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首页> 外文期刊>Physics in medicine and biology. >Dipole estimation errors due to differences in modeling anisotropic conductivities in realistic head models for EEG source analysis
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Dipole estimation errors due to differences in modeling anisotropic conductivities in realistic head models for EEG source analysis

机译:由于脑电图源分析的实际头部模型中各向异性电导率建模的差异导致偶极子估计误差

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摘要

To improve the EEG source localization in the brain, the conductivities used in the head model play a very important role. In this study, we focus on the modeling of the anisotropic conductivity of the white matter. The anisotropic conductivity profile can be derived from diffusion weighted magnetic resonance images (DW-MRI). However, deriving these anisotropic conductivities from diffusion weighted MR images of the white matter is not straightforward. In the literature, two methods can be found for calculating the conductivity from the diffusion weighted images. One method uses a fixed value for the ratio of the conductivity in different directions, while the other method uses a conductivity profile obtained from a linear scaling of the diffusion ellipsoid. We propose a model which can be used to derive the conductivity profile from the diffusion tensor images. This model is based on the variable anisotropic ratio throughout the white matter and is a combination of the linear relationship as stated in the literature, with a constraint on the magnitude of the conductivity tensor ( also known as the volume constraint). This approach is stated in the paper as approach A. In our study we want to investigate dipole estimation differences due to using a more simplified model for white matter anisotropy ( approach B), while the electrode potentials are derived using a head model with a more realistic approach for the white matter anisotropy ( approach A). We used a realistic head model, in which the forward problem was solved using a finite difference method that can incorporate anisotropic conductivities. As error measures we considered the dipole location error and the dipole orientation error. The results show that the dipole location errors are all below 10 mm and have an average of 4 mm in gray matter regions. The dipole orientation errors ranged up to 66.4 degrees, and had a mean of, on average, 11.6 degrees in gray matter regions. In a qualitative manner, the results show that the orientation and location error is dependent on the orientation of the test dipole. The location error is larger when the orientation of the test dipole is similar to the orientation of the anisotropy, while the orientation error is larger when the orientation of the test dipole deviates from the orientation of the anisotropy. From these results, we can conclude that the modeling of white matter anisotropy plays an important role in EEG source localization. More specifically, accurate source localization will require an accurate modeling of the white matter conductivity profile in each voxel.
机译:为了改善脑电信号源的定位,头部模型中使用的电导率起着非常重要的作用。在这项研究中,我们专注于白质各向异性电导率的建模。各向异性电导率曲线可以从扩散加权磁共振图像(DW-MRI)中得出。但是,从白质的扩散加权MR图像导出这些各向异性电导率并不容易。在文献中,可以找到两种方法用于根据扩散加权图像计算电导率。一种方法对不同方向上的电导率比率使用固定值,而另一种方法使用根据扩散椭圆体的线性比例获得的电导率分布。我们提出了一个模型,该模型可用于从扩散张量图像中导出电导率分布。该模型基于整个白质的可变各向异性比率,并且是文献中所述的线性关系与电导率张量大小的约束(也称为体积约束)的组合。该方法在本文中称为方法A。在我们的研究中,我们希望调查偶极子估计的差异,这是由于使用了一种更为简化的白质各向异性模型(方法B),而电极电势是使用具有更高模型的头部模型导出的白质各向异性的现实方法(方法A)。我们使用了一个现实的水头模型,其中正向问题使用可以包含各向异性电导率的有限差分方法解决。作为误差度量,我们考虑了偶极子位置误差和偶极子方位误差。结果表明,偶极子定位误差均在10 mm以下,在灰质区域平均为4 mm。偶极子定向误差范围高达66.4度,在灰质区域平均为11.6度。从定性的角度来看,结果表明方向和位置误差取决于测试偶极子的方向。当测试偶极子的取向与各向异性的取向相似时,位置误差较大,而当测试偶极子的取向偏离各向异性的取向时,定位误差较大。从这些结果,我们可以得出结论,白质各向异性的建模在脑电图源定位中起着重要作用。更具体地说,精确的源定位将需要对每个体素中的白质电导率轮廓进行精确的建模。

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