One-year test-retest reliability of intrinsic connectivity network fMRI in older adults
Open accessAbstract
"Resting-state" or task-free fMRI can assess intrinsic connectivity network (ICN) integrity in health and disease, suggesting a potential for use of these methods as disease-monitoring biomarkers. Numerous analytical options are available, including model-driven ROI-based correlation analysis and model-free, independent component analysis (ICA). High test-retest reliability will be a necessary feature of a successful ICN biomarker, yet available reliability data remains limited. Here, we examined ICN fMRI test-retest reliability in 24 healthy older subjects scanned roughly one year apart. We focused on the salience network, a disease-relevant ICN not previously subjected to reliability analysis, as well as the default mode network. Most ICN analytical methods proved reliable (intraclass coefficients>0.4) and were further improved by wavelet analysis. Seed-based ROI correlation analysis showed high scan-wise reliability, whereas graph theoretical analysis and temporal concatenation group ICA proved most reliable at the individual unit-wise level (voxels, ROIs). Including global signal regression in ROI-based correlation analyses reduced reliability. Our study provides a direct comparison between the most commonly used ICN fMRI methods and potential guidelines for measuring intrinsic connectivity in aging control and patient populations over time.
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Recent studies of test-retest reproducibility for time-concatenated ICA of resting state fMRI indicate very good reproducibility when resting state sessions are performed within one year of each other.
“Several recent studies of testretest reproducibility for time-concatenated ICA (i.e., our ICA method in this study) of resting state fMRI, however, indicate very good reproducibility when the resting state sessions are performed within one year of each other [Guo et al., 2012;Meindl et al., 2010;Zuo et al., 2010].”
From Specific default mode subnetworks support mentalizing as revealed through opposing network recruitment by social and semantic FMRI tasks: Mentalizing and Default-Mode Subnetworks (2015) · cites this paper as Guo et al., 2012
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- Authors
- Guo, C. C., Kurth, F., Zhou, J., Mayer, E. A., Eickhoff, S. B., Kramer, J. H., & Seeley, W. W.
- Affiliations
- University of California, San Francisco (US)
- University of California, Los Angeles (US)
- Forschungszentrum Jülich (DE)
- Corresponding author
- Seeley, William W.
- ORCID
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2012-07
- Volume
- 61
- Issue
- 4
- Pages
- 1471-1483
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC4226138
- OpenAlex
- W2060759363
- Cited by
- 252
- References
- 57
- Citations by year
- 2026: 7 · 2025: 4 · 2024: 7 · 2023: 13 · 2022: 16 · 2021: 29 · 2020: 15 · 2019: 23 · 2018: 18 · 2017: 31 · 2016: 17 · 2015: 27 · 2014: 20 · 2013: 23 · 2012: 2
- FWCI
- 11.80
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- JuSER (Forschungszentrum Jülich) (submittedVersion)
- Funders
- Larry L. Hillblom Foundation
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- resting-state networks, test-retest reliability, resting-state fMRI, older adults, aging, salience network, default mode network, independent component analysis, graph theory, wavelet analysis, global signal regression, biomarkers
- MeSH terms
- Aged, Aged, 80 and over, Aging, Brain, Brain Mapping, Female, Humans, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Male, Neural Pathways, Reproducibility of Results
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