A local de-insulation method and its application in neural microneedle array

Silicon-based neural microneedle arrays, such as the Utah Array, have demonstrated excellent performance in chronic recordings from the cerebral cortex. Unlike planar thin-film electrodes with recording sites arranged on the surface of a silicon film, the recording sites of microneedle arrays are located at the tips of three-dimensional needles, which significantly complicates the fabrication process required for single-neuron recordings. To address this challenge, we develop a local de-insulation method for microneedle recording electrodes that eliminates the need for etching: the microneedle tips are encapsulated in a controllable-thickness protective layer, followed by deposition of a Parylene-C insulation layer. By optimizing the elasticity of the protection material, as well as its adhesion and shape on both the protective layer and the electrode shaft, we were able to precisely control the area of the removed insulated layers, resulting in consistent tip exposure. Experimental results show that the non-uniformity of the exposed microneedle recording sites in the silicon-based neural microelectrode arrays (each has 10 × 10 array) fabricated using this method is 3.32 ± 1.02%. Furthermore, the arrays exhibited high stability and reliability in both mechanical performance and electrical characteristics. They achieved an average spike signal-to-noise ratio of 12.63 ± 6.64 during in vivo testing. This fabrication technique provides a valuable method for the development of high-performance neural microelectrode array.

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Publication Details

Journal
Microsystems & Nanoengineering
Published
2025-05-26
DOI
https://doi.org/10.1038/s41378-025-00922-6
Primary Topic
Neuroscience and Neural Engineering
Type
article
Field-Weighted Citation Impact
0.00

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article

A local de-insulation method and its application in neural microneedle array

Zhaoxin Geng, Chunrong Wei, Daoben Zhu, Qiang Gui et al.
4 links
Microsystems & Nanoengineering
Neuroscience and Neural Engineering
article

A local de-insulation method and its application in neural microneedle array

Zhaoxin Geng, Chunrong Wei, Daoben Zhu, Qiang Gui, Jingfeng Zhou, Rongyu Tang, Weihua Pei, Guowei Han, Jin Ning, Xiaowei Yang, Xin Zhao, Yijun Wang
article en

Abstract

Silicon-based neural microneedle arrays, such as the Utah Array, have demonstrated excellent performance in chronic recordings from the cerebral cortex. Unlike planar thin-film electrodes with recording sites arranged on the surface of a silicon film, the recording sites of microneedle arrays are located at the tips of three-dimensional needles, which significantly complicates the fabrication process required for single-neuron recordings. To address this challenge, we develop a local de-insulation method for microneedle recording electrodes that eliminates the need for etching: the microneedle tips are encapsulated in a controllable-thickness protective layer, followed by deposition of a Parylene-C insulation layer. By optimizing the elasticity of the protection material, as well as its adhesion and shape on both the protective layer and the electrode shaft, we were able to precisely control the area of the removed insulated layers, resulting in consistent tip exposure. Experimental results show that the non-uniformity of the exposed microneedle recording sites in the silicon-based neural microelectrode arrays (each has 10 × 10 array) fabricated using this method is 3.32 ± 1.02%. Furthermore, the arrays exhibited high stability and reliability in both mechanical performance and electrical characteristics. They achieved an average spike signal-to-noise ratio of 12.63 ± 6.64 during in vivo testing. This fabrication technique provides a valuable method for the development of high-performance neural microelectrode array.

Microsystems & NanoengineeringVol. 11(1)
Minzu University of China (CN), Chinese Academy of Sciences (CN), Beijing Normal University (CN), State Key Laboratory on Integrated Optoelectronics (CN), Chinese Institute for Brain Research (CN), Institute of Semiconductors (CN), University of Chinese Academy of Sciences (CN), Xiangtan University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 87%
Neuroscience and Neural Engineering
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