ArticleMethodsX2020
Dynamic Functional Connectivity as a complex random walk: Definitions and the dFCwalk toolbox.
Article in MethodsX, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Arousal-driven critical roaming reproduces human functional connectivity dynamics.PLoS biology · 2026Article
- Phase-dependent stimulation response is shaped by the brain's dynamic functional connectivity.Network neuroscience (Cambridge, Mass.) · 2026Article
- A lightweight, end-to-end explainable, and generalized attention-based graph neural network model trained on high-order spatiotemporal organization of dynamic functional connectivity to classify autistics from typically developing.Network neuroscience (Cambridge, Mass.) · 2025Article
- Dynamicity of brain network organization & their community architecture as characterizing features for classification of common mental disorders from whole-brain connectome.Translational psychiatry · 2024Article
- Viscous dynamics associated with hypoexcitation and structural disintegration in neurodegeneration via generative whole-brain modeling.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- EiDA: A lossless approach for dynamic functional connectivity; application to fMRI data of a model of ageing.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- White-matter degradation and dynamical compensation support age-related functional alterations in human brain.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- State-switching and high-order spatiotemporal organization of dynamic functional connectivity are disrupted by Alzheimer's disease.Network neuroscience (Cambridge, Mass.) · 2023Article
- Structure-function clustering in weighted brain networks.Scientific reports · 2022Article
- Feature Extraction of the Brain's Dynamic Complex Network Based on EEG and a Framework for Discrimination of Pediatric Epilepsy.Sensors (Basel, Switzerland) · 2022Article
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Authors and funding
6 authors.
Funding
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Abstract
•We have developed a framework to describe the dynamics of Functional Connectivity (dFC) estimated from brain activity time-series as a complex random walk in the space of possible functional networks. This conceptual and methodological framework considers dFC as a smooth reconfiguration process, combining "liquid" and "coordinated" aspects. Unlike other previous approaches, our method does not require the explicit extraction of discrete connectivity states.•In our previous work, we introduced several metrics for the quantitative characterization of the dFC random walk. First, dFC speed analyses extract the distribution of the time-resolved rate of reconfiguration of FC along time. These distributions have a clear peak (typical dFC speed, that can already serve as a biomarker) and fat tails (denoting deviations from Gaussianity that can be detected by suitable scaling analyses of FC network streams). Second, meta-connectivity (MC) analyses identify groups of functional links whose fluctuations co-vary in time and that define veritable dFC modules organized along specific dFC meta-hub controllers (differing from conventional FC modules and hubs). The decomposition of whole-brain dFC by MC allows performing dFC speed analyses separately for each of the detected dFC modules.•We present here blocks and pipelines for dFC random walk analyses that are made easily available through a dedicated MATLAB
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