Electronics and computational hardware for ultra-high channel count electrophysio

用于超高通道数电生理学的电子和计算硬件

• 批准号: 8715028
• 负责人: Jessica Barber
• 金额: $ 34.97万
• 依托单位: LEAFLABS, LLC
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-06 至 2016-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8715028
• 关键词: 3-Dimensional; Alzheimer' s Disease; Animals; Architecture; Area; Back; Biological; Brain Diseases; Characteristics; Cognition; Collaborations; Computer Analysis; Computers; Data; Data Set; Data Sources; Data Storage and Retrieval; Development; Devices; Electrodes; Electronics; Electrophysiology (science); Ensure; Epilepsy; Head; Laboratories; Laboratory Research; Laws; Learning; Memory; Mental Depression; Monitor; Motivation; Mus; Neurons; Noise; Parkinson Disease; Plant Leaves; Polishes; Population; Process; Resources; Signal Transduction; System; Systems Analysis; Testing; Time; Work; advanced system; awake; cost; data acquisition; density; design; extracellular; improved; in vivo; innovation; interest; prototype; public health relevance; relating to nervous system

DESCRIPTION (provided by applicant): The advent of in vivo multielectrode recording has indicated the importance of recording from large populations of neurons. As a result, there is much interest in creating new kinds of in vivo multielectrode arrays, including the polytrode, new kinds of microfabricated electrode arrays, and new kinds of ultradense 3-D electrode array. And yet, innovation on the back-end systems for amplifying digitizing, storing, and analyzing extracellular electrophysiological recordings has remained limited, even though these systems often comprise one of the most expensive components of the entire enterprise. Accordingly, we are working to develop a system of advanced electronics and computational hardware to fill the gap in data acquisition systems for ultra high channel count probes, or alternatively to reduce the cost of neural data recording by an order of magnitude in the next two years - the equivalent of a six-fold speedup in the "Moore's law" of the field. Our system, dubbed "Wired-Leaf," currently being prototyped in collaboration with the Boyden Lab at MIT, is a radically new kind of minimalist computer that overcomes several drawbacks associated with existing commercially available systems. In particular, current designs rely upon obsolete architectures and depend on computational systems that are loaded with unnecessary features, while skimping on the raw resources required to acquire and process neural data. Our near-optimally simple and scalable devices directly amplify and digitize data, store it directly to a data storage drive, then transmi it to downstream computers for analysis, all at an order of magnitude lower cost than what is commercially available currently. While our current prototype validates this approach, the focus of this proposal is to polish our current system for marketability and widespread use.

描述(申请人提供)：活体多电极记录的出现表明了从大量神经元中记录的重要性。因此，人们对创造新型在体多电极阵列非常感兴趣，包括多电极、新型微细加工电极阵列和新型超高密度三维电极阵列。然而，用于放大、数字化、存储和分析细胞外电生理记录的后端系统的创新仍然有限，尽管这些系统往往构成整个企业最昂贵的组件之一。因此，我们正在努力开发一种先进的电子和计算硬件系统，以填补超高通道数探测器的数据采集系统的空白，或者在未来两年内将神经数据记录的成本降低一个数量级--相当于该领域“摩尔定律”的六倍加速。我们的系统名为“Wire-Leaf”，目前正在与麻省理工学院博伊登实验室合作制作原型，是一种全新的极简主义计算机，它克服了与现有商业系统相关的几个缺陷。特别是，当前的设计依赖于过时的架构，依赖于加载了不必要功能的计算系统，而对获取和处理神经数据所需的原始资源却很少。我们近乎最佳的简单和可扩展的设备直接放大和数字化数据，直接将其存储到数据存储驱动器，然后将其传输到下游计算机进行分析，所有这些都比目前商业上可用的成本低一个数量级。虽然我们目前的原型验证了这一方法，但该提案的重点是为市场和广泛使用完善我们目前的系统。