Electronics and computational hardware for ultra-high channel count electrophysio

描述（由申请人提供）：体内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，人们对开发新型的体内多电极阵列非常感兴趣，包括多极体、新型微加工电极阵列和新型超密集三维电极阵列。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，尽管这些系统通常是整个企业中最昂贵的组件之一。因此，我们正在努力开发一种先进的电子和计算硬件系统，以填补超高通道计数探针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。我们的系统被称为“线叶”，目前正在与麻省理工学院的博伊登实验室合作制作原型，这是一种全新的极简计算机，克服了现有商用系统的几个缺点。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，同时忽略了获取和处理神经数据所需的原始资源。我们的设备非常简单且可扩展，可直接放大和数字化数据，将其直接存储到数据存储驱动器中，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用的成本低一个数量级。虽然我们目前的原型验证了这种方法，但本提案的重点是完善我们当前的系统，使其具有市场价值和广泛使用。

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.