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Related Experiment Video

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Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

Shapley ratings in brain networks.

Rolf Kötter1, Andrew T Reid, Antje Krumnack

  • 1Department of Cognitive Neuroscience, Radboud University Nijmegen Medical Centre The Netherlands.

Frontiers in Neuroinformatics
|November 1, 2008
PubMed
Summary

This study applies graph and game theory, specifically the Shapley value, to analyze brain network connectivity. Results show Shapley values correlate with network centrality and density, indicating brain network resilience.

Keywords:
cerebral cortexconnectivitygame theorygraph analysisneural network

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Area of Science:

  • Neuroscience
  • Network Science
  • Graph Theory
  • Game Theory

Background:

  • Growing interest in analyzing brain connectivity patterns due to advances in network theory and empirical brain data.
  • Need for novel techniques to analyze large-scale brain connectivity networks.

Purpose of the Study:

  • To explore the application of graph and game theory concepts for analyzing brain network connectivity.
  • To utilize the Shapley value principle to assess individual brain structure contributions to global connectivity.

Main Methods:

  • Treated individual brain structures as nodes in a directed graph model.
  • Applied the Shapley value principle to quantify nodal contributions within prefrontal and visual cortical networks.
  • Compared Shapley values with existing nodal measures like betweenness centrality and connection density.

Main Results:

  • Shapley values were reported for prefrontal and visual cortical networks, highlighting nodes with significant contributions.
  • A strong correlation was found between Shapley values and betweenness centrality/connection density.
  • Betweenness centrality alone explained approximately 79% of the variance in Shapley values for random networks.

Conclusions:

  • The Shapley value is a valuable measure for characterizing the organization and functional role of brain networks.
  • Brain networks demonstrate significant structural resistance to local lesions.
  • This approach offers novel insights into brain network organization and resilience.