High channel count electrophysiology and data processing for freely-moving animals

自由移动动物的高通道数电生理学和数据处理

• 批准号: 10680473
• 负责人: John L Sherwood
• 金额: $ 78.88万
• 依托单位: LEAFLABS, LLC
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-21 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10680473
• 关键词: Acceleration; Address; Adoption; Alzheimer' s Disease; Animals; Architecture; BRAIN initiative; Biotechnology; Bite; Brain; Brain Diseases; Budgets; Cells; Chronic; Cognition; Collaborations; Complex; Computer Architectures; Computer software; Data; Data Analyses; Data Storage and Retrieval; Development; Electrophysiology (science); Elements; Engineering; Epilepsy; Funding; Generations; Goals; Head; Image; Individual; Learning; Letters; Mammals; Marketing; Memory; Mental Depression; Modeling; Modification; National Institute of Mental Health; Neurons; Neurosciences; Noise; Parkinson Disease; Performance; Phase; Physiological; Pilot Projects; Population; Process; Production; Research Personnel; Resolution; Rodent; Sampling; Services; Signal Transduction; Silicon; Site; Small Business Innovation Research Grant; Sorting; Speed; Stream; System; Techniques; Technology; Testing; Time; Tissues; Visualization; Weight; Willow; Work; analog; cluster computing; commercialization; computerized data processing; cost; data acquisition; data integration; design; digital; electron beam lithography; expectation; experimental study; fabrication; improved; in vivo; live stream; manufacture; manufacturing process; millisecond; neural; neural circuit; neural stimulation; novel; research facility; response; sensor; solid state; terabyte; theories; tool

PROJECT SUMMARY Simultaneous recording and stimulation of larger populations of neurons distributed throughout the brain is needed to rigorously evaluate theories of neural computation at the cellular level in mammals. Previously, we introduced a direct-to-disk data acquisition architecture (Kinney et al., 2015) designed to work with close-packed silicon probes (Scholvin et al., 2016) to enable 1000-channel neural recording in head-fixed animals (Preliminary Data). Through pilot studies we demonstrated the successful recording of terabytes of neural spiking activity (Preliminary Data), but also discovered some shortcomings of the architecture. Two design elements in particular were limiting. First, our headstages were too bulky for freely-moving experiments. Second, our acquisition hardware did not have the ability to quickly analyze all 1000 channels of data. As a result, it took days to weeks to understand the neural activity content of the terabyte-size recordings. For ultra-high-channel count neural recordings to become routine, the acquisition architecture must allow and facilitate rapid online and offline analysis of large amounts of data. A computer architecture with local data storage and analysis is favored, since a 1000-channel recording (e.g. 1000 channels sampled with 16 bits at 30 kHz) generates neural data at a sustained rate that exceed typical (gigabit ethernet) network connection speed to compute clusters or the cloud. Accordingly, we propose a 1024-channel silicon probe for freely-moving electrophysiology experiments in combination with a data acquisition system optimized for easy data analysis. The novel silicon probe will record and stimulate 1024 closed-packed sites, be compact enough for freely-moving rodent experiments, and reduce headstage cost by a factor of 5 (<$1 per channel). Furthermore, the redesigned acquisition hardware will not only capture 1024 channels of neural data and store to solid-state drive over a high-speed bus, but will now also copy the data to a GPU for spike sorting and RAM for visualization both online and offline. To test the system, we will perform 1024-channel freely-moving neural recordings in rodents, in collaboration with (at least) 3 labs with expertise (see Letters of Support).

项目总结 同时记录和刺激分布在大脑中的更大数量的神经元是 需要在哺乳动物细胞水平上严格评估神经计算理论。此前，我们 推出了直接到磁盘的数据采集体系结构(Kinney等人，2015年)，旨在与 紧密堆积的硅探头(Scholvin等人，2016)，以实现头固定的1000通道神经记录 动物(初步数据)。通过试点研究，我们成功地记录了TB 神经放电活动(初步数据)，但也发现了一些架构的缺陷。二 特别是设计元素是有限的。首先，我们的头台太大，不能自由移动的实验。 其次，我们的采集硬件没有能力快速分析所有1000个通道的数据。作为一名 结果，需要几天到几周的时间才能理解TB大小的记录的神经活动内容。为 超高通道数神经记录要成为常规，采集架构必须允许和 促进对海量数据的快速在线和离线分析。具有本地数据的计算机体系结构 存储和分析是有利的，因为1000通道记录(例如，以16比特采样的1000通道 30 kHz)以超过典型(千兆以太网)网络连接的持续速率生成神经数据 加速计算群集或云。 因此，我们提出了一种用于自由移动电生理的1024通道硅探针 实验与优化的数据采集系统相结合，便于数据分析。这部小说 硅探头将记录和刺激1024个紧密堆积的地点，足够紧凑，适合自由活动的啮齿动物 实验，并将前期成本降低5倍(每个通道1英镑)。此外，重新设计的 采集硬件不仅将捕获1024个通道的神经数据，并将其存储到固态驱动器上 高速总线，但现在还会将数据复制到GPU以进行尖峰排序，并复制到RAM以进行可视化 线上和线下。为了测试该系统，我们将在啮齿动物身上进行1024个通道的自由移动神经记录， 与(至少)3个具有专业知识的实验室合作(见支持函)。