Bernstein Center, University of Freiburg, Hansastr. 9a, 79104 Freiburg, Germany.
J Neural Eng. 2017 Oct;14(5):056008. doi: 10.1088/1741-2552/aa7db1. Epub 2017 Jul 5.
Electrical source localization (ESL) deriving from scalp EEG and, in recent years, from intracranial EEG (iEEG), is an established method in epilepsy surgery workup. We aimed to validate the distributed ESL derived from scalp EEG and iEEG, particularly regarding the spatial extent of the source, using a realistic epileptic spike activity simulator.
ESL was applied to the averaged scalp EEG and iEEG spikes of two patients with drug-resistant structural epilepsy. The ESL results for both patients were used to outline the location and extent of epileptic cortical patches, which served as the basis for designing a spatiotemporal source model. EEG signals for both modalities were then generated for different anatomic locations and spatial extents. ESL was subsequently performed on simulated signals with sLORETA, a commonly used distributed algorithm. ESL accuracy was quantitatively assessed for iEEG and scalp EEG.
The source volume was overestimated by sLORETA at both EEG scales, with the error increasing with source size, particularly for iEEG. For larger sources, ESL accuracy drastically decreased, and reconstruction volumes shifted to the center of the head for iEEG, while remaining stable for scalp EEG. Overall, the mislocalization of the reconstructed source was more pronounced for iEEG.
We present a novel multiscale framework for the evaluation of distributed ESL, based on realistic multiscale EEG simulations. Our findings support that reconstruction results for scalp EEG are often more accurate than for iEEG, owing to the superior 3D coverage of the head. Particularly the iEEG-derived reconstruction results for larger, widespread generators should be treated with caution.
源自头皮脑电图（EEG），近年来源自颅内 EEG（iEEG）的电源定位（ESL）是癫痫手术评估中的一种成熟方法。我们旨在使用逼真的癫痫棘波活动模拟器验证源自头皮 EEG 和 iEEG 的分布式 ESL，特别是关于源的空间范围。
将 ESL 应用于两名耐药性结构性癫痫患者的平均头皮 EEG 和 iEEG 棘波。将两名患者的 ESL 结果用于勾勒出癫痫皮质斑块的位置和范围，这是设计时空源模型的基础。然后为不同的解剖位置和空间范围生成两种模态的 EEG 信号。随后使用 sLORETA（一种常用的分布式算法）对模拟信号执行 ESL。对 iEEG 和头皮 EEG 的 ESL 准确性进行定量评估。
sLORETA 在两种 EEG 尺度上均高估了源体积，误差随源大小增加而增加，尤其是对于 iEEG。对于较大的源，ESL 准确性急剧下降，并且重建体积向 iEEG 的头部中心转移，而对于头皮 EEG 则保持稳定。总体而言，对于 iEEG，重建源的误定位更为明显。
我们提出了一种基于逼真的多尺度 EEG 模拟的新型分布式 ESL 评估多尺度框架。我们的发现支持头皮 EEG 的重建结果通常比 iEEG 更准确，这归因于头部的优越 3D 覆盖范围。特别是对于更大、广泛分布的发生器，应谨慎对待 iEEG 得出的重建结果。
