2018/04/30 by Hao Wang, Wang, Hao, Jiahui Wang +15
Biochemistry, Genetics and Molecular Biology · Engineering · Neuroscience · #EEG and Brain-Computer Interfaces #FOS: Biological sciences #Muscle activation and electromyography studies #Neurons and Cognition (q-bio.NC) #Neuroscience and Neural Engineering #q-bio.NC
paper · pdf · doi:10.48550/arxiv.1804.11310
openalex publication_date 2018/04/30 · openalex created_date 2018/05/07 · arxiv created 2018/06/14 · arxiv updated 2018/06/15 · openalex updated_date 2026/07/28
A new theory, named the Circuit-Probability theory, is proposed to unveil the secret of electrical nerve stimulation, essentially explain the nonlinear and resonant phenomena observed when neural and non-neural tissues are electrically stimulated. For the explanation of frequency dependent response, an inductor is involved in the neural circuit model. Furthermore, predicted response to varied stimulation strength is calculated stochastically. Based on this theory, many empirical models, such as strength-duration relationship and LNP model, can be theoretically explained, derived, and amended. This theory can explain the complex nonlinear interactions in electrical stimulation and fit in vivo experiment data on stimulation-responses of many experiments. As such, the C-P theory should be able to guide novel experiments and more importantly, offer an in-depth physical understanding of the neural tissue. As a promising neural model, we can even further explore the more accurate circuit configuration and probability equation to better describe the electrical stimulation of neural tissues in the future.