IEEE Trans Biomed Eng. 2019 Feb;66(2):471-484. doi: 10.1109/TBME.2018.2849220. Epub 2018 Jun 20.
Currently, there is no imaging method that is able to distinguish the functional activity inside nerves. Such a method would be essential for understanding peripheral nerve physiology and would allow precise neuromodulation of organs these nerves supply. Electrical impedance tomography (EIT) is a method that produces images of electrical impedance change (dZ) of an object by injecting alternating current and recording surface voltages. It has been shown to be able to image fast activity in the brain and large peripheral nerves. To image inside small autonomic nerves, mostly containing unmyelinated fibers, it is necessary to maximize SNR and optimize the EIT parameters. An accurate model of the nerve is required to identify these optimal parameters as well as to validate data obtained in the experiments.
In this study, we developed two three-dimensional models of unmyelinated fibers: Hodgkin-Huxley (HH) squid giant axon (single and multiple) and mammalian C-nociceptor. A coupling feedback system was incorporated into the models to simulate direct and alternating current application and simultaneously record external field during action potential propagation.
Parameters of the developed models were varied to study their influence on the recorded impedance changes; the optimal parameters were identified. The negative dZ was found to monotonically decrease with frequency for both HH and C fiber models, in accordance with the experimental data.
The accurate realistic model of unmyelinated nerve allows the optimization of EIT parameters and matches literature and experimental results.
目前，尚无能够区分神经内功能活动的成像方法。这种方法对于理解周围神经生理学至关重要，并能实现对这些神经所支配器官的精确神经调节。电阻抗断层成像（EIT）是一种通过注入交流电并记录表面电压来产生物体电阻抗变化（dZ）图像的方法。它已被证明能够对大脑和大周围神经的快速活动进行成像。为了对主要包含无髓纤维的小自主神经进行成像，有必要最大化信噪比并优化 EIT 参数。需要准确的神经模型来识别这些最佳参数，并验证实验中获得的数据。
在这项研究中，我们开发了两种无髓纤维的三维模型：Hodgkin-Huxley（HH）鱿鱼巨轴突（单根和多根）和哺乳动物 C 伤害感受器。我们将耦合反馈系统纳入模型中，以模拟直接和交流电应用，并在动作电位传播过程中同时记录外部场。
我们改变了所开发模型的参数以研究它们对记录阻抗变化的影响；确定了最佳参数。HH 和 C 纤维模型的负 dZ 均随频率单调下降，与实验数据一致。
无髓神经的精确现实模型允许 EIT 参数的优化，并与文献和实验结果相匹配。
