A cell–electrode interface signal-to-noise ratio model for 3D micro-nano electrode

Author:

Yin ShuqingORCID,Li Yang,Lu Ruoyu,Guo LihuaORCID,Wang Yansheng,Liu ChongORCID,Li JingminORCID

Abstract

Abstract Objective. Three-dimensional micro-nano electrodes (MNEs) with the vertical nanopillar array distributed on the surface play an increasingly important role in neural science research. The geometric parameters of the nanopillar array and the cell adhesion state on the nanopillar array are the factors that may affect the MNE recording. However, the quantified relationship between these parameters and the signal-to-noise ratio (SNR) is still unclear. This paper establishes a cell–MNE interface SNR model and obtains the mathematical relationship between the above parameters and SNR. Approach. The equivalent electrical circuit and numerical simulation are used to study the sensing performance of the cell–electrode interface. The adhesion state of cells on MNE is quantified as engulfment percentage, and an equivalent cleft width is proposed to describe the signal loss caused by clefts between the cell membrane and the electrode surface. Main results. Whether the planar substrate is insulated or not, the SNR of MNE is greater than planar microelectrode only when the engulfment percentage is greater than a certain value. Under the premise of maximum engulfment percentage, the spacing and height of nanopillars should be minimized, and the radius of the nanopillar should be maximized for better signal quality. Significance. The model can clarify the mechanism of improving SNR by nanopillar arrays and provides the theoretical basis for the design of such nanopillar neural electrodes.

Funder

National Key R&D Program of China

Fundamental Research Funds for the Central Universities

Publisher

IOP Publishing

Subject

Cellular and Molecular Neuroscience,Biomedical Engineering

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3