ArticleCerebral cortex (New York, N.Y. : 1991)2024
Measures of resting-state brain network segregation and integration vary in relation to data quantity: implications for within and between subject comparisons of functional brain network organization.
Article in Cerebral cortex (New York, N.Y. : 1991), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Brain network dynamics reflect psychiatric illness status and transdiagnostic symptom profiles across health and disease.Nature communications · 2026Article
- Distance-related functional connectivity alterations in first-episode, drug-naïve major depressive disorder: a resting-state fMRI study with atlas-based neurotransmitter correlates.BMC psychiatry · 2026Article
- Correspondence of large-scale functional brain network decline across aging mice and humans.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Functional brain network connectivity patterns associated with midlife metabolic syndrome and cognitive vulnerabilities.Frontiers in aging neuroscience · 2026Article
- Pain-side-specific alteration of structural networks in trigeminal neuralgia: a connectome analysis.Frontiers in neuroscience · 2026Article
- Systematic fMRI signal differences across cohorts alter lifespan trajectories of functional brain networks.Imaging neuroscience (Cambridge, Mass.) · 2026Article
- Spatially convergent functional MRI signatures of diabetes and male sex identify genetic vulnerabilities to accelerated brain ageing.Brain communications · 2026Article
- Brain network segregation is associated with drug use severity in individuals with opioid use disorder.Drug and alcohol dependence · 2025Article
- Functional reconfiguration between rest and movie watching relates to theory-of-mind performance among young and older adults.Cerebral cortex (New York, N.Y. : 1991) · 2025Article
- Methods for Brain Connectivity Analysis with Applications to Rat Local Field Potential Recordings.Entropy (Basel, Switzerland) · 2025Article
- Variation in brain aging: A review and perspective on the utility of individualized approaches to the study of functional networks in aging.Neurobiology of aging · 2025Review
- Age- and Sex-Specific Patterns in Adult Brain Network Segregation.Human brain mapping · 2025Article
- Segregation of three resting-state brain networks predicts reappraisal success across the lifespan.Social cognitive and affective neuroscience · 2025Article
- Reproducibility of resting-state functional connectivity in healthy aging and brain injury: A mini-multiverse analysis.Network neuroscience (Cambridge, Mass.) · 2025Article
- Review
- Resting-state functional network segregation of the default mode network predicts valence bias across the lifespan.Imaging neuroscience (Cambridge, Mass.) · 2024Article
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6 authors.
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Abstract
Measures of functional brain network segregation and integration vary with an individual's age, cognitive ability, and health status. Based on these relationships, these measures are frequently examined to study and quantify large-scale patterns of network organization in both basic and applied research settings. However, there is limited information on the stability and reliability of the network measures as applied to functional time-series; these measurement properties are critical to understand if the measures are to be used for individualized characterization of brain networks. We examine measurement reliability using several human datasets (Midnight Scan Club and Human Connectome Project [both Young Adult and Aging]). These datasets include participants with multiple scanning sessions, and collectively include individuals spanning a broad age range of the adult lifespan. The measurement and reliability of measures of resting-state network segregation and integration vary in relation to data quantity for a given participant's scan session; notably, both properties asymptote when estimated using adequate amounts of clean data. We demonstrate how this source of variability can systematically bias interpretation of differences and changes in brain network organization if appropriate safeguards are not included. These observations have important implications for cross-sectional, longitudinal, and interventional comparisons of functional brain network organization.
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