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Unveiling Stimulation Secrets of Electrical Excitation of Neural Tissue Using a Circuit Probability Theory
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Title
Unveiling Stimulation Secrets of Electrical Excitation of Neural Tissue Using a Circuit Probability Theory
DGIST Authors
Lee, SangHoon
Issued Date
2020-07
Citation
Wang, Hao. (2020-07). Unveiling Stimulation Secrets of Electrical Excitation of Neural Tissue Using a Circuit Probability Theory. doi: 10.3389/fncom.2020.00050
Type
Article
Article Type
Article
Author Keywords
electric nerve stimulationmathematical modelcircuit-probability theorycomputational modelinginductor in neural circuit
Keywords
NERVEMODELFIBERSDAMAGEFIELD
ISSN
1662-5188
Abstract
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. © Copyright © 2020 Wang, Wang, Thow, Lee, Peh, Ng, He, Thakor and Lee.
URI
http://hdl.handle.net/20.500.11750/12337
DOI
10.3389/fncom.2020.00050
Publisher
Frontiers Media SA
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Lee, Sanghoon이상훈

Department of Robotics and Mechatronics Engineering

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