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

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大容量数据管理系统的应用，以解决集成神经成像、多模态传感器融合和认知建模的挑战。俄勒冈大学将获得美国国家科学基金会颁发的主要研究仪器奖，建立集成认知神经科学、信息学和计算（ICONIC）网格，该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、计算机与信息科学系和计算科学研究所的高带宽校园网，ICONIC Grid将增强俄勒冈州在认知神经科学方面的卓越能力，并提供所需的计算能力，以解决组织/特征分割、密集阵列脑电图源定位、多模态MRI集成、以及功能成分分析。icon网格将被组织成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协作。在高性能并行和分布式计算、科学数据库、信息学和交互式可视化方面的计算机科学研究将增强ICONIC Grid作为计算科学工具的高效使用。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很重要。几十年来，认知心理学在发展人类心理功能模型的过程中汲取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。认知神经科学的许多研究者现在认识到个体脑成像方法的局限性，例如时间或空间分辨率，或技术的实际实施。其结果是对集成成像和分析的需求不断增加，其中汇聚的方法被用于大脑机制的特定问题。俄勒冈大学以一个大胆的脑、生物学和机器计划（BBMI）开始了这个十年，以促进神经科学、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，是俄勒冈州向综合认知神经科学迈出的第一步。神经成像中心拥有一台新的西门子Allegra 3-Tesla功能核磁共振成型机。标志性网格是这个谜题的下一个关键部分，它为认知神经科学研究、合作、教育和推广的进一步发展提供了重要的资源。对于大学的教育目标、少数族裔的招聘和保留，以及将计算的进步扩展到社会的医学进步，“标志性网格”的广泛影响将是重要的。通过在校内使用先进的成像设备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最先进的解决问题的环境，以进行认知神经科学教育。新的心理学课程计划为学生提供使用这些工具的培训。类似地，CIS部门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并行集群和分布式网格技术的实际访问中受益匪浅。

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.