Network Data Acquisition System Neuroscience Research

网络数据采集系统神经科学研究

• 批准号: 6444464
• 负责人: RICHARD E RENCK
• 金额: $ 41.73万
• 依托单位: R.C. ELECTRONICS, INC.
• 依托单位国家: 美国
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-09-15 至 2004-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6444464
• 关键词: computational neuroscience; computer data analysis; computer network; computer system design /evaluation; data collection; data collection methodology /evaluation

The current trend in neuroscience research is to determine how large populations of information processing neurons relate to behavior. Sensor and electrode technology makes it possible to access large numbers (>100) of neurons. Researchers need to collect data from these sensors and to process the data on-line as a critical next step for understanding more complex neural network interactions. Technology needs to be developed for a scalable system that can simultaneously record data and process data for real time interactive management and control of the system under study. We are proposing to develop a scalable Network based Data Acquisition System (NDAS) for computational neuroscience research. We plan to upgrade our existing DATAMAX recorder design and use commercially available network technology to develop NDA. We will modify our 64 channel system to a 256 channel system with time sync capability and network communication to provide scalability to large channel systems. Commercial network technology will be used by NDAS to provide real time processing by transferring data to other signal analysis workstations for distributed processing. PROPOSED COMMERCIAL APPLICATIONS: There is a market demand for high frequency multi-channel Network Data Acquisition Systems in the computational neuroscience market as a research and teaching tool. There exists an aerospace, industrial and military target in acoustic, vibration, shock, and sonar where high frequency multi-channel recording and processing requires 500 or more channels.

神经科学研究的当前趋势是确定大量的信息处理神经元与行为的关系。传感器和电极技术使访问大量（>100个）神经元成为可能。研究人员需要从这些传感器收集数据，并在线处理数据，这是理解更复杂的神经网络交互的关键下一步。技术需要开发一个可扩展的系统，可以同时记录数据和处理数据的真实的时间交互式管理和控制的系统正在研究。我们建议开发一个可扩展的基于网络的数据采集系统（NDAS）的计算神经科学研究。我们计划升级现有的DATAMAX记录器设计，并使用商用网络技术开发NDA。我们将把我们的64通道系统修改为具有时间同步能力和网络通信的256通道系统，以便为大型通道系统提供可扩展性。NDAS将使用商业网络技术，通过将数据传输到其他信号分析工作站进行分布式处理，提供真实的实时处理。拟议的商业应用：在计算神经科学市场中，高频多通道网络数据采集系统作为研究和教学工具存在市场需求。在声学、振动、冲击和声纳中存在航空航天、工业和军事目标，其中高频多通道记录和处理需要500个或更多通道。