OBJECTIVE Ictal electrographic patterns are widely thought to reflect underlying neural mechanisms of seizures. Here we studied the degree to which seizure patterns are consistent in a given patient, relate to particular brain regions and if two candidate biomarkers (high-frequency oscillations, HFOs; infraslow activity, ISA) and network activity, as assessed with cross-frequency interactions, can discriminate between seizure types. METHODS We analyzed temporal changes in low and high frequency oscillations recorded during seizures, as well as phase-amplitude coupling (PAC) to monitor the interactions between delta/theta and ripple/fast ripple frequency bands at seizure onset. RESULTS Seizures of multiple electrographic patterns were observed in a given patient and brain region. While there was an increase in HFO rate across different electrographic patterns, there are specific relationships between types of HFO activity and onset region. Similarly, changes in PAC dynamics were more closely related to seizure onset region than they were to electrographic patterns while ISA was a poor indicator for seizure onset. CONCLUSIONS Our findings suggest that the onset region sculpts neurodynamics at seizure initiation and that unique features of the cytoarchitecture and/or connectivity of that region play a significant role in determining seizure mechanism. SIGNIFICANCE To learn how seizures are initiated, researchers would do well to consider other aspects of their manifestation, in addition to their electrographic patterns. Examination of onset pattern in conjunction with the interactions between different oscillatory frequencies in the context of different brain regions might be more informative and lead to more reliable clinical inference as well as novel therapeutic approaches.

中文翻译：

---

癫痫发作的位置塑造了起始的动态

目的 发作期电图模式被广泛认为反映了癫痫发作的潜在神经机制。在这里，我们研究了给定患者的癫痫发作模式的一致性程度，与特定的大脑区域有关，以及两个候选生物标志物（高频振荡、HFO；次低活动、ISA）和网络活动，如通过交叉频率相互作用评估的，可以区分癫痫发作类型。方法我们分析了癫痫发作期间记录的低频和高频振荡的时间变化，以及相位幅度耦合 (PAC)，以监测癫痫发作开始时 delta/theta 和纹波/快速纹波频带之间的相互作用。结果 在给定的患者和大脑区域中观察到多个电图模式的癫痫发作。虽然不同电图模式的 HFO 率有所增加，但 HFO 活动类型与发病区域之间存在特定关系。同样，PAC 动力学的变化与癫痫发作区域的关系比与电图模式的关系更密切，而 ISA 是癫痫发作的不良指标。结论我们的研究结果表明，发作区域在癫痫发作开始时塑造了神经动力学，并且该区域的细胞结构和/或连通性的独特特征在确定癫痫发作机制方面起着重要作用。意义 要了解癫痫发作是如何开始的，研究人员最好考虑一下癫痫表现的其他方面，除了他们的电图模式。