Reproducible imaging-based brain growth charts for psychiatry

用于精神病学的可重复的基于成像的大脑生长图

基本信息

批准号：
10001025
负责人：
Michael Peter Milham
金额：
$ 72.48万
依托单位：
UNIVERSITY OF PENNSYLVANIA
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-08-22 至 2024-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10001025
关键词：
Address Adolescence Age Base of the Brain Bayesian Method Brain Brain Diseases Categories Childhood Clinical Clinical Data Code Communities Data Data Aggregation Data Analytics Data Collection Data Pooling Data Set Detection Development Diagnosis Dimensions Disease Docking Early Intervention Failure Fright Functional Imaging Grain Growth Heterogeneity Human Image Informatics International Life Link Machine Learning Maps Measurement Measures Mental disorders Modeling Multimodal Imaging National Institute of Mental Health Neurosciences Outcome Participant Phenotype Process Properdin Protocols documentation Psychiatry Psychopathology Public Health Recording of previous events Reproducibility Research Resources Rest Sampling Scanning Sex Differences Site Societies Structure Sum Symptoms Techniques Training Validation Variant Youth aging brain anxious base brain abnormalities clinical phenotype computing resources cost data archive data harmonization data integration data resource design disability externalizing behavior image processing imaging study indexing insight instrument machine learning method multidimensional data multimodality neuroimaging novel portability quality assurance response segregation serial imaging sex somatosensory synergism theories young adult

项目摘要

ABSTRACT Major psychiatric illnesses are increasingly understood as disorders of brain development, which has led to large-scale studies of youth that combine multi-modal neuroimaging with clinical phenotyping. Together, such data have emphasized the promise of objective ‘growth charts’ of brain development. However, synergies across major efforts remains unrealized due to use of different clinical instruments, different scanning protocols, challenges in informatics, and difficulties in data integration. In this proposal, we will overcome these obstacles by leveraging advances in multivariate harmonization and analysis techniques to build highly reproducible growth charts of human brain development. To do this, we will aggregate and harmonize eight existing large-scale developmental imaging studies, comprising over 10,000 participants between the age of 5- 24 (Aim 1). We will use this harmonized data to build generalizable indices of normal network brain development (Aim 2). Finally, developmental abnormalities within specific brain networks will be linked to dimensions of psychopathology (Aim 3). Critically, all code, data, and derived indices will be shared publicly, creating a massive new resource to accelerate research in the developmental neuroscience community (Aim 4). In sum, this proposal will have provide a new data resource, yield reproducible growth charts of brain development, and delineate novel mechanisms regarding the developmental basis of psychopathology in youth.

抽象的人们越来越多地将主要精神疾病理解为大脑发育障碍，这导致将多模式神经影像学与临床表型分析结合在一起的大规模青少年研究。数据强调了大脑发育客观“生长图”的前景。由于使用不同的临床仪器、不同的扫描，跨主要努力仍未实现在这个提案中，我们将克服协议、信息学的挑战和数据集成的困难。通过利用多元协调和分析技术的进步来克服这些障碍为此，我们将汇总并协调八个人类大脑发育的可重复生长图表。现有的大规模发育成像研究，包括超过 10,000 名 5 岁至 24（目标 1）我们将使用这些统一的数据来构建正常网络大脑的通用指数。最后，特定大脑网络内的发育异常将与此相关。重要的是，所有代码、数据和派生指数都将公开共享，创建大量新资源以加速发育神经科学界的研究（目标 4）总而言之，该提案将提供新的数据资源，产生可重复的大脑生长图表。发展，并描绘有关精神病理学发展基础的新机制青年。