Training in Advanced Statistical Methods in Neuroimaging and Genetics

摘要 该计划将设计，实施，并建立一个课程，教先进的统计方法， 神经影像学和遗传学在过去的十年里，美国国立卫生研究院（National Institutes of Health）大大增加了对 利用先进的神经影像学方法，遗传学方法和先进的统计学方法。 虽然提供入门课程，但美国没有提供任何课程， 一个密集的，动手学习的机会，以更好地准备先进的生物医学和临床研究人员 方法.考虑到利用这些先进分析技术的赠款的合并预算， 国家神经疾病和中风研究所（NINDS），国家精神卫生研究所（NIMH）， 国家老龄化研究所（NIA）、国家药物滥用研究所（NIDA）和国家生物医学研究所（NBI） 成像和生物工程（NIBIB）（五个研究所，大大利用神经成像和遗传学），已经成长 5-从约2.5亿美元增加到约12.5亿美元，非常需要提供教育机会 确保劳动力能够很好地执行这些和其他部门确定的重要工作， 院所该计划将创建课程，“在神经影像学高级统计方法的培训， 遗传学”。它将汇集世界一流的科学家和教育工作者在为期两周的密集格式， 理论讲座与动手操作的计算机教程相结合。这个项目将在第一年教20名学生， 2年级和3年级有25名学生，4年级和5年级有30名学生。这些学生将被所有 在美国各地，关注多样化的学生群体，确保女性入学， 代表性不足的少数民族。此外，该项目将根据财务需要分发旅行奖。的 课程的开始将是基本统计方法和分析基础设施的全天入门。超过 两个星期，学生将学习并付诸实践的方法，如：分层统计模型，贝叶斯 统计学，网络科学，功能和结构连接组学，疾病驱动的大脑退化，以及 分析遗传学数据的方法，如多基因风险评分和结构方程模型。 本课程将以多模态分析的讲座和实验结束，包括多模态成像分析， 和成像遗传学分析，沿着用于生物标志物开发的分类方法。帮助学生 将获得的知识和技能应用于他们在家乡研究所的独立研究项目，我们 将以继续教育部分补充课程。在正式的两周后的6个月里， 课程，学生将有机会获得理论讲师每月在一个结构化的学习 环境此外，在6个月的随访期间，他们还将获得近乎实时的访问权限 通过Slack消息传递和协作平台解决技术实施问题。这 继续教育部分将大大增加成功利用他们的新的实践技能在自己的研究。

Abstract This program will design, implement, and establish a course to teach advanced statistical methods in neuroimaging and genetics. Over the past decade the National Institutes of Health has greatly increased funding of grants that utilized advanced neuroimaging methods, genetic methods, and advanced statistical methods. While introductory courses are offered, there is, however, no course offered in the United States that provides an intensive, hands-on learning opportunity to better prepare biomedical and clinical researchers in advanced methods. Given that the combined budgets for grants that utilize these advanced analysis techniques from the National Institute of Neurological Disorders and Stroke (NINDS), National Institute of Mental Health (NIMH), National Institute on Aging (NIA), National Institute on Drug Abuse (NIDA), and National Institute of Biomedical Imaging and Bioengineering (NIBIB (five Institutes that greatly utilize neuroimaging and genetics), have grown 5-fold from ~250 million USD to ~1250 million USD, there is a great need to provide an educational opportunity to ensure the workforce is well positioned to carry out important work that has been identified by these and other institutes. This program will create the course, “Training in Advanced Statistical Methods in Neuroimaging and Genetics”. It will bring together world-class scientists and educators in a two-week intensive format to provide theoretical lectures paired with hands-on computer tutorials. This program will teach 20 students in the first year, 25 students in years 2 and 3, and then 30 students in years 4 and 5. These students will be accepted from all across the United States, with attention to a diverse student cohort, ensuring enrollment of women and underrepresented minorities. Additionally, the project will distribute Travel Awards based on financial need. The beginning of the course will be a full-day primer on basic statistical methods and analytic infrastructure. Over two weeks, students will learn and put into practice methods such as: hierarchical statistical models, Bayesian statistics, network science, functional and structural connectomics, disease driven degeneration of the brain, and methods for analysis of genetics data such as polygenic risk scoring and structural equation modeling. The course will conclude with lectures and labs on multi-modal analysis, including multi-modal imaging analysis, and imaging-genetics analysis, along with classification methods for biomarker development. To help students apply the acquired knowledge and skills to their independent research projects back at their home institutes, we will supplement the course with a continuing education portion. For the 6 months following the formal two-week course, the students will have access to the theory lecturers on a monthly basis in a structured learning environment. Additionally, during that 6-month follow-up period, they will also have near-real-time access regarding technical implementation questions through the Slack messaging and collaboration platform. This continued education portion will greatly increase success utilizing their new practical skills in their own research.