Department of Cognitive Sciences, University of California, Irvine, CA 92697, USA.
IEEE Trans Biomed Eng. 2012 Nov;59(11):2979-85. doi: 10.1109/TBME.2012.2183638. Epub 2012 Jan 11.
Surface Laplacian of scalp EEG can be used to estimate the potential distribution on the cortical surface as an alternative to invasive approaches. However, the accuracy of surface Laplacian estimation depends critically on the geometric shape of the head model. This paper presents a new method for computing the surface Laplacian of scalp potential directly on realistic scalp surfaces in the form of a triangular mesh reconstructed from MRI scans. Unlike previous methods, this algorithm does not resort to any surface fitting proxy and can improve the surface Laplacian estimation of cortical potential patterns by as much as 34% on realistically shaped head models. Simulations and experimental data are presented to demonstrate the advantage of the proposed method over the conventional spherical approximation and the utility of a more accurate surface Laplacian method for estimating cortical potentials from scalp electrodes.
头皮 EEG 的表面拉普拉斯可以被用来估计皮质表面的电势分布，这是一种替代有创方法的手段。然而，表面拉普拉斯的估计精度严重依赖于头模型的几何形状。本文提出了一种新的方法，可以直接在从 MRI 扫描重建的三角网格形式的真实头皮表面上计算头皮电位的表面拉普拉斯。与以前的方法不同，该算法不依赖于任何表面拟合代理，并且可以在真实形状的头模型上提高皮质电位模式的表面拉普拉斯估计多达 34%。模拟和实验数据表明，与传统的球近似相比，所提出的方法具有优势，并且从头皮电极估计皮质电位的更精确的表面拉普拉斯方法具有实用性。
