ArticleNetwork neuroscience (Cambridge, Mass.)2017
Visibility graphs for fMRI data: Multiplex temporal graphs and their modulations across resting-state networks.
Article in Network neuroscience (Cambridge, Mass.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 63 citations in OpenAlex.
- Localizing Synergies of Hidden Factors in Complex Systems: Resting Brain Networks and HeLa GeneExpression Profile as Case Studies.Entropy (Basel, Switzerland) · 2025Article
- Brain Mapping of Behavior Contagion Based on Visibility Graph Analysis of ERP Signals.Basic and clinical neuroscience · 2025Article
- Multilevel irreversibility reveals higher-order organization of nonequilibrium interactions in human brain dynamics.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Network Representation of fMRI Data Using Visibility Graphs: The Impact of Motion and Test-Retest Reliability.Neuroinformatics · 2024Article
- Visibility graph analysis for brain: scoping review.Frontiers in neuroscience · 2023Article
- Automated sleep state classification of wide-field calcium imaging data via multiplex visibility graphs and deep learning.Journal of neuroscience methods · 2022Article
- Visibility graph based temporal community detection with applications in biological time series.Scientific reports · 2021Article
- Horizontal visibility graph of a random restricted growth sequence.Advances in applied mathematics · 2021Article
- Network Analysis of Time Series: Novel Approaches to Network Neuroscience.Frontiers in neuroscience · 2021Review
- Estimation of Dynamic Bivariate Correlation Using a Weighted Graph Algorithm.Entropy (Basel, Switzerland) · 2020Article
- Timescales of spontaneous fMRI fluctuations relate to structural connectivity in the brain.Network neuroscience (Cambridge, Mass.) · 2020Article
- Decoding cortical brain states from widefield calcium imaging data using visibility graph.Biomedical optics express · 2018Article
- A combinatorial framework to quantify peak/pit asymmetries in complex dynamics.Scientific reports · 2018Article
- Sample entropy reveals an age-related reduction in the complexity of dynamic brain.Scientific reports · 2017Article
- A multiplex network approach for the analysis of intracranial pressure and heart rate data in traumatic brain injured patients.Applied network science · 2017Article
Corrections and comments
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Authors and funding
4 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Visibility algorithms are a family of methods that map time series into graphs, such that the tools of graph theory and network science can be used for the characterization of time series. This approach has proved a convenient tool, and visibility graphs have found applications across several disciplines. Recently, an approach has been proposed to extend this framework to multivariate time series, allowing a novel way to describe collective dynamics. Here we test their application to fMRI time series, following two main motivations, namely that (a) this approach allows vs to simultaneously capture and process relevant aspects of both local and global dynamics in an easy and intuitive way, and (b) this provides a suggestive bridge between time series and network theory that nicely fits the consolidating field of network neuroscience. Our application to a large open dataset reveals differences in the similarities of temporal networks (and thus in correlated dynamics) across resting-state networks, and gives indications that some differences in brain activity connected to psychiatric disorders could be picked up by this approach.
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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.