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首页> 外文期刊>Neuroinformatics >PyPNS: Multiscale Simulation of a Peripheral Nerve in Python
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PyPNS: Multiscale Simulation of a Peripheral Nerve in Python

机译：Python中的周围神经的多尺度模拟

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Bioelectronic Medicines that modulate the activity patterns on peripheral nerves have promise as a new way of treating diverse medical conditions from epilepsy to rheumatism. Progress in the field builds upon time consuming and expensive experiments in living organisms. To reduce experimentation load and allow for a faster, more detailed analysis of peripheral nerve stimulation and recording, computational models incorporating experimental insights will be of great help. We present a peripheral nerve simulator that combines biophysical axon models and numerically solved and idealised extracellular space models in one environment. We modelled the extracellular space as a three-dimensional resistive continuum governed by the electro-quasistatic approximation of the Maxwell equations. Potential distributions were precomputed in finite element models for different media (homogeneous, nerve in saline, nerve in cuff) and imported into our simulator. Axons, on the other hand, were modelled more abstractly as one-dimensional chains of compartments. Unmyelinated fibres were based on the Hodgkin-Huxley model; for myelinated fibres, we adapted the model proposed by McIntyre et al. in 2002 to smaller diameters. To obtain realistic axon shapes, an iterative algorithm positioned fibres along the nerve with a variable tortuosity fit to imaged trajectories. We validated our model with data from the stimulated rat vagus nerve. Simulation results predicted that tortuosity alters recorded signal shapes and increases stimulation thresholds. The model we developed can easily be adapted to different nerves, and may be of use for Bioelectronic Medicine research in the future.
机译：调节外周神经的活性模式的生物电子药物承诺作为治疗从癫痫到风湿病的多样化病症的新方式。在生物体中的耗时和昂贵的实验时，该领域的进展构建。为了减少实验载荷并允许更快，更详细地分析周围神经刺激和记录，并入实验洞察的计算模型将具有很大的帮助。我们提出了一个周围神经模拟器，它在一个环境中结合了生物物理轴突模型和数值溶解的细胞外空间模型。我们将细胞外空间建模为由麦克斯韦方程的电Quasistatic近似控制的三维电阻连续体。潜在的分布在不同培养基的有限元模型中预先计算（营养盐，袖口中的盐水，神经）并进口到我们的模拟器中。另一方面，轴突被更加抽象地建模为单位的隔间一维链。未键合的纤维基于Hodgkin-Huxley模型;对于髓纤维，我们改编了McIntyre等人提出的模型。 2002年到较小的直径。为了获得现实的轴突形状，迭代算法沿着神经定位的纤维，其可变曲折度适合成像轨迹。我们通过来自受刺激的大鼠迷走神经的数据验证了我们的模型。仿真结果预测，曲折化改变了记录的信号形状并增加刺激阈值。我们开发的型号可以很容易地适应不同的神经，并且可以在未来使用生物电子医学研究。

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