Data Exploration and Analysis Portal for Brain Research through Advanced Imaging Neuroscience

通过高级成像神经科学进行脑研究的数据探索和分析门户

• 批准号: 10011169
• 负责人: Chun Chieh Fan
• 金额: $ 114.25万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-17 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10011169
• 关键词: Adolescent; Adult; Behavior; Behavioral; Behavioral Mechanisms; Brain; Brain Mapping; Brain imaging; Brain region; Child; Communities; Complex; Data; Data Analyses; Data Scientist; Development; Elements; Enrollment; Epidemiology; Fostering; Goals; Human; Image; Individual; Informatics; Investigation; Knowledge; Link; Logistics; Longevity; Maps; Measures; Methodology; Methods; Mind; Modality; Modeling; Modernization; Multimodal Imaging; National Institute of Mental Health; Nature; Neurosciences; Online Systems; Ontology; Outcome; Pattern; Population; Probability; Process; Reproducibility; Research; Research Design; Research Personnel; Resolution; Risk Factors; Sample Size; Sampling; Sampling Studies; Scoring Method; Site; Spatial Distribution; Specific qualifier value; Statistical Data Interpretation; Statistical Models; Testing; Time; Work; base; brain research; cognitive development; cohort; connectome; data and analysis portal; data archive; data collection site; data exploration; data resource; design; experience; flexibility; follow-up; image processing; imaging modality; informatics tool; innovation; longitudinal design; modifiable risk; neurodevelopment; novel; prevent; structured data; symposium; tool; web-based informatics

Project Summary Population neuroscience requires investigation of brain-behavioral relationships within epidemiological samples studied in longitudinal designs, including a large number of assessment modalities and with subjects enrolled at many data collection sites to achieve a large sample and broad representation of the population. Of note, the Adolescent Brain Cognitive Development (ABCD) Study and the Human Connectome Project Development (HCP-D and HCP-A), have, in aggregate, enrolled thousands of individuals, many as children and adolescents, and are expected to follow them for up to ten years. Foreseeing the need for an accessible analysis platform to foster rigorous modeling, the ABCD Data Analysis and Informatics Center (DAIC) has developed and deployed the web-based Data Exploration and Analysis Portal (DEAP). Despite its nascent stage, the present version of DEAP already provides a flexible tool that meets many needs of both data scientists and applied investigators. Here, we propose to produce a more versatile extension of DEAP, the Data Exploration and Analysis Portal for Brain Research through Advanced Imaging Neuroscience (DEAP- BRAIN). We will implement important new features by incorporating approaches for: i) including HCP data to assess generalizability; ii) newly developed poly-vertex score as a method to summarize generalizability of whole brain patterns; and iii) bias assessment based on causal inference methods. By the completion of this proposal, we will facilitate reproducible and valid scientific discovery through providing the research community with an easy to use but sophisticated informatics tool. The Specific Aims of the proposal are: Specific Aim 1: Integrating HCP data into DEAP-BRAIN. We will integrate ABCD and HCP data through homogenizing the imaging processing and variable conventions. The HCP adult cohort and HCP lifespan development cohort will be integrated in DEAP, allowing a formal assessment of generalizability. Specific Aim 2: Implementing poly-vertex scores (PVS) as the framework for assessing generalizability of brain mapping. We will implement our newly developed PVS method, an innovative approach to summarize the reproducibility of association patterns across brain. Specific Aim 3: Implementing bias assessment modules. We will implement the bias assessment module for DEAP users based on causal inference principles, using propensity scores, principal component methods, and synthetic controls.

项目总结

项目成果

Intelligence Polygenic Score Is More Predictive of Crystallized Measures: Evidence From the Adolescent Brain Cognitive Development (ABCD) Study.

智力多基因评分更能预测结晶测量：来自青少年大脑认知发展 (ABCD) 研究的证据。

• DOI: 10.1177/09567976231160702
• 发表时间: 2023
• 期刊: Psychological science
• 影响因子: 8.2
• 作者: Loughnan,RobertJ;Palmer,ClareE;Thompson,WesleyK;Dale,AndersM;Jernigan,TerryL;ChiehFan,Chun
• 通讯作者: ChiehFan,Chun

A semi-parametric Bayesian model for semi-continuous longitudinal data.

• DOI: 10.1002/sim.9359
• 发表时间: 2022-06-15
• 期刊: STATISTICS IN MEDICINE
• 影响因子: 2
• 作者: Ren, Junting;Tapert, Susan;Fan, Chun Chieh;Thompson, Wesley K.
• 通讯作者: Thompson, Wesley K.

Unique prediction of developmental psychopathology from genetic and familial risk.

• DOI: 10.1111/jcpp.13649
• 发表时间: 2022-12
• 期刊: JOURNAL OF CHILD PSYCHOLOGY AND PSYCHIATRY
• 影响因子: 7.6
• 作者: Loughnan, Robert J.;Palmer, Clare E.;Makowski, Carolina;Thompson, Wesley K.;Barch, Deanna M.;Jernigan, Terry L.;Dale, Anders M.;Fan, Chun Chieh
• 通讯作者: Fan, Chun Chieh

Association of Genetic Variant Linked to Hemochromatosis With Brain Magnetic Resonance Imaging Measures of Iron and Movement Disorders.

• DOI: 10.1001/jamaneurol.2022.2030
• 发表时间: 2022-09-01
• 期刊: JAMA NEUROLOGY
• 影响因子: 29
• 作者: Loughnan, Robert;Ahern, Jonathan;Tompkins, Cherisse;Palmer, Clare E.;Iversen, John;Thompson, Wesley K.;Andreassen, Ole;Jernigan, Terry;Sugrue, Leo;Dale, Anders;Boyle, Mary E. T.;Fan, Chun Chieh
• 通讯作者: Fan, Chun Chieh

Individual Differences in Cognitive Performance Are Better Predicted by Global Rather Than Localized BOLD Activity Patterns Across the Cortex.

认知表现的个体差异可以通过大脑皮层的整体而不是局部的大胆活动模式更好地预测。

• DOI: 10.1093/cercor/bhaa290
• 发表时间: 2021
• 期刊: Cerebral cortex (New York, N.Y. : 1991)
• 作者: Zhao,Weiqi;Palmer,ClareE;Thompson,WesleyK;Chaarani,Bader;Garavan,HughP;Casey,BJ;Jernigan,TerryL;Dale,AndersM;Fan,ChunChieh
• 通讯作者: Fan,ChunChieh