Reliable intrinsic connectivity networks: test-retest evaluation using ICA and dual regression approach
Open accessAbstract
Functional connectivity analyses of resting-state fMRI data are rapidly emerging as highly efficient and powerful tools for in vivo mapping of functional networks in the brain, referred to as intrinsic connectivity networks (ICNs). Despite a burgeoning literature, researchers continue to struggle with the challenge of defining computationally efficient and reliable approaches for identifying and characterizing ICNs. Independent component analysis (ICA) has emerged as a powerful tool for exploring ICNs in both healthy and clinical populations. In particular, temporal concatenation group ICA (TC-GICA) coupled with a back-reconstruction step produces participant-level resting state functional connectivity maps for each group-level component. The present work systematically evaluated the test-retest reliability of TC-GICA derived RSFC measures over the short-term (<45 min) and long-term (5-16 months). Additionally, to investigate the degree to which the components revealed by TC-GICA are detectable via single-session ICA, we investigated the reproducibility of TC-GICA findings. First, we found moderate-to-high short- and long-term test-retest reliability for ICNs derived by combining TC-GICA and dual regression. Exceptions to this finding were limited to physiological- and imaging-related artifacts. Second, our reproducibility analyses revealed notable limitations for template matching procedures to accurately detect TC-GICA based components at the individual scan level. Third, we found that TC-GICA component's reliability and reproducibility ranks are highly consistent. In summary, TC-GICA combined with dual regression is an effective and reliable approach to exploratory analyses of resting state fMRI data.
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Brain function is largely determined by genes and is relatively stable within and across adolescence and adulthood.
“brain function is also largely determined by genes and is relatively stable within and across adolescence and adulthood (Manuck et al., 2007; Caceres et al., 2009; Zuo et al., 2010; Koolschijn et al., 2011)”
From Neural Activation to Parental Praise Interacts With Social Context to Predict Adolescent Depressive Symptoms (2019) · cites this paper as Zuo et al., 2010
Results §3.2 reports moderate-to-high test–retest reliability for some functional networks, supporting a limited claim of stability. Methods §§2.1 and 2.7 show that the study followed 26 participants (mean age 20.5 years) for 5–16 months; it does not establish stability across adolescence and adulthood or that brain function is largely determined by genes. (LLM, conf=0.88)
Experimental — accuracy not yet measuredDual regression is a reliable technique which allows for the identification of group differences in the spatial and temporal features of ICNs common to the entire sample.
“Dual regression is a reliable technique which allows for the identification of group differences in the spatial and temporal features of ICNs common to the entire sample (Filippini et al., 2009; Zuo et al., 2010).”
From Investigating functional brain network integrity using a traditional and novel categorical scheme for neurodevelopmental disorders (2019) · cites this paper as Zuo et al., 2010
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 Zuo et al., 2010
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Flagged first, then by citations
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- Authors
- Zuo, X.-N., Kelly, C., Adelstein, J. S., Klein, D. F., Castellanos, F. X., & Milham, M. P.
- Affiliations
- New York University (US)
- Nathan Kline Institute for Psychiatric Research (US)
- Corresponding author
- Milham, Michael P.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2010-02
- Volume
- 49
- Issue
- 3
- Pages
- 2163-2177
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC2877508
- OpenAlex
- W2107360535
- Cited by
- 744
- References
- 87
- Citations by year
- 2026: 6 · 2025: 12 · 2024: 26 · 2023: 28 · 2022: 33 · 2021: 54 · 2020: 32 · 2019: 50 · 2018: 55 · 2017: 67 · 2016: 47 · 2015: 77 · 2014: 62 · 2013: 65 · 2012: 57
- FWCI
- 20.72
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- NIMH (R01MH081218)
- 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, resting-state functional connectivity, test-retest reliability, dual regression, reproducibility, template matching, resting-state fMRI, independent component analysis
- MeSH terms
- Brain, Brain Mapping, Female, Humans, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Male, Neural Pathways, Reproducibility of Results, Principal Component Analysis, Young Adult
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