A realistic, accurate and fast source modeling approach for the EEG forward problem
A realistic, accurate and fast source modeling approach for the EEG forward problem
复制标题
DOI：
10.1016/j.neuroimage.2018.08.054
复制
发表时间：
2019-01-01
期刊：
影响因子：
5.7
通讯作者：
Pursiainen, Sampsa
中科院分区：
文献类型：
--
作者：
Miinalainen, Tuuli;Rezaei, Atena;Pursiainen, Sampsa
本文的目的是在传统的三室(皮肤、头骨、脑)模型的基础上，考虑脑组织的非均质性(灰质、白质和脑脊液)，提出一种基于有限元方法的脑电(EEG)源分析方法。这种新的方法应该能够在人类薄皮层结构中进行准确的脑电正演建模，更具体地说，在儿童大脑研究或病理应用中的特别薄的大脑皮层中。因此，源模型应该足够聚焦，以便在薄皮质中使用，但在另一端应该比当前标准的数学点偶极子更现实。此外，它在数值上应该是准确的，在计算上也应该很快。我们建议使用电流保持(散度顺应)偶极子源模型来实现这些需求之间的最佳平衡。我们发展和研究了不同数目的保流源基元素n(n=1，…，n=5)。为了验证，我们在存在解析解的多层球面区域内进行了数值实验。结果表明，随着基元个数的增加，精度提高，而焦度降低。结果表明，当n=4(或者在极端情况下甚至n=3)基函数时，薄皮质的精度和焦度之间达到最佳平衡，而对于较厚的皮质，建议n=5以获得最高的精度。我们还将保流方法与另外两种有限元源建模技术，即部分积分法和圣维南方法进行了比较，结果表明，最好的保流方法在整体平衡方面优于竞争方法。对于所有测试的方法，有限元传递矩阵使计算速度更快。我们将新的EEG正演模拟方法应用到开放源码的Duneuro库中，用于生物电磁学的正演模拟，以使其能够被大脑研究社区更广泛地使用。该库建立在用于并行有限元模拟的沙丘框架之上，并与FieldTrip等高级工具箱集成在一起。此外，还使用真实头部模型进行了反演测试，以演示和比较上述震源模型之间的差异。
The aim of this paper is to advance electroencephalography (EEG) source analysis using finite element method (FEM) head volume conductor models that go beyond the standard three compartment (skin, skull, brain) approach and take brain tissue inhomogeneity (gray and white matter and cerebrospinal fluid) into account. The new approach should enable accurate EEG forward modeling in the thin human cortical structures and, more specifically, in the especially thin cortices in children brain research or in pathological applications. The source model should thus be focal enough to be usable in the thin cortices, but should on the other side be more realistic than the current standard mathematical point dipole. Furthermore, it should be numerically accurate and computationally fast. We propose to achieve the best balance between these demands with a current preserving (divergence conforming) dipolar source model. We develop and investigate a varying number of current preserving source basis elements n (n = 1, ..., n=5). For validation, we conducted numerical experiments within a multi-layered spherical domain, where an analytical solution exists. We show that the accuracy increases along with the number of basis elements, while focality decreases. The results suggest that the best balance between accuracy and focality in thin cortices is achieved with n = 4 (or in extreme cases even n = 3) basis functions, while in thicker cortices n = 5 is recommended to obtain the highest accuracy. We also compare the current preserving approach to two further FEM source modeling techniques, namely partial integration and St. Venant, and show that the best current preserving source model outperforms the competing methods with regard to overall balance. For all tested approaches, FEM transfer matrices enable high computational speed. We implemented the new EEG forward modeling approaches into the open source duneuro library for forward modeling in bioelectromagnetism to enable its broader use by the brain research community. This library is build upon the DUNE framework for parallel finite elements simulations and integrates with high-level toolboxes like FieldTrip. Additionally, an inversion test has been implemented using the realistic head model to demonstrate and compare the differences between the aforementioned source models.