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Discrete gamma oscillations identify the seizure onset zone in some pediatric epilepsy patients

机译:离散的伽马振荡确定了一些小儿癫痫患者的癫痫发作区

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Intracranial electroencephalography (IEEG) plays an important role in guiding epilepsy surgery in pediatric epilepsy patients. Recently, there has been increased interest in higher frequency components of clinical IEEG recordings and their potential relationship to epileptogenic brain tissue. We employ a previously validated, automated discrete gamma oscillation (GO) detection algorithm to determine the prevalence of discrete gamma events over prolonged, representative segments of IEEG recorded from ten patients. Approximately 8 h of IEEG, 16 randomly selected 30-min segments of continuous interictal IEEG per patient, were analyzed. The electrodes within the seizure onset zone were found to have significantly higher mean GO activity averaged across these 16 segments in five of the ten patients. There was observed variability between individual 30-min segments in these patients, indicating that longer recordings of interictal activity improved localization. Our data suggest this method of automated GO detection across long periods may be useful in planning epilepsy surgery in certain children with intractable epilepsy. Further research is required to help determine which patients would benefit from this technique.
机译:颅内脑电图(IEEG)在指导小儿癫痫患者的癫痫手术中起着重要作用。最近,人们对临床IEEG记录的更高频率成分及其与癫痫性脑组织的潜在关系越来越感兴趣。我们采用先前验证过的自动离散伽玛振动(GO)检测算法来确定从十名患者记录的IEEG的延长的代表性段中离散伽玛事件的发生率。大约IEEG的8小时,分析了每位患者随机选择的16个30分钟的连续发作的IEEG片段。发现癫痫发作区域内的电极在十名患者中的五名患者中,在这16个节段中平均具有较高的平均GO活性。在这些患者中,观察到各个30分钟段之间存在差异,这表明更长的记录间质活动可改善定位。我们的数据表明,这种长期的自动GO检测方法可能有助于计划某些难治性癫痫患儿的癫痫手术。需要进一步的研究来帮助确定哪些患者将从该技术中受益。

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