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Phase Synchronization Dynamics of Neural Network during Seizures
1School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
Computational and Mathematical Methods in Medicine
|November 10, 2018
Summary
Brain network synchronization increases before seizure termination in epilepsy patients. Network state transitions do not appear to drive seizure evolution, suggesting synchronization plays a key role in ending seizures.
Area of Science:
- Neuroscience
- Epileptology
- Computational Neuroscience
Background:
- Epilepsy is viewed as a network disorder.
- Seizures arise from brain network reorganization and evolving synchronization.
- Understanding seizure dynamics is crucial for developing effective treatments.
Purpose of the Study:
- To investigate the role of brain network synchronization in seizure termination.
- To analyze transitions in brain network states during preseizure, seizure, and postseizure periods.
Main Methods:
- Phase synchronization analysis was performed on electrocorticogram (ECoG) data.
- Brain networks were constructed from ECoG signals of eleven refractory epilepsy patients.
Main Results:
- A significant increase in synchronization was observed preceding seizure termination.
- No significant differences were found in network state transitions between preseizure, seizure, and postseizure phases.
Conclusions:
- Increased synchronization may contribute to the termination of epileptic seizures.
- Network state transitions are unlikely to be the primary drivers of seizure evolution.
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