MRI: Acquisition of Instrumentation for Coupled Experimental-Computational Neuroscience and Biology Research

MRI：购买用于耦合实验计算神经科学和生物学研究的仪器

• 批准号: 0821622
• 负责人: Jose Fortes
• 金额: $ 50万
• 依托单位: University of Florida
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-07-01 至 2012-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0821622&HistoricalAwards=false
• 关键词: MRI; Acquisition; Instrumentation; Coupled; Experimental

Proposal #: CNS 08-21622PI(s): Fortes, Jose A. McIntyre, Lauren M.; Moroz, Leonid L.; Principe, Jose C.; Sanchez, Justin C.Institution: University of Florida Gainesville, FL 32611-2002Title: MRI/Acq.: Instrumentation for Coupled Experimental-Computational Neuroscience and Biology ResearchProject Proposed:This project, acquiring a virtualized multicomputer instrument with shared-memory subsystems and storage capacity, intends to use this instrument as a shared instrument whose resources can be virtualized, reserved, and configured on demand for different research activities related to neuroscience, computational biology, and cyberinfrastructure. Its configurations can also be dedicated and tightly coupled to in vivo experiments using network connections to in situ instrumentation used for experiments. It can simultaneously support multiple research activities because of its unique capability to support real-time computer-in-the-loop experiments, its ability to run many concurrent computation threads, its shared memory and storage subsystems, and its use of virtualization technology to manage the coexistence of multiple computing environments. To develop and validate autonomic computing nodes and techniques for multiuser virtualized computational systems, the instrument provides traces of performance and other needed monitored data. Research activities in brain-machine interfaces, neurogenesis, genomics, bioinformatics, signal processing, cyberinfrastructure, autonomic computing and other areas include:- Brain-machine interfaces where cortex models for motor control are dynamically learned and applied in real-time,- Experimental drug discovery through real-time analysis of large amounts of genetic data and many thousands of compounds,- Analysis of Terabytes of genetic data captured in real-time as a neuron grows, learns, and remembers, and- Online learning algorithms using dynamic filter topologies with online computation requirements that increase over time.The activities have transformative goals, including the introduction of real-time, and address the high performance computation into closed-loop experiments and/or systems whose behavior is driven by complex processing of sensed data. Another goal involves providing off-line computing capabilities to match the unprecedented rate and volume of genetic data produced by massively parallel DNA sequencing technology.

提案编号：CNS 08- 21622 PI：Fortes，Jose A. McIntyre，Lauren M.; Moroz，Leonid L.; Principe，Jose C.;机构：佛罗里达大学 Gainesville，FL 32611- 2002标题：MRI/采集： 耦合实验计算神经科学和生物学研究的仪器项目建议：该项目，获得具有共享内存子系统和存储容量的虚拟化多计算机仪器，打算使用该仪器作为共享仪器，其资源可以虚拟化，保留和配置的不同研究活动相关的神经科学，计算生物学和网络基础设施。它的配置也可以专用和紧密耦合到体内实验，使用网络连接到用于实验的原位仪器。它可以同时支持多个研究活动，因为它具有支持实时计算机在环实验的独特能力，能够运行许多并发计算线程，共享内存和存储子系统，以及使用虚拟化技术来管理多个计算环境的共存。为了开发和验证多用户虚拟化计算系统的自主计算节点和技术，该仪器提供了性能跟踪和其他所需的监控数据。在脑机接口，神经发生，基因组学，生物信息学，信号处理，网络基础设施，自主计算和其他领域的研究活动包括：- 脑-机接口，其中用于运动控制的皮层模型被动态学习并实时应用，-通过实时分析大量遗传数据和数千种化合物来发现实验性药物，-分析在神经元生长、学习和记忆时实时捕获的TB遗传数据，以及-使用动态过滤器拓扑的在线学习算法，其在线计算要求随着时间的推移而增加。这些活动具有变革性目标，包括实时的引入，并将高性能计算处理到闭环实验和/或系统中，所述闭环实验和/或系统的行为由感测数据的复杂处理驱动。另一个目标涉及提供离线计算能力，以匹配大规模并行DNA测序技术产生的前所未有的遗传数据速度和数量。