• Syu-Jyun Peng, Chien-Chen Chou, Hsiang-Yu Yu, Chien Chen, Der-Jen Yen, Shang-Yeong Kwan, HsuSanford P CSPC4Neurosurgery, Neurological Institute, Taipei Veterans General Hospital; and.5School of Medicine, National Yang-Ming University, Taipei, Taiwan., Chun-Fu Lin, Hsin-Hung Chen, and Cheng-Chia Lee.
• 1Biomedical Electronics Translational Research Center and.
• J. Neurosurg. 2019 Oct 1; 131 (4): 108611941086-1194.

ObjectiveIn this study, the authors investigated high-frequency oscillation (HFO) networks during seizures in order to determine how HFOs spread from the focal cerebral cortex and become synchronized across various areas of the brain.MethodsAll data were obtained from stereoelectroencephalography (SEEG) signals in patients with drug-resistant temporal lobe epilepsy (TLE). The authors calculated intercontact cross-coefficients between all pairs of contacts to construct HFO networks in 20 seizures that occurred in 5 patients. They then calculated HFO network topology metrics (i.e., network density and component size) after normalizing seizure duration data by dividing each seizure into 10 intervals of equal length (labeled I1-I10).ResultsFrom the perspective of the dynamic topologies of cortical and subcortical HFO networks, the authors observed a significant increase in network density during intervals I5-I10. A significant increase was also observed in overall energy during intervals I3-I8. The results of subnetwork analysis revealed that the number of components continuously decreased following the onset of seizures, and those results were statistically significant during intervals I3-I10. Furthermore, the majority of nodes were connected to a single dominant component during the propagation of seizures, and the percentage of nodes within the largest component grew significantly until seizure termination.ConclusionsThe consistent topological changes that the authors observed suggest that TLE is affected by common epileptogenic patterns. Indeed, the findings help to elucidate the epileptogenic network that characterizes TLE, which may be of interest to researchers and physicians working to improve treatment modalities for epilepsy, including resection, cortical stimulation, and neuromodulation treatments that are responsive to network topologies.

5 keywords...

hide…