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Identification of the Epileptogenic Zone from Stereo-EEG Signals: A Connectivity-Graph Theory Approach

机译:从立体脑电图信号识别癫痫区:一种连通图理论方法

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摘要

In the context of focal drug-resistant epilepsies, the surgical resection of the epileptogenic zone (EZ), the cortical region responsible for the onset, early seizures organization, and propagation, may be the only therapeutic option for reducing or suppressing seizures. The rather high rate of failure in epilepsy surgery of extra-temporal epilepsies highlights that the precise identification of the EZ, mandatory objective to achieve seizure freedom, is still an unsolved problem that requires more sophisticated methods of investigation. Despite the wide range of non-invasive investigations, intracranial stereo-EEG (SEEG) recordings still represent, in many patients, the gold standard for the EZ identification. In this contest, the EZ localization is still based on visual analysis of SEEG, inevitably affected by the drawback of subjectivity and strongly time-consuming. Over the last years, considerable efforts have been made to develop advanced signal analysis techniques able to improve the identification of the EZ. Particular attention has been paid to those methods aimed at quantifying and characterizing the interactions and causal relationships between neuronal populations, since is nowadays well assumed that epileptic phenomena are associated with abnormal changes in brain synchronization mechanisms, and initial evidence has shown the suitability of this approach for the EZ localization. The aim of this review is to provide an overview of the different EEG signal processing methods applied to study connectivity between distinct brain cortical regions, namely in focal epilepsies. In addition, with the aim of localizing the EZ, the approach based on graph theory will be described, since the study of the topological properties of the networks has strongly improved the study of brain connectivity mechanisms.
机译:在局灶性耐药性癫痫的背景下,癫痫发生区(EZ)的手术切除,负责发作,早期癫痫发作组织和繁殖的皮质区域,可能是减少或抑制癫痫发作的唯一治疗选择。颞外癫痫的癫痫手术失败率很高,这表明对EZ的准确识别(实现癫痫发作的强制性目标)仍然是一个悬而未决的问题,需要更复杂的研究方法。尽管进行了无创性检查,但在许多患者中,颅内立体脑电图(SEEG)记录仍是EZ鉴定的黄金标准。在本次比赛中,EZ本地化仍基于SEEG的可视化分析,不可避免地受到主观性缺点的影响,并且耗时很长。在过去的几年中,为开发先进的信号分析技术做出了巨大的努力,这些技术能够改善EZ的识别能力。特别关注那些旨在量化和表征神经元群体之间的相互作用和因果关系的方法,因为如今人们已经充分认识到癫痫现象与大脑同步机制的异常变化有关,并且初步证据表明这种方法的适用性。用于EZ本地化。这篇综述的目的是概述用于研究不同大脑皮层区域之间(即局灶性癫痫中)的连通性的不同EEG信号处理方法。另外,以对EZ进行定位为目标,将描述基于图论的方法,因为对网络拓扑特性的研究极大地改善了对大脑连通性机制的研究。

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