A 16-channel Si probe monolithically integrated with CMOS chips for neural recording

IF 6.5 Q1 BIOTECHNOLOGY & APPLIED MICROBIOLOGY
Guang-Yang Gou , Changhua You , Pan Yao , Yu-Sen Guo , Tie-Zhu Liu , Zi-Xuan Song , Ben-Yuan He , MingHui Yin , Xuan Zhang , Chunxiu Liu , Jun Zhou , Xuan Sun , Chengyu Zhuang , Yuan-Dong Gu , Lei Yao , Ning Xue , Ming Zhao
{"title":"A 16-channel Si probe monolithically integrated with CMOS chips for neural recording","authors":"Guang-Yang Gou ,&nbsp;Changhua You ,&nbsp;Pan Yao ,&nbsp;Yu-Sen Guo ,&nbsp;Tie-Zhu Liu ,&nbsp;Zi-Xuan Song ,&nbsp;Ben-Yuan He ,&nbsp;MingHui Yin ,&nbsp;Xuan Zhang ,&nbsp;Chunxiu Liu ,&nbsp;Jun Zhou ,&nbsp;Xuan Sun ,&nbsp;Chengyu Zhuang ,&nbsp;Yuan-Dong Gu ,&nbsp;Lei Yao ,&nbsp;Ning Xue ,&nbsp;Ming Zhao","doi":"10.1016/j.snr.2024.100206","DOIUrl":null,"url":null,"abstract":"<div><p>Multi-channel neural electrodes as a crucial means are of great significance for information exchange between the brain and computers. Herein, we present a 16-channel Si-based active neural probe system that achieves a monolithic integration between the electrodes and circuits in a single probe, making it a standalone integrated electrophysiology recording system. The ASIC prepared on a base (<span><math><mrow><mn>2</mn><mspace></mspace><mo>×</mo><mspace></mspace><mn>2</mn><mspace></mspace><mi>m</mi><msup><mrow><mi>m</mi></mrow><mn>2</mn></msup></mrow></math></span>) is a 16-channel analog frontend (AFE) for neural recording, and each channel has a low-noise amplifier (LNA), a bandpass filter (BPF), a buffer and a current bias circuit. The 258 neural signal recording electrodes (<span><math><mrow><mn>22</mn><mspace></mspace><mo>×</mo><mspace></mspace><mn>24</mn><mspace></mspace><mi>μ</mi><msup><mrow><mi>m</mi></mrow><mn>2</mn></msup></mrow></math></span>) are densely packed on a 50 μm thick, 100 μm wide, and 3 mm long shank. The ASIC of neural probe, internal interconnecting wires are all implemented in commercial SMIC 0.18 μm CMOS technology. The neural probe system achieves a 3.6 μV<sub>rms</sub> input-referred noise (IRN) in a bandwidth of 1.1Hz-10 kHz, 70.8 μW power consumption, 0.0785 mm<sup>2</sup> area per channel, as well as an AFE gain of 58.1 dB Furthermore, the impedances of the Au electrodes can be obtained as 0.5–2.1 MΩ at a frequency of 1 kHz. The functionality of a 16-channel silicon-based neural probe is validated in an in-vivo experiment on lab rats.</p></div>","PeriodicalId":426,"journal":{"name":"Sensors and Actuators Reports","volume":"8 ","pages":"Article 100206"},"PeriodicalIF":6.5000,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666053924000225/pdfft?md5=c1e13733680810a35fc396ccb92755a3&pid=1-s2.0-S2666053924000225-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sensors and Actuators Reports","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666053924000225","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOTECHNOLOGY & APPLIED MICROBIOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Multi-channel neural electrodes as a crucial means are of great significance for information exchange between the brain and computers. Herein, we present a 16-channel Si-based active neural probe system that achieves a monolithic integration between the electrodes and circuits in a single probe, making it a standalone integrated electrophysiology recording system. The ASIC prepared on a base (2×2mm2) is a 16-channel analog frontend (AFE) for neural recording, and each channel has a low-noise amplifier (LNA), a bandpass filter (BPF), a buffer and a current bias circuit. The 258 neural signal recording electrodes (22×24μm2) are densely packed on a 50 μm thick, 100 μm wide, and 3 mm long shank. The ASIC of neural probe, internal interconnecting wires are all implemented in commercial SMIC 0.18 μm CMOS technology. The neural probe system achieves a 3.6 μVrms input-referred noise (IRN) in a bandwidth of 1.1Hz-10 kHz, 70.8 μW power consumption, 0.0785 mm2 area per channel, as well as an AFE gain of 58.1 dB Furthermore, the impedances of the Au electrodes can be obtained as 0.5–2.1 MΩ at a frequency of 1 kHz. The functionality of a 16-channel silicon-based neural probe is validated in an in-vivo experiment on lab rats.

用于神经记录的与 CMOS 芯片单片集成的 16 通道硅探针
多通道神经电极作为一种重要手段,对大脑与计算机之间的信息交流具有重要意义。在这里,我们介绍一种基于硅的 16 通道有源神经探针系统,该系统实现了电极和电路在单个探针中的单片集成,使其成为独立的集成电生理记录系统。在底座(2×2 平方毫米)上制备的 ASIC 是用于神经记录的 16 通道模拟前端(AFE),每个通道都有一个低噪声放大器(LNA)、一个带通滤波器(BPF)、一个缓冲器和一个电流偏置电路。258 个神经信号记录电极(22×24μm2)密集排列在一个厚 50 μm、宽 100 μm、长 3 mm 的柄上。神经探针的 ASIC 和内部互连线均采用 0.18 μm CMOS 商业 SMIC 技术实现。神经探针系统在 1.1Hz-10 kHz 的带宽内实现了 3.6 μVrms 的输入参考噪声(IRN),功耗为 70.8 μW,每个通道的面积为 0.0785 平方毫米,AFE 增益为 58.1 dB,此外,金电极的阻抗在 1 kHz 频率下可达到 0.5-2.1 MΩ。16 通道硅基神经探针的功能在实验鼠的体内实验中得到了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
9.60
自引率
0.00%
发文量
60
审稿时长
49 days
期刊介绍: Sensors and Actuators Reports is a peer-reviewed open access journal launched out from the Sensors and Actuators journal family. Sensors and Actuators Reports is dedicated to publishing new and original works in the field of all type of sensors and actuators, including bio-, chemical-, physical-, and nano- sensors and actuators, which demonstrates significant progress beyond the current state of the art. The journal regularly publishes original research papers, reviews, and short communications. For research papers and short communications, the journal aims to publish the new and original work supported by experimental results and as such purely theoretical works are not accepted.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信