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Unveiling Stimulation Secrets of Electrical Excitation of Neural Tissue Using a Circuit Probability Theory.
Wang, Hao; Wang, Jiahui; Thow, Xin Yuan; Lee, Sanghoon; Peh, Wendy Yen Xian; Ng, Kian Ann; He, Tianyiyi; Thakor, Nitish V; Lee, Chengkuo.
Afiliação
  • Wang H; Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Sciences (CAS), Shenzhen, China.
  • Wang J; Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore.
  • Thow XY; Center for Intelligent Sensor and MEMS, National University of Singapore, Singapore, Singapore.
  • Lee S; Hybrid Integrated Flexible Electronic Systems, National University of Singapore, Singapore, Singapore.
  • Peh WYX; Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore.
  • Ng KA; Center for Intelligent Sensor and MEMS, National University of Singapore, Singapore, Singapore.
  • He T; Hybrid Integrated Flexible Electronic Systems, National University of Singapore, Singapore, Singapore.
  • Thakor NV; Singapore Institute for Neurotechnology (SINAPSE), National University of Singapore, Singapore, Singapore.
  • Lee C; Singapore Institute for Neurotechnology (SINAPSE), National University of Singapore, Singapore, Singapore.
Front Comput Neurosci ; 14: 50, 2020.
Article em En | MEDLINE | ID: mdl-32754023
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Comput Neurosci Ano de publicação: 2020 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Front Comput Neurosci Ano de publicação: 2020 Tipo de documento: Article País de afiliação: China