Cited by 66Functional Brain Connectivity StudiesAdvanced Neuroimaging Techniques and ApplicationsAdvanced MRI Techniques and Applications

Neurometrics of intrinsic connectivity networks at rest using fMRI: retest reliability and cross-validation using a meta-level method

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Wisner, Krista M., Atluri, Gowtham, Lim, Kelvin O., MacDonald, Angus W.·2013·NeuroImage

Abstract

Functional images of the resting brain can be empirically parsed into intrinsic connectivity networks (ICNs) which closely resemble patterns of evoked task-based brain activity and which have a biological and genetic basis. Recently, ICNs have become popular for investigating brain functioning and brain-behavior relationships. However, the replicability and neurometrics of these networks are only beginning to be reported. Using a meta-level independent component analysis (ICA), we produced ICNs from three data sets collected from two samples of healthy adults. The ICNs from our data sets demonstrated robust and independent replication of 12 intrinsic networks that reflected 17 canonical, task-based, brain networks. We found within-subject reliability of ICNs was modest overall, but ranged from poor to good, and that voxels with the highest measured connectivity rarely had the highest reliability. Networks associated with executive functions, visuospatial reasoning, motor coordination, speech and audition, default mode, vision, and interoception showed moderate to high group-level reproducibility and replicability. However, only the first four of these networks also showed fair or better within-subject reliability over time. Our findings highlight the replicability of ICNs across data sets, the range of within-subject neurometrics across different networks, and the shared characteristics between resting and task-based networks.

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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).”

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Authors
Wisner, K. M., Atluri, G., Lim, K. O., & MacDonald, A. W.
Affiliations
University of Minnesota (US)
Corresponding author
MacDonald, Angus W.
Venue
NeuroImage
Publisher
Elsevier BV
Published
2013-08
Volume
76
Pages
236-251
ISSN
1053-8119 (ISSN-L)
OpenAlex
W2052993482
Cited by
66
References
83
Citations by year
2026: 2 · 2025: 4 · 2024: 1 · 2023: 1 · 2021: 3 · 2020: 7 · 2019: 6 · 2018: 6 · 2017: 9 · 2016: 7 · 2015: 6 · 2014: 10 · 2013: 3
FWCI
0.74
Type
journal article
Language
en
Open access
Locations
  • NeuroImage (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • NIMH (R01MH060662, 5T32MH017069-29)
  • NIDA (R01MH084861, R21MH079262)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
Keywords
resting-state networks, resting-state brain activity, test-retest reliability, cross-validation, neurometrics, default mode network, interoception, visuospatial reasoning
MeSH terms
Adolescent, Adult, Biometry, Brain, Brain Mapping, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Neural Pathways, Rest, Reproducibility of Results, Young Adult

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