ArticleNetwork neuroscience (Cambridge, Mass.)2022
Hyperbolic disc embedding of functional human brain connectomes using resting-state fMRI.
Article in Network neuroscience (Cambridge, Mass.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 15 citations in OpenAlex.
- Altered cortical activation and functional connectivity during fixed phrase verbal fluency in children with autism spectrum disorder.Frontiers in psychiatry · 2026Article
- Integral Betti signatures of brain, climate and financial networks compared to hyperbolic, Euclidean and spherical models.Scientific reports · 2025Article
- Interaction of Functional Brain Networks Is Associated With k-Clique Percolation in the Human Structural Connectome.Human brain mapping · 2025Article
- Geometric representations of brain networks can predict the surgery outcome in temporal lobe epilepsy.NPJ systems biology and applications · 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
- Big Data Analytics for Uncovering Voxel Connectivity Patterns in Attention Deficit Hyperactivity Disorder.Journal of multidisciplinary healthcare · 2025Article
- On null models for temporal small-worldness in brain dynamics.Network neuroscience (Cambridge, Mass.) · 2024Article
- Characteristic functional cores revealed by hyperbolic disc embedding and k-core percolation on resting-state fMRI.Scientific reports · 2022Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The brain presents a real complex network of modular, small-world, and hierarchical nature, which are features of non-Euclidean geometry. Using resting-state functional magnetic resonance imaging, we constructed a scale-free binary graph for each subject, using internodal time series correlation of regions of interest as a proximity measure. The resulting network could be embedded onto manifolds of various curvatures and dimensions. While maintaining the fidelity of embedding (low distortion, high mean average precision), functional brain networks were found to be best represented in the hyperbolic disc. Using the 𝕊
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