CRCNS: US-Spain Research Proposal: Computational Modeling of PNS Stimulation

拟议工作的目标是开发并向科学界提供一个模块， 集成的多尺度计算建模框架，允许用户设计安全和 有效的外周神经刺激剂。多尺度计算框架是基于无缝 集成特别适合于集成的多个计算模块/平台：(A)多个 基于我们的分辨率、频域、大规模的电磁场建模平台 用导纳/阻抗法(AM/IM)预测神经元中感应的电场和电流 组织由任意神经刺激器；(B)微米分辨率计算模型的块状电学和 哺乳动物周围神经模型中轴突的磁性及其兴奋作用 神经元软件，在空间和时间上耦合到导纳/阻抗法；(C)计算 用于估计因以下原因引起的直接、电磁或磁致组织和神经损伤的工具 任意的、用户定义的外周神经刺激器和波形以及对活动的估计- 基于早期轴突损伤(EAD)与实验观察到的损伤的相关性 长期植入的神经刺激器。拟议模块的开发将提供最多 提供完整的预测性软件框架，用于评估外周设备的急性和基于活动的安全性 神经刺激器的参数，包括电极几何形状：：AL特征、电荷密度、电荷单位 时相、刺激频率和体温升高。 据我们所知，目前还没有现成的计算方法来解决这两个问题 神经刺激器的有效性(由于随意性而导致的周围神经模型中的兴奋建模 电极几何形状和波形)和神经刺激器的安全性 (人体的电磁组织模型基于高分辨率、基于介电特性、 离散的计算模型)和微米级的分辨率(神经级别)。拟议的努力将 包括a)生成周围神经的计算模型；b)开发 计算模块和平台；以及c)对预测能力的实验验证 计算模型和平台。

The goal of the proposed effort is to develop and make available to the scientific community a modular, integrated, multiscale computational modeling framework that will allow the user to design safe and effective peripheral neurostimulators. The multiscale computational framework is based on the seamless integration of multiple computational modules/platforms particularly suited for integration: (a) a multi- resolution, frequency-domain, large-scale electromagnetic field modeling platform based upon our Admittance/Impedance Method (AM/IM) for the prediction of fields and currents induced in the neural tissue by arbitrary neurostimulators; (b) micron-resolution computational models of the bulk electrical and magnetic properties of axons and their excitation in peripheral nerve models of mammalians using NEURON software, coupled in space and time to the Admittance/Impedance Method; (c) a computational tool for the estimation of direct, electrically or magnetically-induced, tissue and neural damage due to arbitrary, user-defined, peripheral neurostimulators and waveforms and for the estimation of activity- based early axonal damage (EAD) based on correlation with experimentally observed damage in chronically implanted neurostimulators. The development of the proposed modules will provide the most complete predictive software framework available to assess acute and activity-based safety of peripheral neurostimulators due to parameters including electrode geometric::al features, charge density, charge per phase, frequency of stimulation and thermal increase. To the best of our knowledge, there is no computational method readily available that addresses both the effectiveness of the neurostimulator (modeling of the excitation in peripheral nerve models due to arbitrary electrode geometries and waveforms) and the safety of the neurostimulator both at the large-scale (electromagnetic tissue models of the human body based on high-resolution, dielectric properties- based, discretized computational models) and at micron-resolution (neural level). The proposed effort will consists of a) generation of computational models of peripheral nerves; b) development of the computational modules and platform; and c) experimental verification of the predictive capabilities of the computational models and platform.