Please use this identifier to cite or link to this item: https://doi.org/10.3389/fncom.2020.00050
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dc.titleUnveiling Stimulation Secrets of Electrical Excitation of Neural Tissue Using a Circuit Probability Theory
dc.contributor.authorWang, H
dc.contributor.authorWang, J
dc.contributor.authorThow, XY
dc.contributor.authorLee, S
dc.contributor.authorPeh, WYX
dc.contributor.authorNg, KA
dc.contributor.authorHe, T
dc.contributor.authorThakor, NV
dc.contributor.authorLee, C
dc.date.accessioned2021-04-20T03:08:00Z
dc.date.available2021-04-20T03:08:00Z
dc.date.issued2020-07-10
dc.identifier.citationWang, 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
dc.identifier.issn16625188
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/189841
dc.description.abstractElectrical 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.
dc.publisherFrontiers Media SA
dc.sourceElements
dc.subjectcircuit-probability theory
dc.subjectcomputational modeling
dc.subjectelectric nerve stimulation
dc.subjectinductor in neural circuit
dc.subjectmathematical model
dc.typeArticle
dc.date.updated2021-04-15T06:34:07Z
dc.contributor.departmentELECTRICAL AND COMPUTER ENGINEERING
dc.contributor.departmentLIFE SCIENCES INSTITUTE
dc.description.doi10.3389/fncom.2020.00050
dc.description.sourcetitleFrontiers in Computational Neuroscience
dc.description.volume14
dc.description.page50-
dc.published.statePublished
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