Commercial development of microwire bundle technology for massively parallel neural recording.
用于大规模并行神经记录的微线束技术的商业开发。
基本信息
- 批准号:9254605
- 负责人:
- 金额:$ 39.85万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2016
- 资助国家:美国
- 起止时间:2016-04-05 至 2018-03-31
- 项目状态:已结题
- 来源:
- 关键词:Action PotentialsArchitectureBrainCaliberCollaborationsCommunitiesComplexComputer softwareDataData AnalysesData Storage and RetrievalDepositionDevelopmentDevicesElectrodesElectronicsFaceFilmFundingGlassGoalsHairHeadHealth behaviorHumanImageIndividualIndustryInternationalIntuitionLaboratoriesLaboratory ResearchLightMeasuresMechanicsMetalsMethodsMicroelectrodesNeuronsNeurosciencesOptical MethodsOutputPartner in relationshipPolishesPriceProbabilityProcessReproducibilityResearchResolutionSamplingSemiconductorsSeriesSiliconSiteSpeedSurfaceSystemTechniquesTechnologyThinnessTimeUniversitiesWorkarmbasebrain tissuedata acquisitiondesignexperimental studyflexibilityflexible electronicsimprovedin vivoinnovationmicromanipulatormulti-electrode arraysneural circuitnovel strategiesopen sourceprototypepublic health relevancerelating to nervous systemscale upsensortoolvoltage
项目摘要
DESCRIPTION (provided by applicant): This proposal describes a novel approach for recording from tens of thousands of neurons simultaneously using bundles of microwires that are each smaller than a human hair. To accomplish this, thousands of microwires are bundled together, with one end being inserted into the brain and the other being bonded to a high-speed image sensor chip that reads out the voltages on each wire. The sensor output can then be acquired to a PC using standard frame-grabber technology. This approach was developed as part of an international collaboration between the research laboratories of Andreas Schaefer (UCL, UK) and Nicholas Melosh (Stanford University, CA). The company Paradromics was created specifically to develop the academic prototype system into a robust commercial product. Significance - Neural circuits are composed of many thousands of neurons, and information is encoded within these networks by the relative timing of action potentials (1-4). In order to understand how neural circuits behave and how they impact human health and behavior, new techniques are necessary that can resolve the individual spiking activity of many thousands of neurons simultaneously (2, 5, 6). Here we propose a technology that is not only capable of sampling tens of thousands of channels, but can do so in vivo, at depths where non-invasive optical methods are infeasible. Innovation - Our approach is innovative because it combines two highly scalable technologies for the first time ever: high resolution CMOS camera sensors and microwire bundles (7). Our prototype device uses bundles of tens of thousands of wires, and a 640x512 sensor chip (8), but in principle we can scale up both bundles and sensors to millions of channels without any architectural changes. Approach - Here we propose to turn an exciting new laboratory prototype into a turnkey research tool for neuroscience labs around the world. To accomplish this, we propose a series of simple but important improvements to our existing prototype system that will enable us to increase the number of available recording channels by drastically improving bundle-sensor connectivity. We also propose to develop data acquisition software that will make using the system as simple and intuitive as possible. Market - We estimate there are approximately 5,000 active multi-channel recording systems, each with an average less than 100 channels. Our first product will have > 300,000 channels. Two of our systems will therefore be capable of recording from more neurons simultaneously than all of the other multi- channel recording systems in the world combined. Further, because we are harnessing already- developed CMOS technology, we think that we can provide these systems for a price comparable to existing multi-channel recording systems from major suppliers.
