ArticleNeuroImage2022
BOLD cofluctuation 'events' are predicted from static functional connectivity.
Article in NeuroImage, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
27 citing papers in PubMed, 35 citations in OpenAlex.
- Human cortex organizes dynamic co-fluctuations along the sensorimotor-association axis.Nature communications · 2026Article
- The dual interpretation of edge time series: Time-varying connectivity versus statistical interaction.iScience · 2026Article
- System identification and surrogate data analyses imply approximate Gaussianity and non-stationarity of resting-brain dynamics.bioRxiv : the preprint server for 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
- Intrinsic ion dynamics underlies the temporal nature of resting-state functional connectivity.bioRxiv : the preprint server for biology · 2025Article
- Switching Patterns of Cortical-Subcortical Interaction in the Human Brain.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Temporal variability of brain-behavior relationships in fine-scale dynamics of edge time series.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Human brain state dynamics are highly reproducible and associated with neural and behavioral features.PLoS biology · 2024Article
- Estimation of static and dynamic functional connectivity in resting-state fMRI using zero-frequency resonator.Human brain mapping · 2024Article
- Human brain state dynamics reflect individual neuro-phenotypes.bioRxiv : the preprint server for biology · 2024Article
- Modular subgraphs in large-scale connectomes underpin spontaneous co-fluctuation events in mouse and human brains.Communications biology · 2024Article
- Article
- Dynamic functional connectivity to tile the spatiotemporal mosaic of brain states.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Challenges in the measurement and interpretation of dynamic functional connectivity.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Dynamic network characteristics of adolescents with major depressive disorder: Attention network mediates the association between anhedonia and attentional deficit.Human brain mapping · 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
- Static and dynamic functional connectomes represent largely similar information.bioRxiv : the preprint server for biology · 2023Article
- A spatiotemporal complexity architecture of human brain activity.Science advances · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
Abstract
Recent work identified single time points ("events") of high regional cofluctuation in functional Magnetic Resonance Imaging (fMRI) which contain more large-scale brain network information than other, low cofluctuation time points. This suggested that events might be a discrete, temporally sparse signal which drives functional connectivity (FC) over the timeseries. However, a different, not yet explored possibility is that network information differences between time points are driven by sampling variability on a constant, static, noisy signal. Using a combination of real and simulated data, we examined the relationship between cofluctuation and network structure and asked if this relationship was unique, or if it could arise from sampling variability alone. First, we show that events are not discrete - there is a gradually increasing relationship between network structure and cofluctuation; ∼50% of samples show very strong network structure. Second, using simulations we show that this relationship is predicted from sampling variability on static FC. Finally, we show that randomly selected points can capture network structure about as well as events, largely because of their temporal spacing. Together, these results suggest that, while events exhibit particularly strong representations of static FC, there is little evidence that events are unique timepoints that drive FC structure. Instead, a parsimonious explanation for the data is that events arise from a single static, but noisy, FC structure.
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What OpenQuestion holds
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.