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Phase Synchronization Dynamics of Neural Network during Seizures.

Hao Liu¹, Puming Zhang¹

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.

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Electroconvulsive Seizures in Rats and Fractionation of Their Hippocampi to Examine Seizure-induced Changes in Postsynaptic Density Proteins

Electroconvulsive Seizures in Rats and Fractionation of Their Hippocampi to Examine Seizure-induced Changes in Postsynaptic Density Proteins

Published on: August 15, 2017

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.