Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, 27710, USA.
Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, 27710, USA; Department of Electrical and Computer Engineering, Duke University, Durham, NC, 27708, USA; Department of Neurosurgery, Duke University, Durham, NC, 27710, USA; Department of Biomedical Engineering, Duke University, Durham, NC, 27708, USA.
Brain Stimul. 2020 Jan-Feb;13(1):157-166. doi: 10.1016/j.brs.2019.09.015. Epub 2019 Oct 3.
Computational simulations of the E-field induced by transcranial magnetic stimulation (TMS) are increasingly used to understand its mechanisms and to inform its administration. However, characterization of the accuracy of the simulation methods and the factors that affect it is lacking.
To ensure the accuracy of TMS E-field simulations, we systematically quantify their numerical error and provide guidelines for their setup.
We benchmark the accuracy of computational approaches that are commonly used for TMS E-field simulations, including the finite element method (FEM) with and without superconvergent patch recovery (SPR), boundary element method (BEM), finite difference method (FDM), and coil modeling methods.
To achieve cortical E-field error levels below 2%, the commonly used FDM and 1st order FEM require meshes with an average edge length below 0.4 mm, 1st order SPR-FEM requires edge lengths below 0.8 mm, and BEM and 2nd (or higher) order FEM require edge lengths below 2.9 mm. Coil models employing magnetic and current dipoles require at least 200 and 3000 dipoles, respectively. For thick solid-conductor coils and frequencies above 3 kHz, winding eddy currents may have to be modeled.
BEM, FDM, and FEM all converge to the same solution. Compared to the common FDM and 1st order FEM approaches, BEM and 2nd (or higher) order FEM require significantly lower mesh densities to achieve the same error level. In some cases, coil winding eddy-currents must be modeled. Both electric current dipole and magnetic dipole models of the coil current can be accurate with sufficiently fine discretization.
经颅磁刺激(TMS)诱发电场的计算模拟越来越多地用于理解其机制并为其应用提供信息。然而,模拟方法的准确性及其影响因素的特征化却缺乏研究。
为确保 TMS 电场模拟的准确性,我们系统地量化了其数值误差,并为其设置提供了指导原则。
我们对常用于 TMS 电场模拟的计算方法的准确性进行了基准测试,包括有限元法(FEM)和带有或不带有超收敛补丁恢复(SPR)的有限元法、边界元法(BEM)、有限差分法(FDM)和线圈建模方法。
为了将皮层电场误差水平控制在 2%以下,常用的 FDM 和一阶 FEM 需要平均边长小于 0.4mm 的网格,一阶 SPR-FEM 需要边长小于 0.8mm 的网格,BEM 和二阶(或更高阶)FEM 需要边长小于 2.9mm 的网格。采用磁偶极子和电流偶极子的线圈模型分别至少需要 200 和 3000 个偶极子。对于厚的实心导体线圈和高于 3kHz 的频率,可能需要对绕组涡流进行建模。
BEM、FDM 和 FEM 都收敛到相同的解。与常见的 FDM 和一阶 FEM 方法相比,BEM 和二阶(或更高阶)FEM 要达到相同的误差水平,所需的网格密度要低得多。在某些情况下,必须对线圈绕组涡流进行建模。只要离散化足够精细,线圈电流的电偶极子和磁偶极子模型都可以是准确的。