描述(由申请人提供):该提案描述了一种使用每根比人类头发还小的微丝束同时记录数万个神经元的新颖方法。为了实现这一目标,数千根微线被捆绑在一起,一端插入大脑,另一端粘合到高速图像传感器芯片上,该芯片读出每根线上的电压。然后可以使用标准图像采集卡技术将传感器输出采集到 PC。该方法是 Andreas Schaefer(英国伦敦大学学院)和 Nicholas Melosh(加利福尼亚州斯坦福大学)研究实验室之间国际合作的一部分。 Paradromics 公司是专门为了将学术原型系统开发成强大的商业产品而创建的。意义 - 神经回路由数千个神经元组成,信息通过动作电位的相对时序在这些网络中进行编码 (1-4)。为了了解神经回路的行为方式以及它们如何影响人类健康和行为,需要新技术来同时解析数千个神经元的个体尖峰活动 (2,5,6)。在这里,我们提出了一种技术,不仅能够对数万个通道进行采样,而且可以在非侵入性光学方法无法实现的深度体内进行采样。创新 - 我们的方法具有创新性,因为它首次结合了两种高度可扩展的技术:高分辨率 CMOS 相机传感器和微线束 (7)。我们的原型设备使用数万根电线束和 640x512 传感器芯片 (8),但原则上我们可以将电线束和传感器扩展到数百万个通道,而无需进行任何架构更改。方法 - 在这里,我们建议将一个令人兴奋的新实验室原型转变为世界各地神经科学实验室的交钥匙研究工具。为了实现这一目标,我们对现有原型系统提出了一系列简单但重要的改进,这将使我们能够通过大幅改进束传感器连接来增加可用记录通道的数量。我们还建议开发数据采集软件,使系统的使用尽可能简单直观。市场 - 我们估计大约有 5,000 个活跃的多通道录音系统,每个系统平均少于 100 个通道。我们的第一个产品将拥有超过 300,000 个频道。因此,我们的两个系统能够同时记录的神经元数量比世界上所有其他多通道记录系统的总和还要多。此外,由于我们正在利用已经开发的 CMOS 技术,我们认为我们可以以与主要供应商现有的多通道记录系统相当的价格提供这些系统。
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(1)
The Argo: a high channel count recording system for neural recording in vivo.
Argo:用于体内神经记录的高通道计数记录系统。
- DOI:10.1088/1741-2552/abd0ce
- 发表时间:2021-02-24
- 期刊:
- 影响因子:4
- 作者:Sahasrabuddhe K;Khan AA;Singh AP;Stern TM;Ng Y;Tadić A;Orel P;LaReau C;Pouzzner D;Nishimura K;Boergens KM;Shivakumar S;Hopper MS;Kerr B;Hanna MS;Edgington RJ;McNamara I;Fell D;Gao P;Babaie-Fishani A;Veijalainen S;Klekachev AV;Stuckey AM;Luyssaert B;Kozai TDY;Xie C;Gilja V;Dierickx B;Kong Y;Straka M;Sohal HS;Angle MR
- 通讯作者:Angle MR
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Matthew R Angle其他文献
The Argo: A 65,536 channel recording system for high density neural recording in vivo
Argo:用于体内高密度神经记录的 65,536 通道记录系统
- DOI:
- 发表时间:
2020 - 期刊:
- 影响因子:0
- 作者:
Kunal Sahasrabuddhe;A. Khan;Aditya P Singh;Tyler M Stern;Yeena Ng;Aleksandar Tadić;P. Orel;Chris LaReau;Daniel Pouzzner;Kurtis Nishimura;K. Boergens;Sashank Shivakumar;Matthew S Hopper;Bryan Kerr;Mina;Robert J Edgington;Ingrid McNamara;Devin Fell;P. Gao;Amir Babaie;S. Veijalainen;A. Klekachev;Alison M. Stuckey;B. Luyssaert;Takashi D. Y. Kozai;Chong Xie;V. Gilja;B. Dierickx;Yifan Kong;M. Straka;H. Sohal;Matthew R Angle - 通讯作者:
Matthew R Angle
Laser ablation of the pia mater for insertion of high-density microelectrode arrays in a translational sheep model
激光消融软脑膜,在平移羊模型中插入高密度微电极阵列
- DOI:
10.1088/1741-2552/ac0585 - 发表时间:
2020 - 期刊:
- 影响因子:4
- 作者:
K. Boergens;Aleksandar Tadić;Matthew S. Hopper;Ingrid McNamara;Devin Fell;Kunal Sahasrabuddhe;Yifan Kong;M. Straka;H. Sohal;Matthew R Angle - 通讯作者:
Matthew R Angle
Matthew R Angle的其他文献
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{{ truncateString('Matthew R Angle', 18)}}的其他基金
Development and evaluation of novel high-density intracortical microelectrode arrays for clinical applications
临床应用新型高密度皮质内微电极阵列的开发和评估
- 批准号:
10255795 - 财政年份:2021
- 资助金额:
$ 39.85万 - 项目类别:
Development and evaluation of novel high-density intracortical microelectrode arrays for clinical applications
临床应用新型高密度皮质内微电极阵列的开发和评估
- 批准号:
10483140 - 财政年份:2021
- 资助金额:
$ 39.85万 - 项目类别:
Development and evaluation of novel high-density intracortical microelectrode arrays for clinical applications
临床应用新型高密度皮质内微电极阵列的开发和评估
- 批准号:
10698164 - 财政年份:2021
- 资助金额:
$ 39.85万 - 项目类别:
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