Acquisition of the Oregon ICONIC Grid for Integrated COgnitive Neuroscience Informatics and Computation

收购俄勒冈州标志性网格，用于集成认知神经科学信息学和计算

• 批准号: 0321388
• 负责人: Allen Malony
• 金额: $ 103.75万
• 依托单位: University of Oregon Eugene
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-09-01 至 2007-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0321388&HistoricalAwards=false
• 关键词: Acquisition; Oregon; ICONIC; Grid; Integrated

Future progress in cognitive neuroscience research will rely increasingly on the application of systems for high-performance computation and high-volume data management to address the challenges of integrated neuroimaging, multi-modality sensor fusion, and cognitive modeling. With a Major Research Instrumentation award from the National Science Foundation, the University of Oregon will establish the Integrated COgnitive Neuroscience, Informatics, and Computation (ICONIC) Grid, composed of parallel computing clusters, large-scale data servers, workstations, and interactive visualization devices. Connected by a high-bandwidth campus network linking the Department of Psychology, the Center for Neuroimaging , the Neuroinformatics Center, the Department of Computer and Information Science, and the Computational Science Institute, the ICONIC Grid will enhance Oregon's excellence in cognitive neuroscience with needed computing power to solve neuroimaging problems of tissue/feature segmentation, dense-array EEG source localization, multi-modal MRI integration, and functional components analysis. The ICONIC Grid will be organized as a distributed computing environment to promote grid-style collaboration among cognitive neuroscience research groups. Computer science research in high-performance parallel and distributed computing, scientific databases, informatics, and interactive visualization will enhance the ICONIC Grid for highly productive use as a computational science tool.The interchange between cognitive neuroscience and computational science is now important at both theoretical and empirical levels. For several decades, cognitive psychology has drawn from concepts of cybernetics and information processing in the development of models of human mental function. However, it is in the integration of psychological with neural evidence that the methodological demands for computational advances have become particularly intense. Many investigators in cognitive neuroscience now recognize the limitations of individual brain imaging methods, such as in the temporal or spatial resolution, or practical implementation of the technology. The result is an increasing demand for integrated imaging and analysis, in which convergent methods are brought to bear on a particular issue of brain mechanisms. The University of Oregon began the decade with a bold Brain, Biology, and Machine Initiative (BBMI) to promote interdisciplinary research between neuroscience, cognitive science, molecular biology, genomics, and computational science. The establishment of the Center for Neuroimaging , which houses a new Siemans Allegra 3-Tesla fMRI machine, and the Neuroinformatics Center, were Oregon's first steps towards integrative cognitive neuroscience. The ICONIC Grid is the next critical piece of the puzzle providing an essential resource to further advancements in cognitive neuroscience research, collaboration, education, and outreach.The broader impact of the ICONIC Grid will be important for the University's educational goals, for minority recruitment and retention, and for extending advances in computation to medical advances in society. With on-campus access to both advanced imaging facilities and the computational and visualization infrastructure that processes and presents the experimental data, students in Psychology will be exposed to a state-of-the-art problem-solving environment for cognitive neursocience education. New Psychology curricula are planned for providing students training in the use of such tools. Similarly, the CIS department's academic objectives in parallel and distributed computing, computational science, networking, human-computer interaction, and visualization will benefit greatly from hands-on access to parallel cluster and distributed grid technology.

未来认知神经科学研究的进展将越来越依赖于高性能计算和海量数据管理系统的应用，以应对集成神经成像、多模式传感器融合和认知建模的挑战。俄勒冈大学将利用国家科学基金会颁发的重大研究仪器奖，建立综合认知神经科学、信息学和计算(ICONIC)网格，由并行计算集群、大规模数据服务器、工作站和交互式可视化设备组成。通过连接心理学系、神经成像中心、神经信息学中心、计算机和信息科学系以及计算科学研究所的高带宽校园网络，标志性的网格将增强俄勒冈州在认知神经科学方面的卓越地位，并提供所需的计算能力，以解决组织/特征分割、密集阵列EEG源定位、多模式MRI集成和功能组件分析等神经成像问题。标志性的网格将被组织为一个分布式计算环境，以促进认知神经科学研究小组之间的网格式合作。计算机科学在高性能并行和分布式计算、科学数据库、信息学和交互可视化方面的研究将加强标志性的网格作为一种高效的计算科学工具的使用。认知神经科学和计算科学之间的交流现在在理论和经验层面都是重要的。几十年来，认知心理学在人类心理功能模型的发展中借鉴了控制论和信息处理的概念。然而，正是在心理学和神经证据的整合中，对计算进步的方法论要求变得特别强烈。认知神经科学领域的许多研究人员现在认识到了个人大脑成像方法的局限性，比如在时间或空间分辨率方面，或者在该技术的实际实施方面。其结果是对集成成像和分析的需求不断增加，在这种集成成像和分析中，融合的方法被引入到特定的大脑机制问题上。俄勒冈大学以一项大胆的脑、生物学和机器倡议(BBMI)开始了这十年，该倡议旨在促进神经科学、认知科学、分子生物学、基因组学和计算科学之间的跨学科研究。神经成像中心和神经信息学中心的建立是俄勒冈州迈向综合认知神经科学的第一步。该中心配备了一台新的西门子Allegra 3-Tesla功能磁共振成像仪，以及神经信息学中心。标志性的网格是这一谜题的下一个关键部分，为认知神经科学研究、协作、教育和外展的进一步发展提供了必要的资源。标志性网格的更广泛影响将对大学的教育目标、少数族裔的招募和保留以及将计算方面的进步扩展到社会的医学进步具有重要意义。通过在校园内访问先进的成像设施以及处理和呈现实验数据的计算和可视化基础设施，心理学专业的学生将接触到用于认知神经社交教育的最先进的问题解决环境。计划开设新的心理学课程，为学生提供使用这类工具的培训。同样，独联体系在并行和分布式计算、计算科学、网络、人机交互和可视化方面的学术目标将从对并行集群和分布式网格技术的实际访问中受益匪浅。