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癫痫网络的临床与电生理学。

Semiology and Epileptic Networks.

机构信息

Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France; APHM, Timone Hospital, Epileptology and cerebral rythmology, Marseille, France.

出版信息

Neurosurg Clin N Am. 2020 Jul;31(3):373-385. doi: 10.1016/j.nec.2020.03.003. Epub 2020 Apr 25.

Abstract

Seizure semiology represents the dynamic clinical expression of seizures and is an important behavioral data source providing clues to cerebral organization. It is produced through interactions between electrical seizure discharge and physiologic and pathologic brain networks. Semiology is described in spatial and temporal terms; its expression depends on spatial (localization) and temporal (eg, discharge frequency, synchrony) characteristics of cerebral electrical activity. Stereoelectroencephalography studies of electroclinical correlations, including with quantified signal analysis, have helped elucidate several semiological patterns. Future research could help improve pattern recognition of complex semiological patterns, possibly using deep learning methods in a multiscale, multimodal modelization framework.

摘要

发作症候学代表着发作的动态临床表现,是提供大脑组织线索的重要行为数据来源。它是通过电发作放电与生理和病理大脑网络之间的相互作用产生的。症候学是用空间和时间术语来描述的;它的表现取决于大脑电活动的空间(定位)和时间(例如,放电频率,同步性)特征。立体脑电图研究了电临床相关性,包括使用量化信号分析,这有助于阐明几种症候学模式。未来的研究可能有助于提高复杂症候学模式的模式识别,可能使用深度学习方法在多尺度、多模态模型化框架中。

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