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Unveiling Stimulation Secrets of Electrical Excitation of Neural Tissue Using a Circuit Probability Theory
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dc.contributor.author Wang, Hao ko
dc.contributor.author Wang, Jiahui ko
dc.contributor.author Thow, Xin Yuan ko
dc.contributor.author Lee, SangHoon ko
dc.contributor.author Peh, Wendy Yen Xian ko
dc.contributor.author Ng, Kian Ann ko
dc.contributor.author He, Tianyiyi ko
dc.contributor.author Thakor, Nitish, V ko
dc.contributor.author Lee, Chengkuo ko
dc.date.accessioned 2020-08-24T07:11:46Z -
dc.date.available 2020-08-24T07:11:46Z -
dc.date.created 2020-08-04 -
dc.date.issued 2020-07 -
dc.identifier.citation Frontiers in Computational Neuroscience, v.14, no.50, pp.1 - 10 -
dc.identifier.issn 1662-5188 -
dc.identifier.uri http://hdl.handle.net/20.500.11750/12337 -
dc.description.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. -
dc.language English -
dc.publisher Frontiers Media SA -
dc.title Unveiling Stimulation Secrets of Electrical Excitation of Neural Tissue Using a Circuit Probability Theory -
dc.type Article -
dc.identifier.doi 10.3389/fncom.2020.00050 -
dc.identifier.wosid 000555873900001 -
dc.identifier.scopusid 2-s2.0-85088525925 -
dc.type.local Article(Overseas) -
dc.type.rims ART -
dc.identifier.bibliographicCitation Wang, Hao. (2020-07). Unveiling Stimulation Secrets of Electrical Excitation of Neural Tissue Using a Circuit Probability Theory. doi: 10.3389/fncom.2020.00050 -
dc.description.journalClass 1 -
dc.contributor.nonIdAuthor Wang, Hao -
dc.contributor.nonIdAuthor Wang, Jiahui -
dc.contributor.nonIdAuthor Thow, Xin Yuan -
dc.contributor.nonIdAuthor Peh, Wendy Yen Xian -
dc.contributor.nonIdAuthor Ng, Kian Ann -
dc.contributor.nonIdAuthor He, Tianyiyi -
dc.contributor.nonIdAuthor Thakor, Nitish, V -
dc.contributor.nonIdAuthor Lee, Chengkuo -
dc.identifier.citationVolume 14 -
dc.identifier.citationNumber 50 -
dc.identifier.citationStartPage 1 -
dc.identifier.citationEndPage 10 -
dc.identifier.citationTitle Frontiers in Computational Neuroscience -
dc.type.journalArticle Article -
dc.description.isOpenAccess Y -
dc.subject.keywordAuthor electric nerve stimulation -
dc.subject.keywordAuthor mathematical model -
dc.subject.keywordAuthor circuit-probability theory -
dc.subject.keywordAuthor computational modeling -
dc.subject.keywordAuthor inductor in neural circuit -
dc.subject.keywordPlus NERVE -
dc.subject.keywordPlus MODEL -
dc.subject.keywordPlus FIBERS -
dc.subject.keywordPlus DAMAGE -
dc.subject.keywordPlus FIELD -
dc.contributor.affiliatedAuthor Lee, SangHoon -
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