A novel method for calibrating head models to account for variability in conductivity and its evaluation in a sphere model
A novel method for calibrating head models to account for variability in conductivity and its evaluation in a sphere model
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DOI：
10.1088/1361-6560/abc5aa
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发表时间：
2020-10
影响因子：
3.5
通讯作者：
Sophie Schrader;M. Antonakakis;Stefan Rampp;Christian Engwer;Carsten H. Wolters
中科院分区：
文献类型：
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作者：
Sophie Schrader;M. Antonakakis;Stefan Rampp;Christian Engwer;Carsten H. Wolters
脑电(EEG)和联合脑电和脑磁图(MEG)源重建以及优化经颅电刺激(TES)的准确性取决于分配给头部模型的导电特性，最重要的是取决于个体头骨的导电性。在这项研究中，我们提出了一种基于体感诱发电位和场重建P20/N20反应的头部模型的自动校准管道。为了在不存在数值误差的情况下，在受控良好的情况下验证算法的准确性，我们在一个四层球形头部模型中，使用真实的噪声水平以及与体感实验相关的强度和方位的不同偏心的偶极子源来评估该算法的准确性。我们的结果表明，对于类似于P20/N20响应的发生器的源，参考头骨电导率可以可靠地重建。在头皮电导率假设错误的情况下，得到的头骨电导率参数抵消了这种影响，因此使用拟合的头骨电导率参数重建脑电源的误差低于使用标准值时的误差。我们提出了一种自动校准头部模型的程序，该程序只依赖于标准脑磁图实验室中提供的非侵入性模式，在活体条件下和在感兴趣的低频范围内进行测量。校正后的头部建模可以改善EEG，结合EEG/MEG源分析以及优化的TES。
The accuracy in electroencephalography (EEG) and combined EEG and magnetoencephalography (MEG) source reconstructions as well as in optimized transcranial electric stimulation (TES) depends on the conductive properties assigned to the head model, and most importantly on individual skull conductivity. In this study, we present an automatic pipeline to calibrate head models with respect to skull conductivity based on the reconstruction of the P20/N20 response using somatosensory evoked potentials and fields. In order to validate in a well-controlled setup without interplay with numerical errors, we evaluate the accuracy of this algorithm in a 4-layer spherical head model using realistic noise levels as well as dipole sources at different eccentricities with strengths and orientations related to somatosensory experiments. Our results show that the reference skull conductivity can be reliably reconstructed for sources resembling the generator of the P20/N20 response. In case of erroneous assumptions on scalp conductivity, the resulting skull conductivity parameter counterbalances this effect, so that EEG source reconstructions using the fitted skull conductivity parameter result in lower errors than when using the standard value. We propose an automatized procedure to calibrate head models which only relies on non-invasive modalities that are available in a standard MEG laboratory, measures under in vivo conditions and in the low frequency range of interest. Calibrated head modeling can improve EEG and combined EEG/MEG source analysis as well as optimized TES.