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（由申请人提供）：体内多电极记录的出现表明，从大量神经元中记录的重要性。结果，人们有很大的兴趣创建新型的体内多电极阵列，包括多质冰，新型的微生物电极阵列和新型的超高3-D电极阵列。然而，尽管这些系统通常构成了整个企业中最昂贵的组件之一，但后端系统上的创新用于扩增数字化，存储和分析细胞外电生理记录。因此，我们正在努力开发一个高级电子设备和计算硬件系统，以填补超高通道计数探针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到数量级 - 相当于“摩尔法律”的“摩尔法则”中的六倍速度。我们的系统被称为“有线叶”，目前与麻省理工学院的Boyden Lab合作进行了原型型原型，它是一种极具新型的简约计算机，它克服了与现有市售系统相关的几个缺点。特别是，当前的设计依赖于过时的体系结构，并依赖带有不必要功能的计算系统，同时浏览获取和处理神经数据所需的原始资源。我们近乎最简单且可扩展的设备直接放大并数字化数据，将其直接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，所有这些都比当前可商购的价格低。尽管我们当前的原型验证了这种方法，但该提案的重点是为我们当前的销售性和广泛使用的系统增色。