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

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 引入了紧密堆积的硅探测器(Scholvin等人，2016)和直接到磁盘的数据采集架构 (Kinney等人，2015年)，以实现头部固定动物的1000通道神经记录(初步数据)。 通过先导研究，我们证明了成功地记录了TB级的神经放电活动 (初步数据)，但也发现了架构的一些不足。中的两个设计元素 特别是有局限性的。首先，我们的头台太大，不能自由移动的实验。第二，我们的 采集硬件没有能力快速分析所有1000个通道的数据。结果，它花了很多时间 几天到几周的时间来了解TB大小的录音的神经活动内容。用于超高频段 计数神经记录要成为例行公事，采集架构必须允许并促进快速在线 以及对大量数据的离线分析。一种具有本地数据存储和分析的计算机体系结构， 优选，因为1000通道记录(例如，以30 kHz用16位采样的1000通道)产生神经 数据以超过典型(千兆以太网)网络连接速度的持续速率连接到计算群集或 云彩。 因此，我们提出了一种用于自由移动电生理的1000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。小说《​》 硅探头将记录和刺激1000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，并将前台成本降低10倍，降至每个通道1美元。此外， 重新设计的采集硬件不仅可以捕获1000个通道的神经数据并存储到固态 通过高速总线驱动，但现在还会将数据复制到GPU以进行峰值排序，并将RAM复制到 在线和离线的可视化。为了测试该系统，我们将进行1000个通道的自由运动神经 与(至少)3个有专业知识的实验室合作，对啮齿动物进行录音(见支持函)。

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 close-packed silicon probes (Scholvin et al., 2016) and a direct-to-disk data acquisition architecture (Kinney et al., 2015) 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 1000-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 1000 closed-packed sites, be compact enough for freely-moving rodent experiments, and reduce headstage cost by a factor of 10, down to $1 per channel. Furthermore, the re-designed acquisition hardware will not only capture 1000 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 1000-channel freely-moving neural recordings in rodents, in collaboration with (at least) 3 labs with expertise (see letters of support).