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

拟议努力的目标是开发并向科学界提供一个模块， 集成的，多尺度的计算建模框架，将允许用户设计安全， 有效的外周神经刺激器多尺度计算框架是基于无缝 特别适合集成的多个计算模块/平台的集成：（a）多个 分辨率，频域，大规模电磁场建模平台，基于我们的 导纳/阻抗法（AM/IM）用于预测神经元中感应的场和电流 （B）通过任意神经刺激器的体电和组织的微米分辨率计算模型; 磁特性的轴突和他们的兴奋在周围神经模型的神经元使用 NEURON软件，在空间和时间上与导纳/阻抗方法相结合;（c）计算 用于估计直接、电或磁诱导的组织和神经损伤的工具， 任意、用户定义的外周神经刺激器和波形，以及活动估计- 早期轴突损伤（EAD）与实验观察到的损伤相关， 长期植入的神经刺激器拟议模块的开发将提供最多的 完整的预测性软件框架可用于评估外周血管的急性和基于活动的安全性 神经刺激器的参数，包括电极几何特征、电荷密度、 相位、刺激频率和热增加。 据我们所知，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（由于任意的神经刺激器， 电极几何形状和波形）和神经刺激器的安全性， （基于高分辨率，基于介电特性， 离散计算模型）和微米分辨率（神经级）。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;和c）实验验证的预测能力， 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.