Yang Zecheng, Fan Denggui, Wang Qingyun, Luan Guoming
School of Mathematics and Physics, University of Science and Technology Beijing, Beijing, 100083 China.
Department of Dynamics and Control, Beihang University, Beijing, 100191 China.
Cogn Neurodyn. 2021 Aug;15(4):649-659. doi: 10.1007/s11571-020-09662-x. Epub 2021 Jan 7.
In this paper, phase space reconstruction from stereo-electroencephalography data of ten patients with focal epilepsy forms a series of graphs. Those obtained graphs reflect the transition characteristics of brain dynamical system from pre-seizure to seizure of epilepsy. Interestingly, it is found that the rank of Laplacian matrix of these graphs has a sharp decrease when a seizure is close to happen, which thus might be viewed as a new potential biomarker in epilepsy. In addition, the reliability of this method is numerically verified with a coupled mass neural model. In particular, our simulation suggests that this potential biomarker can play the roles of predictive effect or delayed awareness, depending on the bias current of the Gaussian noise. These results may give new insights into the seizure detection.
在本文中，对十名局灶性癫痫患者的立体脑电图数据进行相空间重构，形成了一系列图形。所得到的这些图形反映了癫痫脑动力系统从发作前到发作时的转变特征。有趣的是，发现当癫痫发作临近时，这些图形的拉普拉斯矩阵的秩会急剧下降，因此这可能被视为癫痫的一种新的潜在生物标志物。此外，用一个耦合质量神经模型对该方法的可靠性进行了数值验证。特别是，我们的模拟表明，根据高斯噪声的偏置电流，这种潜在生物标志物可以起到预测作用或延迟感知作用。这些结果可能为癫痫发作检测提供新的见解。
