Pelot Nicole A, Thio Brandon J, Grill Warren M
Department of Biomedical Engineering, Duke University Durham, NC, United States.
Department of Electrical and Computer Engineering, Duke University Durham, NC, United States.
Front Comput Neurosci. 2018 Jun 8;12:40. doi: 10.3389/fncom.2018.00040. eCollection 2018.
Computational modeling provides an important toolset for designing and analyzing neural stimulation devices to treat neurological disorders and diseases. Modeling enables efficient exploration of large parameter spaces, where preclinical and clinical studies would be infeasible. Current commercial finite element method software packages enable straightforward calculation of the potential distributions, but it is not always clear how to implement boundary conditions to appropriately represent metal stimulating electrodes. By quantifying the effects of different electrode representations on activation thresholds for model axons, we provide recommendations for accurate and efficient modeling of neural stimulating electrodes. We quantified the effects of different representations of current sources for neural stimulation in COMSOL Multiphysics for monopolar, bipolar, and multipolar electrode designs. We recommend modeling each electrode contact as a thin platinum domain, modeling the electrode substrate with the conductivity of silicone, and either using a point current source in the center of each electrode contact or using a boundary current source. Alternatively, to avoid possible numerical instabilities associated with a large range of conductivity values (i.e., platinum and silicone) and to eliminate the small mesh elements required for thin electrode contacts, the electrode substrate can be assigned the conductivity of platinum by using insulating boundaries between the substrate and surrounding medium, and within the substrate to isolate the contacts from each other. When modeling more than one contact, we recommend using superposition by solving the model once for each contact, leaving inactive contacts floating, and superposing the resulting potentials. We computed comparable errors in activation thresholds across the different implementations in a simplified model (electrode in a homogeneous, isotropic medium), and in realistic models of rat spinal cord stimulation (SCS) and human deep brain stimulation, indicating that the recommended approaches are applicable to different stimulation targets.
计算建模为设计和分析用于治疗神经系统疾病的神经刺激设备提供了一个重要的工具集。建模能够有效地探索大型参数空间,而在这些参数空间中进行临床前和临床研究是不可行的。当前的商业有限元方法软件包能够直接计算电位分布,但如何实施边界条件以恰当地表示金属刺激电极并不总是很清楚。通过量化不同电极表示对模型轴突激活阈值的影响,我们为神经刺激电极的准确高效建模提供了建议。我们在COMSOL Multiphysics中针对单极、双极和多极电极设计量化了神经刺激电流源不同表示的影响。我们建议将每个电极触点建模为一个薄铂域,用硅酮的电导率对电极基板进行建模,并在每个电极触点的中心使用点电流源或使用边界电流源。或者,为了避免与大范围电导率值(即铂和硅酮)相关的可能数值不稳定性,并消除薄电极触点所需的小网格单元,可以通过在基板与周围介质之间以及基板内部使用绝缘边界来将电极基板的电导率指定为铂,以将触点彼此隔离。在对多个触点进行建模时,我们建议通过对每个触点分别求解模型、使非活动触点悬空并叠加所得电位来使用叠加法。我们在一个简化模型(均匀各向同性介质中的电极)以及大鼠脊髓刺激(SCS)和人类深部脑刺激的实际模型中计算了不同实现方式下激活阈值的可比误差,表明所推荐的方法适用于不同的刺激靶点。