NeuroSys:Neuroinformatics for Neural Systems

NeuroSys：神经系统的神经信息学

• 批准号: 6796237
• 负责人: Gwen Ann Jacobs
• 金额: $ 35.38万
• 依托单位: MONTANA STATE UNIVERSITY - BOZEMAN
• 依托单位国家: 美国
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-09-01 至 2006-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6796237
• 关键词: computational neuroscience; computer program /software; computer system design /evaluation; informatics; neural information processing; space perception; time perception

DESCRIPTION (provided by applicant): A grand challenge in neuroscience is to understand the biological basis of information processing at the cellular and network levels. One major technological barrier to continuing progress is the lack of adequate informatics and analysis tools to enable exploration of the structural organization of complex neural circuits, the discovery and understanding of emergent properties of neural ensembles, the formulation of quantitative hypotheses about neural computation, and the testing of those hypotheses experimentally. We have developed a prototype database system that provides many of the needed capabilities, and have used this software system to study mechanisms underlying neural encoding. The general goals of the work proposed here are to extend the capabilities and general utility of this prototype system, to interface the database with several additional tools for the analysis of structural and time-series data, and to enable more effective data sharing between remote collaborators. The core informatics and neuroscience research will be carried out by a group of researchers at Montana State University. Collaborations have also been established with researchers at several other research institutions, to insure interoperability of our system with other data collection and analysis tools and to facilitate the testing and refinement of our system. The investigator and co-investigators are all funded through NIH to study dynamic aspects of sensory processing at the cellular and network levels in a variety of preparations, including the cat and monkey visual systems. The researchers all share the following general neuroscience research aims: a) to understand the relationships between spatio-temporal activity patterns in neural ensembles and the information they convey, b) to understand how the spatio-temporal patterns at one processing stage are decoded at the next processing stage, c) to understand how computations are carried out on that decoded information, and d) to understand the mechanisms through which the observed dynamical patterns emerge from the morphology, synaptic connectivity, and intrinsic biophysical characteristics of the neurons in the ensembles. The software tools developed here will be applied to these ongoing studies, enabling a substantial increase in the breadth, depth, rigor, and rate of progress of those research projects. That neuroscience research will, in turn, provide a rigorous basis for the refinement, generalization and extension of the informatics tools.

描述（由申请人提供）：神经科学的一个巨大挑战是 了解细胞和信息处理的生物学基础 网络级别。持续进步的一个主要技术障碍是 缺乏足够的信息学和分析工具来探索 复杂神经回路的结构组织、发现和 理解神经集合的涌现特性，制定 关于神经计算的定量假设及其测试 实验假设。我们开发了一个原型数据库系统 提供了许多所需的功能，并使用该软件系统 研究神经编码的潜在机制。工作总体目标 这里提出的建议是扩展此功能和一般实用性 原型系统，将数据库与几个附加工具连接起来 结构和时间序列数据的分析，并能够更有效地 远程协作者之间的数据共享。核心信息学和 蒙大拿州的一组研究人员将进行神经科学研究 州立大学。还与以下机构的研究人员建立了合作 其他几个研究机构，以确保我们系统的互操作性 与其他数据收集和分析工具一起使用，以便于测试和 完善我们的系统。研究者和联合研究者均获得资助 通过 NIH 研究细胞和感觉处理的动态方面 网络层面有多种准备，包括猫和猴子 视觉系统。研究人员都分享以下一般神经科学知识 研究目的：a）了解时空之间的关系 神经集合中的活动模式及其传达的信息，b） 了解一个处理阶段的时空模式是如何解码的 在下一个处理阶段，c) 了解计算是如何进行的 d）了解解码后的信息的机制 观察到的动态模式来自形态、突触 神经元的连接性和内在的生物物理特征 合奏团。这里开发的软件工具将应用于这些正在进行的 研究的广度、深度、严谨性和速度都有了大幅提高 这些研究项目的进展情况。神经科学研究将在 转，为细化、概括和延伸提供严格的基础 的信息学工具。