for the n-back task with both atlases, smallworldness. For all three tasks and atlases, low mean ICCs were seen for the local network properties. However, node-specific good reliabilities were detected for node degree in regions known to be critical for the challenged functions (resting-state: default-mode network nodes, n-back: fronto-parietal nodes, face-matching: limbic nodes). Between-atlas comparison demonstrated significantly higher reliabilities for the functional parcellations for global and local network properties. Our findings can inform the choice of processing strategies, brain atlases and outcome properties for fMRI studies using active tasks, graph theory methods, and within-subject designs, in particular future pharmaco-fMRI studies.
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The connectivity matrices are not dominated by simple coactivation during task blocks.
“To ensure that the connectivity matrices are not dominated by simple coactivation during the task blocks, we have regressed out the task activation using a general linear model (GLM), consistent with our prior work (23, 35, 47, 52).”
From Dynamic reconfiguration of frontal brain networks during executive cognition in humans (2015) · cites this paper as [47]
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References 102 · Cited by 227
- Authors
- Cao, H., Plichta, M. M., Schäfer, A., Haddad, L., Grimm, O., Schneider, M., Esslinger, C., Kirsch, P., Meyer-Lindenberg, A., & Tost, H.
- Affiliations
- Heidelberg University (DE)
- Corresponding author
- Tost, Heike
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2014-01
- Volume
- 84
- Pages
- 888-900
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2075712714
- Cited by
- 227
- References
- 102
- Citations by year
- 2026: 9 · 2025: 12 · 2024: 14 · 2023: 11 · 2022: 15 · 2021: 18 · 2020: 17 · 2019: 23 · 2018: 24 · 2017: 31 · 2016: 17 · 2015: 30 · 2014: 6
- FWCI
- 9.69
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Bundesministerium für Bildung und Forschung (01GQ1102)
- China Scholarship Council
- Innovative Medicines Initiative (115008)
- 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, brain connectome, graph theory, functional connectivity, working memory, emotional processing, resting state, n-back task, brain atlas, AAL atlas, functional parcellation, small-worldness, node degree, default mode network, frontoparietal network, limbic network, within-subjects design
- MeSH terms
- Brain, Brain Mapping, Emotions, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Memory, Short-Term, Rest, Reproducibility of Results, Young Adult
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