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A cell-electrode interface signal-to-noise ratio model for 3D micro-nano electrode
Shuqing Yin1, Yang Li1, Ruoyu Lu1
1Key Laboratory for Micro/Nano Technology and System of Liaoning Province, Dalian University of Technology, Dalian, People's Republic of China.
Journal of Neural Engineering
|July 20, 2023
Summary
Three-dimensional micro-nano electrodes (MNEs) improve neural recording signal-to-noise ratio (SNR) when cells adhere sufficiently. Optimal MNE design minimizes nanopillar spacing and height while maximizing radius for enhanced neural signal quality.
Area of Science:
- Neural Engineering
- Biophysics
- Materials Science
Background:
- Three-dimensional micro-nano electrodes (MNEs) with vertical nanopillar arrays are crucial for neural science.
- Geometric parameters and cell adhesion influence MNE recording performance.
- The precise relationship between these factors and signal-to-noise ratio (SNR) remains undefined.
Purpose of the Study:
- To establish a quantitative model for the cell-MNE interface SNR.
- To determine the mathematical relationship between MNE geometric parameters, cell adhesion, and SNR.
- To provide a theoretical basis for designing advanced neural electrodes.
Main Methods:
- Utilized equivalent electrical circuit analysis and numerical simulations.
- Quantified cell adhesion using engulfment percentage.
- Introduced an equivalent cleft width to model signal loss due to cell-electrode gaps.
Main Results:
- MNEs outperform planar electrodes in SNR only when cell engulfment percentage exceeds a specific threshold.
- Maximal cell adhesion requires minimized nanopillar spacing and height for superior signal quality.
- Maximal nanopillar radius is beneficial for signal quality under maximum engulfment.
Conclusions:
- The developed model elucidates how nanopillar arrays enhance SNR in neural recordings.
- Findings offer theoretical guidance for optimizing the design of MNEs for neural interfaces.
- This research facilitates the development of more effective neural recording technologies.
