Epileptogenic Source Imaging Using Cross-Frequency Coupled Signals From Scalp EEG
Epileptogenic Source Imaging Using Cross-Frequency Coupled Signals From Scalp EEG
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DOI：
10.1109/tbme.2016.2613936
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发表时间：
2016-12-01
影响因子：
4.6
通讯作者：
Bardakjian, Berj L.
中科院分区：
文献类型：
--
作者：
Li, Chunsheng;Jacobs, Daniel;Bardakjian, Berj L.
目的：致痫带（epileptogeniczone，EZ）是一个包含癫痫发生源的脑区。切除EZ与切除手术后癫痫发作停止相关，如Engel I级评分所测量。本研究描述了一种新型的脑电（electroencephalogram，EEG）源成像（ESI）方法，该方法使用来自头皮脑电的跨频耦合电位信号（SCFC）。方法：对10例（20次）癫痫患者进行头皮脑电图检查。SCFC由电图发作时低频和高频节律的相位和振幅构建。然后使用SCFC进行ESI。该技术的验证是由已知的皮质源的正向和反向计算机建模，以及患者切除区域的ESI与EZ的对应关系促进的。结果如下：对于从4名患者中以500 Hz或以上采样的10次癫痫发作，所有估计的来源都位于切除区域内，强调了更高采样率的临床重要性。SCFC表现出显着的优势，“原始”头皮EEG，表明其强大的噪声性能。建模研究表明，信噪比高于0.2是足以实现成功的定位有关EMG伪影。结论：估计的源与EZ的关联表明，交叉频率耦合是大脑神经网络的一个特征，而不是人为活动。SCFC可以有效地从噪声背景中提取大脑信号。意义：我们提出这种方法，以提高颅内电极的放置手术干预。
Objective: The epileptogenic zone (EZ) is a brain region containing the sources of seizure genesis. Removal of the EZ is associated with cessation of seizures after resective surgical procedures, as measured by Engel Class I score. This study describes a novel EEG (electroencephalography) source imaging (ESI) method which uses cross-frequency coupled potential signals (SCFC) derived from scalp EEG. Methods: Scalp EEG were recorded from ten patients (20 seizures) suffering from epilepsy. The SCFC were constructed from the phase and amplitude of the lower and higher frequency rhythms at electrographic seizure onset. ESI was then performed using the SCFC. Validation of the technique was facilitated by forward and inverse computer modeling of known cortical sources, and the correspondence of the ESI with EZ in resected regions of patients. Results: For ten seizures sampled at or above 500 Hz from four patients, all estimated sources lay within the resected region, emphasizing the clinical importance of higher sampling rates. The SCFC demonstrated significant advantages over the "raw" scalp EEG, indicating its robust noise performance. Modeling investigations indicated that a signal-to-noise ratio above 0.2 was sufficient to achieve successful localization regarding EMG artifacts. Conclusion: The association of the estimated sources to the EZ suggests that cross-frequency coupling is a feature of the brain's neural networks, not of artifactual activity. The SCFC can effectively extract brain signals from a noisy background. Significance: We propose this approach to enhance the placement of intracranial electrode for surgical intervention.