ArticleCerebral cortex (New York, N.Y. : 1991)2023
Uncovering individual differences in fine-scale dynamics of functional connectivity.
Article in Cerebral cortex (New York, N.Y. : 1991), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
19 citing papers in PubMed.
- Human cortex organizes dynamic co-fluctuations along the sensorimotor-association axis.Nature communications · 2026Article
- Resting fMRI functional connectivity reflects fluctuations in inhibitory interneuron activity.bioRxiv : the preprint server for biology · 2026Article
- The dual interpretation of edge time series: Time-varying connectivity versus statistical interaction.iScience · 2026Article
- Using connectome-based predictive models to reveal the systems standardized tests and clinical symptoms are reflecting.Nature communications · 2026Article
- Connectome-based predictive modeling of concurrent and longitudinal substance use vulnerability in adolescence.Developmental cognitive neuroscience · 2026Article
- Individual identifiability following Procrustes alignment of functional gradients: effect of subspace dimensionality.Communications biology · 2026Article
- The individuality of single-frame functional brain connectivity.bioRxiv : the preprint server for biology · 2026Article
- Variation in high-amplitude events across the human lifespan.Network neuroscience (Cambridge, Mass.) · 2026Article
- Cortical representational geometry of diverse tasks reveals subject-specific and subject-invariant cognitive structures.Communications biology · 2025Article
- Time-varying synergy/redundancy dominance in the human cerebral cortex.Journal of physics. Complexity · 2025Article
- Temporal variability of brain-behavior relationships in fine-scale dynamics of edge time series.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Time-resolved instantaneous functional loci estimation (TRIFLE): Estimating time-varying allocation of spatially overlapping sources in functional magnetic resonance imaging.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Edge time series components of functional connectivity and cognitive function in Alzheimer's disease.Brain imaging and behavior · 2024Article
- Modular subgraphs in large-scale connectomes underpin spontaneous co-fluctuation events in mouse and human brains.Communications biology · 2024Article
- Edge Time Series Components of Functional Connectivity and Cognitive Function in Alzheimer's Disease.medRxiv : the preprint server for health sciences · 2023Article
- Living on the edge: network neuroscience beyond nodes.Trends in cognitive sciences · 2023Review
- Intermediately synchronised brain states optimise trade-off between subject specificity and predictive capacity.Communications biology · 2023Article
- Synchronous high-amplitude co-fluctuations of functional brain networks during movie-watching.Imaging neuroscience (Cambridge, Mass.) · 2023Article
- The individuality of single-frame functional brain connectivity.Imaging neuroscience (Cambridge, Mass.)Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Functional connectivity (FC) profiles contain subject-specific features that are conserved across time and have potential to capture brain-behavior relationships. Most prior work has focused on spatial features (nodes and systems) of these FC fingerprints, computed over entire imaging sessions. We propose a method for temporally filtering FC, which allows selecting specific moments in time while also maintaining the spatial pattern of node-based activity. To this end, we leverage a recently proposed decomposition of FC into edge time series (eTS). We systematically analyze functional magnetic resonance imaging frames to define features that enhance identifiability across multiple fingerprinting metrics, similarity metrics, and data sets. Results show that these metrics characteristically vary with eTS cofluctuation amplitude, similarity of frames within a run, transition velocity, and expression of functional systems. We further show that data-driven optimization of features that maximize fingerprinting metrics isolates multiple spatial patterns of system expression at specific moments in time. Selecting just 10% of the data can yield stronger fingerprints than are obtained from the full data set. Our findings support the idea that FC fingerprints are differentially expressed across time and suggest that multiple distinct fingerprints can be identified when spatial and temporal characteristics are considered simultaneously.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.