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。

• 批准号: 9254605
• 负责人: Matthew R Angle
• 金额: $ 39.85万
• 依托单位: PARADROMICS, INC.
• 依托单位国家: 美国
• 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: https://reporter.nih.gov/project-details/9254605
• 关键词: Action Potentials; Architecture; Brain; Caliber; Collaborations; Communities; Complex; Computer software; Data; Data Analyses; Data Storage and Retrieval; Deposition; Development; Devices; Electrodes; Electronics; Face; Film; Funding; Glass; Goals; Hair; Head; Health behavior; Human; Image; Individual; Industry; International; Intuition; Laboratories; Laboratory Research; Light; Measures; Mechanics; Metals; Methods; Microelectrodes; Neurons; Neurosciences; Optical Methods; Output; Partner in relationship; Polishes; Price; Probability; Process; Reproducibility; Research; Resolution; Sampling; Semiconductors; Series; Silicon; Site; Speed; Surface; System; Techniques; Technology; Thinness; Time; Universities; Work; arm; base; brain tissue; data acquisition; design; experimental study; flexibility; flexible electronics; improved; in vivo; innovation; micromanipulator; multi-electrode arrays; neural circuit; novel strategies; open source; prototype; public health relevance; relating to nervous system; scale up; sensor; tool; voltage

 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（由适用提供）：该提案描述了一种新的方法，用于从数以万计的神经元中使用的微孔束，每束比人毛小。为此，成千上万的微管被捆绑在一起，一端插入大脑中，另一端被粘合到高速图像传感器芯片上，该芯片读出每条电线上的电压。然后，可以使用标准框架 - 加勒伯技术将传感器输出获取到PC。这种方法是作为Andreas Schaefer（UCL，UCL）和尼古拉斯·梅洛什（Nicholas Melosh）（加利福尼亚州斯坦福大学）的国际合作的一部分开发的。该公司的范式是专门为将学术原型系统开发成强大的商业产品而创建的。显着性 - 神经回路由数千个神经元组成，并且通过动作电位的相对时机在这些网络中编码信息（1-4）。为了了解神经元的行为以及它们如何影响人类的健康和行为，需要新技术可以解决数千个神经元的单个尖峰活动（2、5、6）。在这里，我们提出了一项技术，该技术不仅能够对成千上万的通道进行取样，而且可以在体内，在非侵入性光学方法不可行的深度处进行体内。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摄像头传感器和Microwire捆绑包（7）。我们的原型设备使用数以万计的电线和640x512传感器芯片（8）的束，但是原则上，我们可以将捆绑包和传感器缩放到数百万个通道，而无需任何建筑变化。方法 - 在这里，我们建议将令人兴奋的新实验室原型变成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，我们提出了一系列简单但重要的改进，以改进我们现有的原型系统，这将使我们能够通过大幅度改善捆绑传感器的连接来增加可用录制渠道的数量。我们还建议开发数据采集软件，以使使用系统尽可能简单和直观。市场 - 我们估计，大约有5,000个主动多通道记录系统，每个录制系统平均少于100个频道。我们的第一个产品将具有> 300,000个频道。因此，与世界上所有其他多通道记录系统相比，我们的两个系统将能够从更多的神经元记录中记录。此外，由于我们正在利用已经开发的CMOS技术，因此我们认为我们可以以与主要供应商的现有多通道记录系统相媲美的价格提供这些系统。

项目成果

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

• DOI: 10.1088/1741-2552/abd0ce
• 发表时间: 2021-02-24
• 期刊: Journal of neural engineering
• 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