Dynamic Network Connectivity Analysis to Identify Epileptogenic Zones Based on Stereo-Electroencephalography.
Objectives:Accurate localization of epileptogenic zones (EZs) is essential for successful surgical treatment of refractory focal epilepsy. The aim of the present study is to investigate whether a dynamic network connectivity analysis based on stereo-electroencephalography (SEEG) signals is effective in localizing EZs.Methods:SEEG data were recorded from seven patients who underwent presurgical evaluation for the treatment of refractory focal epilepsy and for whom the subsequent resective surgery gave a good outcome. A time-variant multivariate autoregressive model was constructed using a Kalman filter, and the time-variant partial directed coherence was computed. This was then used to construct a dynamic directed network model of the epileptic brain. Three graph measures (in-degree, out-degree, and betweenness centrality) were used to analyze the characteristics of the dynamic network and to find the important nodes in it.Results:In all seven patients, the indicative EZs localized by the in-degree and the betweenness centrality were highly consistent with the clinically diagnosed EZs. However, the out-degree did not indicate any significant differences between nodes in the network.Conclusions:In this work, a method based on ictal SEEG signals and effective connectivity analysis localized EZs accurately. The results suggest that the in-degree and betweenness centrality may be better network characteristics to localize EZs than the out-degree.
School of Biomedical Engineering, Shanghai Jiao Tong University Shanghai, China.
Jun-Wei
JW
Mao
Department of Functional Neurosurgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University Shanghai, China.
Xiao-Lai
XL
Ye
School of Biomedical Engineering, Shanghai Jiao Tong University Shanghai, China.
Yong-Hua
YH
Li
School of Biomedical Engineering, Shanghai Jiao Tong University Shanghai, China.
Pei-Ji
PJ
Liang
Department of Functional Neurosurgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University Shanghai, China.
Ji-Wen
JW
Xu
School of Biomedical Engineering, Shanghai Jiao Tong University Shanghai, China.
Pu-Ming
PM
Zhang
Kalman filter; epileptogenic zones; graph theory; stereo-EEG; time-variant partial directed coherence