The Argo: a high channel count recording system for neural recording in vivo.

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2021-02-24 DOI:10.1088/1741-2552/abd0ce
Kunal Sahasrabuddhe, Aamir A Khan, Aditya P Singh, Tyler M Stern, Yeena Ng, Aleksandar Tadić, Peter Orel, Chris LaReau, Daniel Pouzzner, Kurtis Nishimura, Kevin M Boergens, Sashank Shivakumar, Matthew S Hopper, Bryan Kerr, Mina-Elraheb S Hanna, Robert J Edgington, Ingrid McNamara, Devin Fell, Peng Gao, Amir Babaie-Fishani, Sampsa Veijalainen, Alexander V Klekachev, Alison M Stuckey, Bert Luyssaert, Takashi D Y Kozai, Chong Xie, Vikash Gilja, Bart Dierickx, Yifan Kong, Malgorzata Straka, Harbaljit S Sohal, Matthew R Angle
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引用次数: 0

Abstract

Objective: Decoding neural activity has been limited by the lack of tools available to record from large numbers of neurons across multiple cortical regions simultaneously with high temporal fidelity. To this end, we developed the Argo system to record cortical neural activity at high data rates.

Approach: Here we demonstrate a massively parallel neural recording system based on platinum-iridium microwire electrode arrays bonded to a CMOS voltage amplifier array. The Argo system is the highest channel count in vivo neural recording system, supporting simultaneous recording from 65 536 channels, sampled at 32 kHz and 12-bit resolution. This system was designed for cortical recordings, compatible with both penetrating and surface microelectrodes.

Main results: We validated this system through initial bench testing to determine specific gain and noise characteristics of bonded microwires, followed by in-vivo experiments in both rat and sheep cortex. We recorded spiking activity from 791 neurons in rats and surface local field potential activity from over 30 000 channels in sheep.

Significance: These are the largest channel count microwire-based recordings in both rat and sheep. While currently adapted for head-fixed recording, the microwire-CMOS architecture is well suited for clinical translation. Thus, this demonstration helps pave the way for a future high data rate intracortical implant.

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Argo:用于体内神经记录的高通道数记录系统。
目的:神经活动解码一直受限于缺乏可同时记录多个皮层区域大量神经元高时间保真度活动的工具。为此,我们开发了 Argo 系统,以高数据率记录皮层神经活动:在此,我们展示了一种基于铂铱微线电极阵列和 CMOS 电压放大器阵列的大规模并行神经记录系统。Argo 系统是体内通道数最多的神经记录系统,支持 65 536 个通道同时记录,采样频率为 32 kHz,分辨率为 12 位。该系统专为皮层记录而设计,兼容穿透式和表面微电极:我们通过初步的台架测试验证了这一系统,确定了粘合微线的具体增益和噪声特性,随后在大鼠和绵羊皮层进行了体内实验。我们记录了大鼠 791 个神经元的尖峰活动和绵羊 3 万多个通道的表面局域电位活动:意义:这是在大鼠和绵羊体内进行的通道数最多的基于微线的记录。虽然微导线-CMOS 结构目前适用于头部固定记录,但非常适合临床应用。因此,该演示有助于为未来的高数据速率皮层内植入铺平道路。
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来源期刊
CiteScore
7.20
自引率
4.30%
发文量
567
期刊介绍: ACS Applied Electronic Materials is an interdisciplinary journal publishing original research covering all aspects of electronic materials. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials science, engineering, optics, physics, and chemistry into important applications of electronic materials. Sample research topics that span the journal's scope are inorganic, organic, ionic and polymeric materials with properties that include conducting, semiconducting, superconducting, insulating, dielectric, magnetic, optoelectronic, piezoelectric, ferroelectric and thermoelectric. Indexed/​Abstracted: Web of Science SCIE Scopus CAS INSPEC Portico
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