Advanced neuroprosthetic electrode design optimized by electromagnetic finite element simulation: innovations and applications

Front Bioeng Biotechnol. 2024 Nov 6:12:1476447. doi: 10.3389/fbioe.2024.1476447. eCollection 2024.

Abstract

Based on electrophysiological activity, neuroprostheses can effectively monitor and control neural activity. Currently, electrophysiological neuroprostheses are widely utilized in treating neurological disorders, particularly in restoring motor, visual, auditory, and somatosensory functions after nervous system injuries. They also help alleviate inflammation, regulate blood pressure, provide analgesia, and treat conditions such as epilepsy and Alzheimer's disease, offering significant research, economic, and social value. Enhancing the targeting capabilities of neuroprostheses remains a key objective for researchers. Modeling and simulation techniques facilitate the theoretical analysis of interactions between neuroprostheses and the nervous system, allowing for quantitative assessments of targeting efficiency. Throughout the development of neuroprostheses, these modeling and simulation methods can save time, materials, and labor costs, thereby accelerating the rapid development of highly targeted neuroprostheses. This article introduces the fundamental principles of neuroprosthesis simulation technology and reviews how various simulation techniques assist in the design and performance enhancement of neuroprostheses. Finally, it discusses the limitations of modeling and simulation and outlines future directions for utilizing these approaches to guide neuroprosthesis design.

Keywords: finite element model; neural electrode; neuron simulation; neuroprosthesis; neuroprosthesis simulation.

Publication types

  • Review

Grants and funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This research was supported by Scientific and Technological Innovation 2030 Key Project (2022ZD0209800), Natural Science Foundation of China Grants (31930047), National Key R&D Program of China (2020YFC2008503), the Strategic Priority Research Program of Chinese Academy of Science (XDB32030103), National Special Support Grant (W02020453), NSFC-Guangdong Joint Fund (U20A6005), Key- Area Research and Development Program of Guangdong Province (2018B030331001 and 2018B030338001), Shenzhen Infrastructure for Brain Analysis and Modeling (ZDKJ20190204002).