脑电源定位中传感器密度与头表面覆盖

Jasmine Song, Colin Davey, C. Poulsen, S. Turovets, P. Luu, D. Tucker
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引用次数: 10

摘要

在脑电图(EEG)测量的研究中,为了将脑电图电位与脑功能联系起来,识别在头表面记录的电位的潜在来源是有用的。记录在头部表面的脑电图是大脑特定部位(主要是皮层)电流如何通过头部组织传导体积传播的函数。源定位的准确性取决于对表面势场的充分采样,对传导体积(头部模型)的准确估计以及逆技术。本文报道了头部表面势场空间采样的影响,包括传感器密度和下(下)和上(上)头部区域的覆盖率。研究了四壳球头模型和有限差分模型的几种反演方法。与以往的研究一致,传感器密度越大,源定位精度越高。此外,在所有采样密度和逆方法中,整个头部表面的采样提高了源估计的准确性。
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Sensor density and head surface coverage in EEG source localization
In research with electroencephalographic (EEG) measures, it is useful to identify the sources underlying the potentials recorded at the head surface in order to relate the EEG potentials to brain function. The EEG recorded at the head surface is a function of how current at specific brain (primarily cortical) locations propagates through the conducting volume of head tissues. The accuracy of source localization depends on a sufficient sampling of the surface potential field, an accurate estimation of the conducting volume (head model), and the inverse technique. The present paper reports the effect of spatial sampling of the potential field at the head surface, in terms of both sensor density and coverage of the inferior (lower) as well as superior (upper) head regions. Several inverse methods are examined, using the four shells spherical head model and the finite difference model. Consistent with previous research, greater sensor density improves source localization accuracy. In addition, across all sampling density and inverse methods, sampling across the whole head surface improves the accuracy of source estimates.
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