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

机译:离散伽马振荡识别一些儿科癫痫患者的癫痫发作区域

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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)在小儿癫痫患者引导癫痫手术中起重要作用。最近,对临床IEEG记录的较高频率分量及其与癫痫脑组织的潜在关系的兴趣增加了兴趣。我们采用先前经过验证的自动离散伽马振荡(GO)检测算法,以确定从十名患者记录的IEEG的延长,代表性段的离散伽马事件的普遍性。分析了大约8小时的IEEG,16分别选择每位患者的30分钟的连续Interrictal IEEG段。发现癫痫发作区域内的电极在十个患者中的五个患者中,在这16个段中,在这16个细分中平均平均值更高。在这些患者中观察到各个30分钟的细分之间的可变性,表明液间活动的较长记录改善了本地化。我们的数据表明,这种自动化的方法在长期中的自动化方法可能是在某些患有顽固性癫痫的儿童中规划癫痫手术的方法。需要进一步的研究来帮助确定哪些患者会受益于这种技术。

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