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Synchronization stability of epileptic brain network with higher-order interactions.

Zhaohui Li1,2, Chenlong Wang1, Mindi Li1

  • 1School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, China.

Chaos (Woodbury, N.Y.)
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Epilepsy research reveals brain network synchronization stability, not just strength, is key. Increased stability before seizure termination suggests a self-regulation mechanism, highlighting higher-order interactions in brain networks.

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Area of Science:

  • Neuroscience
  • Complex Systems
  • Computational Biology

Background:

  • Epilepsy is characterized by abnormal neuronal excitability and synchronization.
  • Previous research primarily focused on synchronization strength, neglecting synchronization stability in epileptic brain networks.
  • Understanding network dynamics is crucial for deciphering seizure mechanisms.

Purpose of the Study:

  • To introduce a novel hypergraph brain network (HGBN) model for analyzing epileptic brain synchronization.
  • To investigate the synchronization stability framework using a nonlinear coupled oscillation dynamic model (generalized Kuramoto model) in HGBNs.
  • To quantify synchronization stability and explore its relationship with seizure termination and brain network topology.

Main Methods:

  • Construction of hypergraph brain networks (HGBNs) based on phase synchronization.
  • Application of the synchronization stability framework from the generalized Kuramoto model.
  • Quantification of synchronization stability via eigenvalue spectrum of the higher-order Laplacian matrix in HGBNs.

Main Results:

  • Synchronization stability slightly decreased in early seizure stages but significantly increased before seizure termination.
  • Variations in synchronization stability correlate with topological changes in epileptogenic zones (EZs).
  • Higher-order interactions were verified to enhance the synchronization stability of HGBNs.

Conclusions:

  • The study validates the synchronization stability framework for HGBNs in epilepsy research.
  • Increased synchronization stability prior to seizure termination suggests an emergency self-regulation mechanism.
  • Higher-order interactions and epileptogenic zone topology play significant roles in epileptic seizure termination.