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Hyperbolic disc embedding of functional human brain connectomes using resting-state fMRI
Wonseok Whi1,2, Seunggyun Ha3, Hyejin Kang4
1Department of Molecular Medicine and Biopharmaceutical Sciences, Seoul National University, Seoul, South Korea.
Network Neuroscience (Cambridge, Mass.)
|January 6, 2023
Summary
Researchers mapped complex brain networks onto hyperbolic geometry, finding the hyperbolic disc best represents brain function. This novel approach aids in detecting neurological anomalies like autism spectrum disorder.
Area of Science:
- Neuroscience
- Network Science
- Computational Geometry
Background:
- The brain exhibits complex network properties like modularity, small-worldness, and hierarchy.
- These characteristics align with principles of non-Euclidean geometry.
- Understanding brain network topology is crucial for neuroscience.
Purpose of the Study:
- To represent functional brain networks using non-Euclidean geometry.
- To develop a novel framework for visualizing and analyzing brain network structures.
- To identify potential biomarkers for neurological disorders using network analysis.
Main Methods:
- Constructed scale-free binary graphs from resting-state functional magnetic resonance imaging (rs-fMRI) data.
- Utilized internodal time series correlation as a proximity measure.
- Embedded functional brain networks onto hyperbolic manifolds using the ๐ยน/โยฒ model.
Main Results:
- Functional brain networks are optimally represented in two-dimensional hyperbolic space (hyperbolic disc).
- The hyperbolic embedding preserved network fidelity (low distortion, high precision).
- Hyperbolic distance analysis successfully detected network anomalies in individuals with autism spectrum disorder.
Conclusions:
- Hyperbolic geometry provides a powerful framework for studying functional brain networks.
- This embedding method allows for efficient visualization and analysis of brain connectivity.
- The approach offers a reliable tool for detecting individual-scale network anomalies, with potential applications in diagnosing neurological conditions.
