Farahmand Sina, Sobayo Tiwalade, Mogul David J
Annu Int Conf IEEE Eng Med Biol Soc. 2018 Jul;2018:2406-2409. doi: 10.1109/EMBC.2018.8512794.
In this paper, an adaptive, non-linear, analytical methodology is proposed in order to quantitatively evaluate the instantaneous phase-synchrony dynamics in epilepsy patients. A group of finite neuronal oscillators is extracted from a multichannel electrocorticographic (ECoG) data, using the empirical mode decomposition (EMD). The instantaneous phases of the extracted oscillators are measured using the Hilbert transform in order to be utilized in the mean-phase coherence analysis. Finally, the dynamical evolution of phase-synchrony among the extracted neuronal oscillators within 1-600 Hz frequency range is assessed using eigenvalue decomposition. A different phasesynchrony dynamics was observed in two patients with frontal vs. temporal lobe epilepsy, as their seizures evolve. However, experimental results demonstrated a hypersynchrony level at seizure offset for both types of epilepsy during the ictal periods. This result suggests that hypersynchronization of the epileptic network may be a crucial, self-regulatory mechanism by which the brain terminate seizures.
本文提出了一种自适应、非线性分析方法，用于定量评估癫痫患者的瞬时相位同步动力学。利用经验模态分解（EMD）从多通道皮质脑电图（ECoG）数据中提取一组有限神经元振荡器。使用希尔伯特变换测量提取振荡器的瞬时相位，以便用于平均相位相干分析。最后，利用特征值分解评估提取的神经元振荡器在1 - 600Hz频率范围内相位同步的动态演化。随着癫痫发作的发展，在两名患有额叶癫痫和颞叶癫痫的患者中观察到了不同的相位同步动力学。然而，实验结果表明，在发作期，两种类型癫痫在发作结束时都存在超同步水平。这一结果表明，癫痫网络的超同步化可能是大脑终止癫痫发作的一种关键的自我调节机制。
