Please use this identifier to cite or link to this item: https://doi.org/10.3389/fncom.2020.00050
Title: Unveiling Stimulation Secrets of Electrical Excitation of Neural Tissue Using a Circuit Probability Theory
Authors: Wang, H
Wang, J 
Thow, XY 
Lee, S 
Peh, WYX 
Ng, KA 
He, T 
Thakor, NV 
Lee, C 
Keywords: circuit-probability theory
computational modeling
electric nerve stimulation
inductor in neural circuit
mathematical model
Issue Date: 10-Jul-2020
Publisher: Frontiers Media SA
Citation: Wang, H, Wang, J, Thow, XY, Lee, S, Peh, WYX, Ng, KA, He, T, Thakor, NV, Lee, C (2020-07-10). Unveiling Stimulation Secrets of Electrical Excitation of Neural Tissue Using a Circuit Probability Theory. Frontiers in Computational Neuroscience 14 : 50-. ScholarBank@NUS Repository. https://doi.org/10.3389/fncom.2020.00050
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.
Source Title: Frontiers in Computational Neuroscience
URI: https://scholarbank.nus.edu.sg/handle/10635/189841
ISSN: 16625188
DOI: 10.3389/fncom.2020.00050
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