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Stereotyped high-frequency oscillations discriminate seizure onset zones and critical functional cortex in focal epilepsy.
Brain ( IF 10.6 ) Pub Date : 2018-03-01 , DOI: 10.1093/brain/awx374
Su Liu 1 , Candan Gurses 2 , Zhiyi Sha 3 , Michael M Quach 4 , Altay Sencer 5 , Nerses Bebek 2 , Daniel J Curry 6 , Sujit Prabhu 7 , Sudhakar Tummala 7 , Thomas R Henry 3 , Nuri F Ince 1
Affiliation  

High-frequency oscillations in local field potentials recorded with intracranial EEG are putative biomarkers of seizure onset zones in epileptic brain. However, localized 80-500 Hz oscillations can also be recorded from normal and non-epileptic cerebral structures. When defined only by rate or frequency, physiological high-frequency oscillations are indistinguishable from pathological ones, which limit their application in epilepsy presurgical planning. We hypothesized that pathological high-frequency oscillations occur in a repetitive fashion with a similar waveform morphology that specifically indicates seizure onset zones. We investigated the waveform patterns of automatically detected high-frequency oscillations in 13 epilepsy patients and five control subjects, with an average of 73 subdural and intracerebral electrodes recorded per patient. The repetitive oscillatory waveforms were identified by using a pipeline of unsupervised machine learning techniques and were then correlated with independently clinician-defined seizure onset zones. Consistently in all patients, the stereotypical high-frequency oscillations with the highest degree of waveform similarity were localized within the seizure onset zones only, whereas the channels generating high-frequency oscillations embedded in random waveforms were found in the functional regions independent from the epileptogenic locations. The repetitive waveform pattern was more evident in fast ripples compared to ripples, suggesting a potential association between waveform repetition and the underlying pathological network. Our findings provided a new tool for the interpretation of pathological high-frequency oscillations that can be efficiently applied to distinguish seizure onset zones from functionally important sites, which is a critical step towards the translation of these signature events into valid clinical biomarkers.awx374media15721572971001.

中文翻译:

刻板印象的高频振荡可区分癫痫发作区和局灶性癫痫的关键功能皮质。

颅内脑电图记录的局部场电位的高频振荡是癫痫性脑癫痫发作区的推测生物标志。但是,也可以从正常和非癫痫性脑结构中记录到局部80-500 Hz振荡。当仅由频率或频率定义时,生理性高频振荡与病理性振荡是无法区分的,这限制了它们在癫痫术前计划中的应用。我们假设病理性高频振荡以重复的方式发生,并具有类似的波形形态,具体表明癫痫发作发作区。我们调查了13例癫痫患者和5例对照对象的自动检测到的高频振荡的波形图,每位患者平均记录了73个硬膜下和脑内电极。通过使用无监督机器学习技术的流水线识别重复的振荡波形,然后将其与独立的临床医生定义的癫痫发作发作区域相关联。一致地,在所有患者中,具有最高波形相似度的定型高频振荡仅局限在癫痫发作发作区域内,而在随机波形中嵌入产生随机振荡的高频振荡的通道位于与癫痫发生部位无关的功能区域中。 。与波动相比,快速波动中的重复波形模式更为明显,这表明波形重复与潜在的病理网络之间存在潜在的关联。
更新日期:2018-01-30
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