Unveiling Stimulation Secrets of Electrical Excitation of Neural Tissue Using a Circuit Probability Theory
Authors: Jiahui Wang
Nitish V Thakor
Wendy Yen Xian Peh
Sanghoon Lee
Hao Wang
Kian Ann Ng
Tianyiyi He
Chengkuo Lee
Xin Yuan Thow
Journal: Frontiers in Computational Neuroscience (2020)
Discipline: NEUROSCIENCE & BEHAVIOR
Keywords: circuit-probability theory; computational modeling; electric nerve stimulation; inductor in neural circuit; mathematical model.
Affiliations: Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Sciences (CAS), Shenzhen, China., Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore., Center for Intelligent Sensor and MEMS, National University of Singapore, Singapore, Singapore., Hybrid Integrated Flexible Electronic Systems, National University of Singapore, Singapore, Singapore., Singapore Institute for Neurotechnology (SINAPSE), National University of Singapore, Singapore, Singapore., Department of Robotics Engineering, Daegu Geongbuk Institute of Science and Technology (DGIST), Daegu, South Korea., NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore, Singapore.

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. 

Retracted: No

PubPeer comments:
 See brief discussion of the significance of the myelin  inductance in a biological setting (it seems to be completely negligible). https: pubpeer.com publications 63A1A96489BE82BE59CF10A04E6E40 , 
 As I commented in another post, the inductance discussed here is consisted with two parts: real inductance generated by the spiraling of the myelin, which is a small value; and an equivalent inductance generated by the flexoelectric effect (you can also consider is as a piezoelectric effect) of the lipid bilayer of cell membrane. Since in this paper, I only care about the electric characteristic of the neuron as a circuit, so the inductance from two origins are not distinguishable. But this paper was actually written several years ago (just published recently), at that time I still dont know what are the physical origins of this huge inductance. Now I know this huge inductance mainly comes from the flexoelectric effect (If you only care about the quantitative value). But the real inductance generated by the spiraling of myelin sheath can generate a magnetic field, which actually plays an importance role in the growth of myelin sheath (at least it affects the spiraling direction). ,