BRAIN Initiative: Assessing development of event-related cortical network dynamics

BRAIN Initiative：评估事件相关皮层网络动态的发展

基本信息

批准号：
10190670
负责人：
Arnaud Delorme
金额：
$ 111.48万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN DIEGO
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-04-01 至 2024-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10190670
关键词：
Adolescent Affective Age Archives Area BRAIN initiative Bayesian learning Behavioral Brain Brain imaging Child Cognitive Collection Communities Complex Computer Analysis Computer software Data Data Analyses Data Set Data Store Descriptor Development Developmental Course Diet Electroencephalography Electrophysiology (science)Environment Event Exhibits Eye Family Film Functional Magnetic Resonance Imaging Funding Genetic Goals Head High Performance Computing Human Image Individual Institutes Life Style Link Machine Learning Magnetic Resonance Imaging Measures Methods Mind Modeling Monoclonal Antibody R24 Neurosciences New York City Participant Pathway Analysis Pattern Phenotype Process Psychopathology Pythons Research Research Personnel Resources Rest Saccades Sampling Signal Transduction Source System Testing Time Video Recording Videotape Visualization Voice actigraphy animation archive data archived data base biobank brain health computer network computing resources data archive data portal data resource data standards data tools density digital experimental study fitness gaze independent component analysis innovation movie multimodality network models neuroimaging open source psychiatric symptom recruit response sample fixation secondary analysis signal processing source localization tool visual tracking

项目摘要

Project Summary The Child Mind Institute’s Healthy Brain Network (HBN) is an ongoing initiative focused on creating and sharing a biobank of brain and behavioral data now being collected from 10,000 New York City area children and adolescents (ages 5-21). In response to RFA-MH-120-20 (‘Integration and analysis of BRAIN Initiative data’), we will collect their high-density EEG and continuous eye tracking data, recorded from now over 3,000 young participants while they watch movies and rest, plus participant MR head images, to create a developmental EEG and eye tracking data and analysis resource within the BRAIN Initiative-funded NEMAR portal (NEMAR.org) to the OpenNeuro human neuroimaging resource (OpenNeuro.org). We will store the data in accord with the latest advances in the Brain Imaging Data Standard (BIDS), including innovative co-registration of eye-tracking information and EEG, extraction of anonymized Leadfield matrices for advanced participant-based source localization, and Hierarchical Event Descriptor (HED) annotation of movie and eye tracking events in the data, to enable sophisticated exploratory and model-based analyses by any user of the Neuroscience Gateway (nsgportal.org), which offers processing of complex tasks on the U.S. XSEDE computer network (XSEDE.org) for users of standard neuroscience software. We propose to build on the large existing and readily extensible set of tools for analysis, modeling, and visualization of human EEG data in the world leading EEGLAB software environment for electrophysiological signal processing we develop and maintain (5R01-NS047293-15) (sccn.ucsd.edu/eeglab), to process the large corpus of innovative EEG and synchronous eye tracking data recorded during movie viewing by the HBN project. We will then apply source-resolved event-related analysis models to cortical EEG network dynamics associated with movie watching, will model their changes across development, and will compare the time course of these changes with changes in eye gaze patterns at the same age levels. We will use cortical source-resolved, event-related functional EEG connectivity measures implemented in the Source Information Flow Toolbox (SIFT) to model event-related EEG dynamics of individual participants, and will apply advanced hierarchical Bayes-based methods and statistical assessment to perform statistical testing on subject group models. We will study the development of event-related cortical information flow during movie watching and rest across the large HBN developmental (5-21 years) sample, and compare it to the developmental trajectory of changes in eye gaze patterns during movie viewing.

项目摘要儿童思维学院的健康大脑网络（HBN）是一项持续的计划，致力于创建和现在从10,000个纽约地区的儿童那里收集大脑和行为数据的生物库和青少年（5-21岁）。响应RFA-MH-1220-20（'大脑倡议的整合和分析数据’），我们将收集他们的高密度脑电图和连续的眼睛跟踪数据，从现在起记录3,000多个年轻的参与者在看电影和休息时，加上参与者先生图像，以创建一个大脑倡议资助的Nemar中的发育性脑电图和眼动跟踪数据和分析资源门户（nemar.org）到OpenNeuro人类神经影像资源（OpenNeuro.org）。我们将存储数据根据大脑成像数据标准（BID）的最新进展，包括创新眼球跟踪信息和脑电图的共同注册，提取高级的匿名铅菲尔德材料基于参与者的源本地化和层次结构事件描述符（HED）电影和眼睛的注释跟踪数据中的事件，以启用任何用户的复杂探索性和基于模型的分析 Neuroscience Gateway（NSGPORTAL.org），在美国Xsede上提供复杂任务的处理用于标准神经科学软件用户的计算机网络（xsede.org）。我们建议建立大型现有且易于扩展的工具集，用于分析，建模和可视化人类脑电图数据世界领先的EEGLAB软件环境用于电生理信号处理，我们开发和维护（5R01-NS047293-15）（sccn.ucd.edu/eeglab），以处理大量创新的脑电图和 HBN项目在电影观看期间记录的同步眼动跟踪数据。然后我们将申请与电影相关的皮质EEG网络动态与源分辨的事件相关的分析模型观看，将在整个开发中建模变化，并将比较这些变化的时间过程随着眼睛凝视模式在相同年龄水平上的变化。我们将使用皮质源分辨，事件相关的源信息流量工具箱（SIFT）中实施的功能性脑电图连接度量与事件相关的个体参与者的EEG动态，并将应用基于高级级别的贝叶斯对主题组模型进行统计测试的方法和统计评估。我们将研究在电影观看期间与事件相关的皮质信息流的开发，并在大型HBN上休息开发（5 - 21年）样本，并将其与眼睛凝视变化的发展轨迹进行比较电影观看期间的模式。