Training in Advanced Statistical Methods in Neuroimaging and Genetics

摘要 该计划将设计、实施和建立一门课程，教授高级统计方法 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大大增加了资金投入 利用先进的神经影像方法、遗传学方法和先进的统计方法的赠款。 虽然提供入门课程，但美国没有提供提供以下内容的课程： 密集的实践学习机会，可以更好地为高级生物医学和临床研究人员做好准备 方法。鉴于利用这些先进分析技术的赠款合并预算 国家神经疾病和中风研究所 (NINDS)、国家心理健康研究所 (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 成像和生物工程（NIBIB（五个充分利用神经成像和遗传学的研究所），已发展壮大 从约 2.5 亿美元增至约 12.5 亿美元 5 倍，非常需要提供教育机会 确保员工队伍能够很好地开展这些和其他方面已确定的重要工作 机构。该计划将创建课程“神经影像学和高级统计方法培训” 遗传学”。它将汇集世界一流的科学家和教育家，以为期两周的密集形式提供 理论讲座与计算机实践教程相结合。该项目第一年将教 20 名学生， 第二年和第三年有 25 名学生，第四年和第五年有 30 名学生。这些学生将被所有学校录取 在美国各地，关注多元化的学生群体，确保女性和女性的入学 代表性不足的少数群体。此外，该项目将根据财务需要分配旅行奖励。的 课程的开始将是关于基本统计方法和分析基础设施的全天入门课程。结束 两周，学生将学习并付诸实践方法，例如：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 遗传学数据分析方法，例如多基因风险评分和结构方程建模。 该课程将以多模态分析的讲座和实验室结束，包括多模态成像分析、 和成像遗传学分析，以及生物标志物开发的分类方法。为了帮助学生 将获得的知识和技能应用到他们家乡研究所的独立研究项目中，我们 将通过继续教育部分补充课程。正式两周后的 6 个月内 课程中，学生每月将有机会与理论讲师进行结构化学习 环境。此外，在 6 个月的随访期内，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。这个 继续教育部分将极大地提高他们在自己的研究中利用新的实践技能的成功率。

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.