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

• 批准号: 8032342
• 负责人: Sandra K Loo
• 金额: $ 8.74万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-02-15 至 2012-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8032342
• 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; relating to nervous system; research study; response; success; treatment response

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）：注意缺陷多动障碍（ADHD）是最常见的儿童精神疾病之一，并伴有显著的发病率。尽管对这种发育障碍进行了广泛的研究，但对ADHD的病因和病理生理仍知之甚少。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，我们建议合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，对来自正在进行的认知控制转化研究（TRECC; NIMH P50 MH077248; PI: McCracken）中心的180名ADHD儿童和60名对照儿童的现有脑电图数据进行分析。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），研究脑电信号产生的神经源。成功应用这些方法和/或相关方法来发现和测试ADHD的基于大脑的生物标志物，在当前ADHD研究的背景下将是高度创新的，也将具有推进ADHD临床研究和实践的明显潜力。本研究拟重新分析在NIMH支持的ADHD临床试验中获得的一组现有EEG数据：1)研究ADHD认知控制异常的脑电图脑网络；2)开发基于脑的ADHD药物治疗反应生物标志物。