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Unveiling Stimulation Secrets of Electrical Excitation of Neural Tissue Using a Circuit Probability Theory
Frontiers in Computational Neuroscience ( IF 2.1 ) Pub Date : 2020-07-10 , DOI: 10.3389/fncom.2020.00050
Hao Wang 1, 2, 3, 4 , Jiahui Wang 2, 3, 4, 5 , Xin Yuan Thow 5 , Sanghoon Lee 2, 3, 4, 5, 6 , Wendy Yen Xian Peh 5 , Kian Ann Ng 5 , Tianyiyi He 2, 3, 4 , Nitish V Thakor 5 , Chengkuo Lee 2, 3, 4, 5, 7
Affiliation  

Electrical excitation of neural tissue has wide applications, but how electrical stimulation interacts with neural tissue remains to be elucidated. Here, we propose a new theory, named the Circuit-Probability theory, to reveal how this physical interaction happen. The relation between the electrical stimulation input and the neural response can be theoretically calculated. We show that many empirical models, including strength-duration relationship and linear-non-linear-Poisson model, can be theoretically explained, derived, and amended using our theory. Furthermore, this theory can explain the complex non-linear and resonant phenomena and fit in vivo experiment data. In this letter, we validated an entirely new framework to study electrical stimulation on neural tissue, which is to simulate voltage waveforms using a parallel RLC circuit first, and then calculate the excitation probability stochastically.

中文翻译:

使用电路概率理论揭示神经组织电激发的刺激秘密

神经组织的电激发具有广泛的应用,但电刺激如何与神经组织相互作用仍有待阐明。在这里,我们提出了一个名为电路概率理论的新理论,以揭示这种物理相互作用是如何发生的。可以从理论上计算电刺激输入和神经反应之间的关系。我们表明,许多经验模型,包括强度-持续时间关系和线性-非线性-泊松模型,都可以使用我们的理论进行理论解释、推导和修正。此外,该理论可以解释复杂的非线性和共振现象并拟合体内实验数据。在这封信中,我们验证了一个全新的框架来研究神经组织的电刺激,即首先使用并行 RLC 电路模拟电压波形,
更新日期:2020-07-10
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