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Advanced Technical IVT

graph theory metrics

Mathematical measures characterizing network topology and organization properties.

Full Definition

Graph theory metrics are mathematical measures used to characterize the topological properties of brain networks represented as graphs, where nodes represent brain regions and edges represent connections between them. Common metrics include clustering coefficient (measuring local connectivity), path length (measuring integration), betweenness centrality (identifying hub regions), and modularity (detecting community structure). These metrics provide quantitative frameworks for understanding brain network organization in health and disease. Graph theory analysis has revealed fundamental principles of brain network architecture, including small-world properties, rich-club organization, and hierarchical modularity that support efficient neural communication.

Usage

Usage note: Use plural form 'metrics' when referring to multiple measures; be specific about which metrics are computed.

In Context

  • "Graph theory metrics revealed altered small-world properties in the patient group." — Network neuroscience study results
  • "Betweenness centrality was computed to identify hub regions in the functional connectome." — Brain network analysis methods

Also known as

network measures topological metrics connectivity metrics

Don't confuse with

connectivity strength correlation measures statistical metrics

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