ArticleNetwork neuroscience (Cambridge, Mass.)2025
Test-retest reliability of dynamic functional connectivity parameters for a two-state model.
Article in Network neuroscience (Cambridge, Mass.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Changes in resting-state functional connectivity linked to affective symptoms: insights from a population-based study of adolescents and young adults.Translational psychiatry · 2026Article
- Sex differences in dynamic and static measures of brain integration derived from resting-state functional magnetic resonance imaging.Biology of sex differences · 2026Article
- Test-retest reliability of dynamic functional connectivity parameters for a two-state model.Network neuroscience (Cambridge, Mass.) · 2025Article
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Abstract
Reliability of imaging parameters is of pivotal importance for further correlation analyses. Here, we investigated the test-retest reliability of two dynamic functional connectivity (dFC) brain states and related parameters for different scan length, atlases with 116 versus 442 regions, and data centering in 23 participants and reproduced the findings in 501 subjects of the Human Connectome Project. Results showed an integrated and a segregated brain state with high intraclass correlation coefficient (ICC) values of the states between sessions (0.67 ≥ ICC ≥ 0.99). The most reliable dFC parameter was state prevalence with an ICC ≈ 0.5 for ∼15 min of uncentered data, while other parameters, such as mean dwell time, were much less reliable. While shorter scans and within-subject data centering further reduce reliability, the atlas choice had no effects. Spearman's correlations among dFC parameters strongly depend on data centering. The effect of global signal regression and a higher number of states is discussed. In conclusion, we recommend formulating hypotheses on cross-sectional differences and correlations between dFC measures of brain integration and other subject-specific measures in terms of state prevalence, especially in small-scale studies.
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