Virginia Tech Carilion Research Institute, Roanoke, VA 24015, USA; Department of Clinical Neurophysiology, Georg-August-University, Göttingen, Germany.
Virginia Tech Carilion Research Institute, Roanoke, VA 24015, USA.
Neuroimage. 2013 Nov 1;81:253-264. doi: 10.1016/j.neuroimage.2013.04.067. Epub 2013 May 1.
Recent evidence indicates subject-specific gyral folding patterns and white matter anisotropy uniquely shape electric fields generated by TMS. Current methods for predicting the brain regions influenced by TMS involve projecting the TMS coil position or center of gravity onto realistic head models derived from structural and functional imaging data. Similarly, spherical models have been used to estimate electric field distributions generated by TMS pulses delivered from a particular coil location and position. In the present paper we inspect differences between electric field computations estimated using the finite element method (FEM) and projection-based approaches described above. We then more specifically examined an approach for estimating cortical excitation volumes based on individualistic FEM simulations of electric fields. We evaluated this approach by performing neurophysiological recordings during MR-navigated motormapping experiments. We recorded motor evoked potentials (MEPs) in response to single pulse TMS using two different coil orientations (45° and 90° to midline) at 25 different locations (5×5 grid, 1cm spacing) centered on the hotspot of the right first dorsal interosseous (FDI) muscle in left motor cortex. We observed that motor excitability maps varied within and between subjects as a function of TMS coil position and orientation. For each coil position and orientation tested, simulations of the TMS-induced electric field were computed using individualistic FEM models and compared to MEP amplitudes obtained during our motormapping experiments. We found FEM simulations of electric field strength, which take into account subject-specific gyral geometry and tissue conductivity anisotropy, significantly correlated with physiologically observed MEP amplitudes (rmax=0.91, p=1.8×10(-5) rmean=0.81, p=0.01). These observations validate the implementation of individualistic FEM models to account for variations in gyral folding patterns and tissue conductivity anisotropy, which should help improve the targeting accuracy of TMS in the mapping or modulation of human brain circuits.
最近的证据表明,特定于主体的脑回折叠模式和白质各向异性独特地塑造了 TMS 产生的电场。目前预测 TMS 影响的脑区的方法涉及将 TMS 线圈位置或重心投影到源自结构和功能成像数据的逼真头部模型上。同样,已经使用球形模型来估计从特定线圈位置和位置发送的 TMS 脉冲产生的电场分布。在本文中,我们检查了使用有限元方法(FEM)和上述基于投影的方法估算的电场之间的差异。然后,我们更具体地检查了一种基于个体 FEM 电场模拟估算皮质激发体积的方法。我们通过在磁共振导航运动映射实验期间进行神经生理学记录来评估这种方法。我们使用两种不同的线圈方向(45°和 90°中线)在右第一背侧骨间(FDI)肌肉热点中心的 25 个不同位置(5×5 网格,1cm 间距)记录了针对单脉冲 TMS 的运动诱发电位(MEP)。我们观察到,运动兴奋性图随着 TMS 线圈位置和方向的变化而在个体内和个体间变化。对于测试的每个线圈位置和方向,使用个体化 FEM 模型计算 TMS 诱导的电场的模拟,并将其与我们运动映射实验中获得的 MEP 幅度进行比较。我们发现,考虑到特定于主体的脑回几何形状和组织电导率各向异性的 FEM 模拟电场强度与生理上观察到的 MEP 幅度显着相关(rmax=0.91,p=1.8×10(-5) rmean=0.81,p=0.01)。这些观察结果验证了实施个体化 FEM 模型以解释脑回折叠模式和组织电导率各向异性的变化,这有助于提高 TMS 在人类大脑回路的映射或调制中的靶向准确性。