Summer Institute in Neuroimaging and Data Science

神经影像和数据科学暑期学院

• 批准号: 10409452
• 负责人: Ariel Shalom Rokem
• 金额: $ 20.59万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-06-01 至 2027-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10409452
• 关键词: Address; Adolescent; Adopted; Big Data; Brain; Brain Diseases; Collection; Communities; Community of Practice; Competence; Computer software; Data; Data Analyses; Data Collection; Data Science; Data Science Core; Data Set; Database Management Systems; Databases; Discipline; Educational Curriculum; Face; Faculty; Familiarity; Fostering; Funding; Habits; Home; Human; Image; Influentials; Institutes; Institution; Instruction; Knowledge; Learning; Machine Learning; Magnetic Resonance Imaging; Methodology; Methods; Neurologic; Neurosciences; Participant; Plant Roots; Positioning Attribute; Problem Solving; Reproducibility; Research; Research Personnel; Resources; Science; Scientist; Site; Software Engineering; Software Tools; Structure; Students; Technical Expertise; Technology; Testing; Training; Training Programs; United States National Institutes of Health; Universities; Washington; base; career; classification algorithm; cognitive development; computer science; connectome; data ecosystem; data visualization; design; e-science; experimental study; follow-up; hackathon; high dimensionality; insight; instructor; knowledge base; large datasets; lectures; neuroimaging; novel; open source; prediction algorithm; programs; skills; statistics; success; summer institute; theories; tool; webinar

Project Summary/Abstract The study of the human brain with neuroimaging technologies has entered an exciting era of Big Data. Many data collection projects, including NIH-funded initiatives such as the Human Connectome Project and the Ado- lescent Brain Cognitive Development Study, have made neuroimaging datasets of unprecedented quality freely available to researchers. Despite appearing only recently, these large datasets have already yielded important new insights about human brain structure and function, and the quantity of ongoing NIH-funded projects related to these datasets suggests that this yield has not yet peaked. However, neuroscience researchers face substan- tial challenges in capitalizing on these datasets. The incorporation of Big Data into research requires a set of technical and theoretical tools that are not emphasized in traditional training in neuroscience. These skills and ideas, collectively referred to as Data Science, include both technical expertise—e.g., computer science, soft- ware engineering, databases, machine learning, statistics, and data visualization—as well as a familiarity with the contemporary data ecosystem and best practices. The Summer Institute in Neuroimaging and Data Science features instruction by experts in data science methodology and by leading neuroimaging researchers who are applying data science to answer scientific questions about the human brain. In addition to lectures and tutorials on the theoretical background of data science methodology and its application to neuroimaging, the course fea- tures a week-long hackathon, in which learning is driven by student-led group-projects, with guidance from the course instructors and additional experts. Overall, the curriculum emphasizes experiential hands-on training and collaborative learning.

项目总结/摘要 利用神经成像技术对人脑的研究已经进入了一个令人兴奋的大数据时代。许多 数据收集项目，包括NIH资助的项目，如人类连接组项目和Ado， Lescent Brain Cognitive Development Study，免费提供了前所未有的高质量神经成像数据集 提供给研究人员。尽管最近才出现，但这些大型数据集已经产生了重要的 关于人类大脑结构和功能的新见解，以及正在进行的NIH资助项目的数量 这些数据表明，这一产量尚未达到峰值。然而，神经科学研究人员面临着巨大的挑战， 利用这些数据集的巨大挑战。将大数据纳入研究需要一套 这些技术和理论工具在神经科学的传统培训中没有得到强调。这些技能和 思想，统称为数据科学，包括技术专长-例如，计算机科学，软件， 软件工程、数据库、机器学习、统计和数据可视化，以及熟悉 当代数据生态系统和最佳实践。神经成像和数据科学暑期研究所 由数据科学方法学专家和领先的神经成像研究人员提供指导， 应用数据科学来回答关于人类大脑的科学问题。除了讲座和辅导之外， 在数据科学方法论的理论背景及其在神经影像学中的应用方面， tures为期一周的黑客，其中学习是由学生领导的小组项目驱动，从指导 课程讲师和其他专家。总的来说，课程强调体验式实践培训， 协作学习