The effect of the subthreshold oscillation induced by the neurons' resonance upon the electrical stimulation-dependent instability

Shoujun Yu; Wenji Yue; Tianruo Guo; Yonghong Liu; Yapeng Zhang; Sara Khademi; Tian Zhou; Zhen Xu; Bing Song; Tianzhun Wu; Fenglin Liu; Yanlong Tai; Xuefei Yu; Hao Wang

doi:10.3389/fnins.2023.1178606

The effect of the subthreshold oscillation induced by the neurons' resonance upon the electrical stimulation-dependent instability

Front Neurosci. 2023 May 9:17:1178606. doi: 10.3389/fnins.2023.1178606. eCollection 2023.

Authors

Shoujun Yu^#^{1

2}, Wenji Yue^#², Tianruo Guo^#³, Yonghong Liu², Yapeng Zhang^{2

4}, Sara Khademi^{2

5}, Tian Zhou², Zhen Xu², Bing Song², Tianzhun Wu^{2

6}, Fenglin Liu², Yanlong Tai², Xuefei Yu¹, Hao Wang²

Affiliations

¹ School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
² Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Sciences (CAS), Shenzhen, China.
³ Graduate School of Biomedical Engineering, University of New South Wales, Sydney, NSW, Australia.
⁴ School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
⁵ Institute of Polymeric Materials, Sahand University of Technology, Tabriz, Iran.
⁶ Key Laboratory of Health Bioinformatics, Chinese Academy of Sciences (CAS), Shenzhen, China.

^# Contributed equally.

Abstract

Repetitive electrical nerve stimulation can induce a long-lasting perturbation of the axon's membrane potential, resulting in unstable stimulus-response relationships. Despite being observed in electrophysiology, the precise mechanism underlying electrical stimulation-dependent (ES-dependent) instability is still an open question. This study proposes a model to reveal a facet of this problem: how threshold fluctuation affects electrical nerve stimulations. This study proposes a new method based on a Circuit-Probability theory (C-P theory) to reveal the interlinkages between the subthreshold oscillation induced by neurons' resonance and ES-dependent instability of neural response. Supported by in-vivo studies, this new model predicts several key characteristics of ES-dependent instability and proposes a stimulation method to minimize the instability. This model provides a powerful tool to improve our understanding of the interaction between the external electric field and the complexity of the biophysical characteristics of axons.

Keywords: Circuit-Probability theory; neural modeling; neural oscillation; subthreshold oscillation; threshold fluctuation.

Grants and funding

This work was supported by the grants from Guangdong Research Program (2019A1515110843), Shenzhen Research Program (GJHZ20200731095206018, JCYJ20210324101610028, JCYJ20180507182057026, and JCYJ20210324101603009), National Natural Science Foundation of China grants (31800871, 82171082, and 62071459), and National Key Research and Development Program of China (2022YFF1202500 and 2022YFF1202502).