CAREER:Identifying Brain Anatomy and Function for Risky Behaviors in Large-Scale Imaging and Genetics Studies

人们从事危害自己和他人健康和寿命的行为的倾向各不相同。这种危险行为给社会带来了巨大的成本，许多公共支出都用于减少这种行为的流行。该项目旨在确定人类大脑的特征，这些特征是参与危险行为倾向的个体差异的基础，以及与之相关的遗传倾向。与之前的研究不同，该项目依赖于小型的非代表性样本，该项目将使用目前可用的最大的大脑扫描集，大约10万张图像。它将把这些图像与全基因组数据和有关危险行为的调查措施结合起来，并使用先进的统计技术分析数据。该项目将为风险行为个体差异的神经解剖学和神经功能基础提供独特的见解，并阐明基因、大脑和行为之间的因果关系。由于大脑的解剖特征和功能对（早期）生活环境因素在敏感发育时期的影响很敏感，该项目可以深入了解这些因素如何影响成年期危险行为的发展。所有的分析都将基于预先注册的协议和公开可用的数据和代码，因此将通过生成可重用的变量和分析脚本来促进未来的研究。教育计划包括组织研讨会，促进遗传学家、磁共振成像（MRI）研究人员和社会科学家之间的对话，以及编写教材，向下一代科学家、商学院学生和公众介绍神经科学和遗传学的概念。该项目整合了研究、教育和推广计划，旨在为理解危险行为个体差异的神经解剖学、神经功能和遗传基础开辟新的领域。拟研究包括高质量T1、扩散张量成像和静息状态功能MRI图像。该研究将把这些数据与危险行为的自我报告测量、常见单核苷酸多态性（snp）、来自独立样本的危险行为的大规模全基因组关联研究（GWAS）的结果以及人口统计学和环境变量结合起来。这个项目的总体目标是确定与从事危险行为倾向密切相关的大脑特征；使用体内脑图像注释先前报道的危险行为的遗传关联；采用统计技术提供大脑特征与危险行为之间因果关系的下限；并使用机器学习技术来汇总整个大脑的多模态测量，以预测个人层面的危险行为。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Humans vary in their tendency to engage in behaviors that risk their own and others’ health and longevity. Such risky behaviors impose significant costs on societies, and much public spending is devoted to reducing their prevalence. This project seeks to identify the features of the human brain that underlie individual differences in the tendency to engage in risky behavior, as well as its associated genetic disposition. Unlike previous research on the topic that has relied on small non-representative samples, this project will use the largest collection of brain scans currently available, about 100,000 images. It will combine these images with genome-wide data and survey measures about risky behavior and analyze the data using advanced statistical techniques. This project will provide unique insights into the neuroanatomical and neurofunctional underpinnings of individual differences in risky behavior, and illuminate the causal relationships between genes, brain and behavior. As features of brain anatomy and function are sensitive to the influence of (early-) life environmental factors during sensitive developmental periods, the project can provide insight into how such factors influence the development of risky behavior during adulthood. All analyses will be based on pre-registered protocols and publicly available data and code, and as such will facilitate future research by generating reusable variables and analysis scripts. The educational plan includes the organization of workshops to facilitate a dialogue between geneticists, magnetic resonance imaging (MRI) researchers, and social scientists, as well as the development of teaching materials that introduce concepts in neuroscience and genetics to the next generation of scientists, business students, and the general public.This project integrates research, education and outreach programs aiming to break new grounds in the understanding of the neuroanatomical, neurofunctional and genetic underpinnings of individual differences in risky behavior. The proposed research includes high-quality T1, diffusion tensor imaging and resting-state functional MRI images. The research will combine this data with self-reported measures of risky behaviors, common single nucleotide polymorphisms (SNPs), results from large-scale genome-wide association studies (GWAS) of risky behaviors from independent samples, and demographic and environmental variables. The overall aims of this projects are to identify brain features that are robustly associated with the tendency to engage in risky behavior; annotate previously reported genetic associations of risky behavior using in-vivo brain images; employ statistical techniques to provide lower bounds of causal relationships between brain features and risky behavior; and to use machine-learning techniques for aggregating multimodal measurements across the brain to predict individual-level risky behavior.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.