CAREER: Area-and-Power-Minimized Many-Channel Neural-Spike DSP

综合、混合和复杂系统加州大学洛杉矶分校职业：面积和功率最小化的多通道神经脉冲数字信号处理（DSP）这项研究的目的是彻底改变用于临床和神经科学应用的多通道电生理记录系统的数字信号处理（DSP）技术。该方法是在算法和底层技术之间提供紧密的交互，以优化DSP架构。我们的目标是演示在增加通道数量和降低硬件成本方面的几个数量级的改进。在智力方面，该项目旨在展示一种可扩展至2,000个神经通道的实时植入式DSP芯片。现有的设计提供部分DSP功能，最多只能支持30个通道。该芯片将能够隔离单个神经元的活动，并将数据速率降低到800 kbps以下，同时保持安全所需的功率密度低于0.8毫瓦/平方毫米。该项目还将为硬件仿真提供DSP架构，以证明与最先进的计算机相比，数据处理速度提高了1万倍以上。就更广泛的影响而言，神经数据处理的成功整合将显著推进视觉、听觉、运动和认知假肢等许多应用。实现电生理数据更快分析的方法将使神经科学家更快地获得重要的研究数据，并提高整体生活质量。该计划旨在通过相关和实用的设计项目，为工业界和学术界的职业培养多样化的学生，并促进更广泛的公众获得最新的研究和教育工具。其深远的社会和经济影响将有助于维持信息技术向新的生物和医学应用的传播和演变。

Integrative, Hybrid and Complex SystemsUniversity of California-Los AngelesDejan MarkovicCAREER: Area-and-Power-Minimized Many-Channel Neural-Spike DSPThe objective of this research is to revolutionize the digital-signal-processing (DSP) technology used for many-channel electrophysiological recording systems used in both clinical and neuroscientific applications. The approach is to provide tight interaction between algorithms and the underlying technology to optimize the DSP architecture. The goal is to demonstrate improvements of several orders of magnitude in the increased number of channels and decreased hardware cost.With respect to intellectual merit, this project intends to demonstrate a real-time implantable DSP chip scalable up to 2,000 neural channels. Existing designs provide partial DSP functionality for only up to 30 channels. The chip will be able to isolate activity from individual neurons and reduce the data rate below 800 kbps while maintaining a power density less than 0.8 milliwatts per square millimeter, as needed for safety. The project will also provide a DSP architecture for hardware emulation to demonstrate over a 10,000 times speed-up in data processing compared to state-of-the-art computers.With respect to broader impact, a successful integration of neural-data processing will significantly advance many applications such as visual, auditory, motor, and cognitive prosthetics. Methods for achieving faster analysis of electrophysiological data will provide neuroscientists quicker access to important research data and improve the overall quality of living. The program intends to train a diverse population of students for careers in industry and academia through relevant and practical design projects, and promote a wider public access to the latest research and educational tools. The far-reaching social and economic impact will be to help sustain the spread and evolution of information technology to new biological and medical applications.