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一种用于癫痫棘波多尺度源分析和建模的新方法。

A novel approach for multiscale source analysis and modeling of epileptic spikes.

作者信息

Dumpelmann Matthias, Cosandier-Rimele Delphine, Ramantani Georgia, Schulze-Bonhage Andreas

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2015;2015:6634-7. doi: 10.1109/EMBC.2015.7319914.

DOI:10.1109/EMBC.2015.7319914
PMID:26737814
Abstract

Multiscale recordings of brain electrical activity are often performed for presurgical evaluation in patients with focal epilepsy to facilitate the identification and precise delineation of the epileptogenic zone. However, data regarding the concordance of source models derived from recordings on different scales and their reciprocal validation against clinical outcomes remains scarce. This study aims to define a common source model that accurately depicts both scalp EEG and subdural EEG (ECoG) interictal spikes. To this purpose, the sLORETA method was applied to averaged spikes and source reconstruction results were implemented to outline the location and extent of an epileptic cortical patch. This estimated patch served as the basis for the spatiotemporal source model in a generative model of EEG. Spike activity was simulated on both scalp EEG and ECoG signal scales, with simulated traces resembling measured traces regarding their spatial distribution and amplitude compared to background. Simulated spikes served for the evaluation of source reconstruction with a known generator topography. The described setup allows for the validation and, ultimately, for the refinement of source reconstruction methods. It provides novel insights towards a thorough understanding of physiological and pathological brain processes and their representation in neuroelectric measurements.

摘要

在局灶性癫痫患者的术前评估中,常进行脑电活动的多尺度记录,以促进癫痫源区的识别和精确划定。然而,关于从不同尺度记录中得出的源模型的一致性以及它们与临床结果的相互验证的数据仍然很少。本研究旨在定义一种能准确描绘头皮脑电图(EEG)和硬膜下脑电图(ECoG)发作间期棘波的通用源模型。为此,将sLORETA方法应用于平均棘波,并实施源重建结果以勾勒癫痫皮质斑块的位置和范围。这个估计的斑块作为脑电图生成模型中时空源模型的基础。在头皮EEG和ECoG信号尺度上模拟棘波活动,与背景相比,模拟轨迹在空间分布和幅度方面类似于测量轨迹。模拟棘波用于评估具有已知发生器地形的源重建。所描述的设置允许对源重建方法进行验证,并最终对其进行优化。它为深入理解生理和病理脑过程及其在神经电测量中的表现提供了新的见解。

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