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Characterizing Complex Networks Using Entropy-Degree Diagrams: Unveiling Changes in Functional Brain Connectivity
Aline Viol1,2, Fernanda Palhano-Fontes3, Heloisa Onias3
1Institute of Theoretical Physics, Technische Universität Berlin, Hardenbergstraße 36, 10623 Berlin, Germany.
Entropy (Basel, Switzerland)
|December 3, 2020
Summary
We introduce geodesic entropy, a new network metric, to analyze brain connectivity. This metric reveals altered brain network patterns after Ayahuasca consumption, indicating changes in consciousness states.
Area of Science:
- Neuroscience
- Network Science
- Complexity Science
Background:
- Understanding human brain functional connectivity is crucial for neuroscience.
- Existing network metrics may not fully capture complex network influences on individual nodes.
- Characterizing network structure provides insights into emergent behaviors like sustained activity.
Purpose of the Study:
- To introduce a novel network metric, geodesic entropy, for analyzing functional connectivity.
- To quantify the influence on a specific node based on overall network structure.
- To investigate the effects of Ayahuasca on human brain functional connectivity.
Main Methods:
- Developed the geodesic entropy metric, quantifying Shannon entropy of distance distributions to a node.
- Applied the metric to functional brain network data from individuals in resting state.
- Compared brain network structures in ordinary consciousness versus Ayahuasca-altered states.
Main Results:
- Geodesic entropy successfully differentiated between ordinary and Ayahuasca-altered states of consciousness.
- Functional brain networks in the Ayahuasca-altered state exhibited higher average geodesic entropy.
- The findings suggest significant alterations in brain network organization under Ayahuasca.
Conclusions:
- Geodesic entropy is a valuable tool for characterizing network influences and understanding brain states.
- This metric offers new insights into the neurobiological effects of psychedelic substances.
- The study highlights the potential of geodesic entropy for analyzing diverse empirical networks.

