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

职业：面积和功耗最小化的多通道神经尖峰 DSP

• 批准号: 0847088
• 负责人: Dejan Markovic
• 金额: $ 40万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-04-01 至 2014-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0847088&HistoricalAwards=false
• 关键词: CAREER; Area; Power; Minimized; Many

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.

集成、混合和复杂系统加州大学洛杉矶分校Dejan MarkovicCAREER：面积和功率最小化多通道神经峰DSP这项研究的目标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。其方法是在算法和底层技术之间提供紧密的交互，以优化DSP体系结构。该项目的目标是在增加的通道数量和降低的硬件成本中展示几个数量级的改进。从智能方面的优点来看，该项目旨在展示一种可扩展到多达2000个神经通道的实时可植入DSP芯片。现有设计仅为多达30个通道提供部分DSP功能。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800kbps以下，同时根据安全需要将功率密度保持在每平方毫米0.8毫瓦以下。该项目还将提供用于硬件仿真的DSP架构，以展示与最先进的计算机相比，数据处理的速度提高10,000倍以上。从更广泛的影响来看，神经数据处理的成功整合将显著促进许多应用，如视觉、听觉、运动和认知假肢。实现电生理数据更快分析的方法将为神经科学家提供更快地获取重要研究数据的途径，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，为工业界和学术界培养多样化的学生群体，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领域的传播和发展。