Brain Source Analysis of Existing EEG Data in Childhood ADHD

儿童多动症现有脑电图数据的脑源分析

基本信息

批准号：
8225179
负责人：
Sandra K Loo
金额：
$ 8.03万
依托单位：
UNIVERSITY OF CALIFORNIA LOS ANGELES
依托单位国家：
美国
项目类别：
财政年份：
2011
资助国家：
美国
起止时间：
2011-02-15 至 2013-12-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8225179
关键词：
Aftercare Agonist Anatomy Anterior Area Attention deficit hyperactivity disorder Base of the Brain Behavior Behavioral Biological Markers Brain Characteristics Child Childhood Clinical Clinical Trials Cognitive Corpus striatum structure Data Data Analyses Data Set Diagnosis Disease Environment Etiology Event Exhibits Eye Frequencies Functional disorder Funding Guanfacine Image Individual Individual Differences Link Magnetic Resonance Imaging Measures Mental disorders Methods Morbidity - disease rate Motor National Institute of Mental Health Nature Parietal Pathology Pattern Performance Pharmaceutical Preparations Phase Population Process Research Resolution Rest Sample Size Sampling Scalp structure Short-Term Memory Signal Transduction Source Surface Symptoms TNFRSF5 gene Task Performances Testing Translational Research United States National Institutes of Health base cognitive control computerized data processing control trial cost developmental disease dexmethylphenidate independent component analysis indexing innovation memory process neuroimaging neuromechanism psychostimulant public health relevance relating to nervous system research study response success treatment response

项目摘要

DESCRIPTION (provided by applicant): Attention-Deficit Hyperactivity Disorder (ADHD) is one of the most prevalent child psychiatric disorders and is accompanied by significant morbidity. Despite extensive research in this developmental disorder, the etiology and pathophysiology of ADHD remain poorly understood. In response to the specific call by NIMH for R03 proposals (PA-10-64) to further analyze existing data sets, we propose to collaboratively apply innovative data analytic approaches including independent component analysis (ICA) decomposition-based methods to existing EEG data from a large, well-characterized sample of 180 children with ADHD and 60 comparison children collected as part of the ongoing Translational Research in Cognitive Control (TRECC; NIMH P50 MH077248; PI: McCracken) Center. We will use the EEGLAB signal processing environment for electrophysiological data analysis (Delorme & Makeig, 2004; 2R01-NS047293-05) to study the neural sources from which the EEG signal originates. Successful application of these and/or related methods to the problem of discovering and testing brain-based biomarkers for ADHD would be highly innovative in the context of current ADHD research, and would also have clear potential for advancing clinical ADHD research and practice. This study proposes to reanalyze EEG data from an existing set obtained during a NIMH supported clinical trial in ADHD: 1) to investigate the EEG brain networks underlying abnormalities in cognitive control in ADHD and 2) to develop brain-based biomarkers for treatment response to medication in ADHD. PUBLIC HEALTH RELEVANCE: The current study proposes to re-analyze electroencephalographic (EEG) data previously collected during a large NIH-funded research study that examined 180 children with ADHD and 60 healthy comparison children. The re-analysis will utilize leading edge statistical analyses such as independent components analysis (ICA) decomposition methods, which will allow us to determine where in the brain the EEG signal originates. These neural sources may potentially be linked to ADHD symptoms and medication response, which may yield biological markers (or biomarkers) that can be used in the diagnosis and treatment of ADHD.

描述（由申请人提供）：注意力缺陷多动障碍（ADHD）是最常见的儿童精神疾病之一，并且伴随着显着的发病率。尽管对这种发育障碍进行了广泛的研究，但 ADHD 的病因学和病理生理学仍然知之甚少。为了响应 NIMH 对 R03 提案 (PA-10-64) 进一步分析现有数据集的具体呼吁，我们建议协作应用创新的数据分析方法，包括基于独立成分分析 (ICA) 分解的方法到现有的脑电图数据作为正在进行的认知控制转化研究（TRECC；NIMH P50）的一部分，收集了 180 名 ADHD 儿童和 60 名对照儿童的大量、特征明确的样本MH077248；PI：麦克拉肯）中心。我们将使用 EEGLAB 信号处理环境进行电生理数据分析（Delorme & Makeig，2004；2R01-NS047293-05）来研究 EEG 信号起源的神经源。将这些和/或相关方法成功应用于发现和测试基于大脑的 ADHD 生物标志物的问题，在当前 ADHD 研究的背景下将具有高度创新性，并且对于推进 ADHD 临床研究和实践也具有明显的潜力。本研究拟重新分析 NIMH 支持的 ADHD 临床试验中获得的现有数据集的脑电图数据：1）研究 ADHD 认知控制异常的脑电图大脑网络；2）开发基于大脑的生物标志物，用于治疗对药物的反应多动症。公共健康相关性：当前的研究建议重新分析先前在 NIH 资助的一项大型研究中收集的脑电图 (EEG) 数据，该研究检查了 180 名 ADHD 儿童和 60 名健康对照儿童。重新分析将利用前沿统计分析，例如独立成分分析（ICA）分解方法，这将使我们能够确定脑电图信号源自大脑的何处。这些神经源可能与多动症症状和药物反应有关，这可能会产生可用于诊断和治疗多动症的生物标记物。