ArticleNetwork neuroscience (Cambridge, Mass.)2023
Static and dynamic fMRI-derived functional connectomes represent largely similar information.
Article in Network neuroscience (Cambridge, Mass.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed.
- Temporal stability of functional network configurations and its relationship to cognition and psychopathology in early psychoses.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026Article
- Static and dynamic intracerebral signal analysis reveals protective networks against seizures in drug-resistant focal epilepsy.Brain communications · 2026Article
- QuNex Recipes: Executable, Human-Readable Workflows for Reproducible Neuroimaging Research.bioRxiv : the preprint server for biology · 2025Article
- Both k-core percolation and directed graph analysis revealed succession and transition of voxels' spatiotemporal progress on dynamic correlation resting-state fMRI.Frontiers in human neuroscience · 2025Article
- Multilayer network analysis across cortical depths in 7-T resting-state fMRI.Network neuroscience (Cambridge, Mass.) · 2025Article
- Tell me why: A scoping review on the fundamental building blocks of fMRI-based network analysis.NeuroImage. Clinical · 2025Article
- Multilayer Network Analysis across Cortical Depths in Resting-State 7T fMRI.bioRxiv : the preprint server for biology · 2024Article
- Tai Chi Practice Buffers Aging Effects in Functional Brain Connectivity.Brain sciences · 2024Article
- Strategies for motion- and respiration-robust estimation of fMRI intrinsic neural timescales.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- The impact of functional correlations on task information coding.Network neuroscience (Cambridge, Mass.) · 2024Article
- Neuroplastic changes induced by long-termFrontiers in neuroscience · 2024Article
- Challenges in the measurement and interpretation of dynamic functional connectivity.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- QuNex recipes: Executable, human-readable workflows for reproducible neuroimaging research.Imaging neuroscience (Cambridge, Mass.)Article
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4 authors.
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Abstract
Functional connectivity (FC) of blood oxygen level-dependent (BOLD) fMRI time series can be estimated using methods that differ in sensitivity to the temporal order of time points (static vs. dynamic) and the number of regions considered in estimating a single edge (bivariate vs. multivariate). Previous research suggests that dynamic FC explains variability in FC fluctuations and behavior beyond static FC. Our aim was to systematically compare methods on both dimensions. We compared five FC methods: Pearson's/full correlation (static, bivariate), lagged correlation (dynamic, bivariate), partial correlation (static, multivariate), and multivariate AR model with and without self-connections (dynamic, multivariate). We compared these methods by (i) assessing similarities between FC matrices, (ii) by comparing node centrality measures, and (iii) by comparing the patterns of brain-behavior associations. Although FC estimates did not differ as a function of sensitivity to temporal order, we observed differences between the multivariate and bivariate FC methods. The dynamic FC estimates were highly correlated with the static FC estimates, especially when comparing group-level FC matrices. Similarly, there were high correlations between the patterns of brain-behavior associations obtained using the dynamic and static FC methods. We conclude that the dynamic FC estimates represent information largely similar to that of the static FC.
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