A 77-dB DR 16-Ch 2nd-order Δ-ΔΣ Neural Recording Chip with 0.0077mm2/Ch

Shiwei Wang, M. Ballini, Xiaolin Yang, C. Sawigun, J. Weijers, Dwaipayan Biswas, C. Lopez
{"title":"A 77-dB DR 16-Ch 2nd-order Δ-ΔΣ Neural Recording Chip with 0.0077mm2/Ch","authors":"Shiwei Wang, M. Ballini, Xiaolin Yang, C. Sawigun, J. Weijers, Dwaipayan Biswas, C. Lopez","doi":"10.23919/VLSICircuits52068.2021.9492482","DOIUrl":null,"url":null,"abstract":"This paper presents a scalable 16-channel neural recording chip enabling simultaneous acquisition of action-potentials (APs), local-field potentials (LFPs), electrode DC offsets (EDOs) and stimulation artifacts (SAs) without saturation. By combining a DC-coupled Δ-ΔΣ architecture with new bootstrapping and chopping schemes, the proposed readout IC achieves an area of 0.0077mm2 per channel, an input-referred noise of 5.53±0.36µVrms in the AP band and 2.88±0.18µVrms in the LFP band, a dynamic range (DR) of 77dB, an EDO tolerance of ±70mV and an input impedance of 283MΩ. The chip has been validated in an in vitro setting, demonstrating the capability to record extracellular signals even when using small, high-impedance electrodes. Because of the small area achieved, this architecture can be used to implement ultra-high-density neural probes for large-scale electrophysiology.","PeriodicalId":106356,"journal":{"name":"2021 Symposium on VLSI Circuits","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 Symposium on VLSI Circuits","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/VLSICircuits52068.2021.9492482","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

This paper presents a scalable 16-channel neural recording chip enabling simultaneous acquisition of action-potentials (APs), local-field potentials (LFPs), electrode DC offsets (EDOs) and stimulation artifacts (SAs) without saturation. By combining a DC-coupled Δ-ΔΣ architecture with new bootstrapping and chopping schemes, the proposed readout IC achieves an area of 0.0077mm2 per channel, an input-referred noise of 5.53±0.36µVrms in the AP band and 2.88±0.18µVrms in the LFP band, a dynamic range (DR) of 77dB, an EDO tolerance of ±70mV and an input impedance of 283MΩ. The chip has been validated in an in vitro setting, demonstrating the capability to record extracellular signals even when using small, high-impedance electrodes. Because of the small area achieved, this architecture can be used to implement ultra-high-density neural probes for large-scale electrophysiology.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
一种77 db DR 16-Ch二阶Δ-ΔΣ神经记录芯片,0.0077mm2/Ch
本文提出了一种可扩展的16通道神经记录芯片,能够同时采集动作电位(APs),局部场电位(LFPs),电极直流偏移(edo)和刺激伪影(SAs)而不饱和。通过将直流耦合Δ-ΔΣ架构与新的自举和斩波方案相结合,所提出的读出IC实现了每通道面积为0.0077mm2, AP频段的输入参考噪声为5.53±0.36µVrms, LFP频段的输入参考噪声为2.88±0.18µVrms,动态范围(DR)为77dB, EDO公差为±70mV,输入阻抗为283MΩ。该芯片已在体外环境中进行了验证,证明即使使用小的高阻抗电极也能记录细胞外信号。由于实现的面积小,该结构可用于实现大规模电生理的超高密度神经探针。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
PIMCA: A 3.4-Mb Programmable In-Memory Computing Accelerator in 28nm for On-Chip DNN Inference A 24–31 GHz Reference Oversampling ADPLL Achieving FoMjitter−N of -269.3 dB A 6.78 MHz Wireless Power Transfer System for Simultaneous Charging of Multiple Receivers with Maximum Efficiency using Adaptive Magnetic Field Distributor IC Enhanced Core Circuits for scaling DRAM: 0.7V VCC with Long Retention 138ms at 125°C and Random Row/Column Access Times Accelerated by 1.5ns A Sub-mW Dual-Engine ML Inference System-on-Chip for Complete End-to-End Face-Analysis at the Edge
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1