Cortical network dynamics underlying cognitive control deficits in 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障碍之一，与严重的长期损害有关。尽管进行了广泛的研究，但ADHD的原因和大脑基础仍然知之甚少。在ADHD中描绘“核心缺陷”的尝试仍然难以捉摸，部分原因是这种疾病的异质性，但也是因为迄今为止用来描述ADHD儿童认知功能的方法相对薄弱。我们提出了一种新的EEG源成像方法，该方法在可识别的皮质区域识别独立的EEG信息源，并允许在组和个人水平上进行高度时间分辨的网络分析。我们将把这种方法应用于NIMH资助的一大组现有脑电和行为数据，这些数据来自患有和不患有ADHD的儿童。我们的目标是开发有效的生物标记物，既可以改善ADHD的诊断，又可以通过识别每个ADHD受试者在连接大脑功能和症状的个体差异的广阔前景中所占据的位置，在非分类的个体受试者水平上更好地理解ADHD病理生理学。这可能是迄今为止关于儿童认知表现过程中脑电皮质网络激活的最全面的研究。这项具有近毫秒时间分辨率的全面评估，在大样本中将阐明ADHD认知缺陷的潜在机制。结果将测试和证明新兴的脑电源成像能力，以更好地表征个人和群体在大脑和行为上的差异。如果成功，这种新方法可能会对ADHD进行更敏感的诊断、个体化治疗和治疗监测，并可以通过挖掘现有但仍未得到充分利用的大量脑电数据集和提供新的研究设计和分析来应用于其他精神病理学的研究。

 DESCRIPTION (provided by applicant): Attention-Deficit Hyperactivity Disorder (ADHD), one of the most prevalent child psychiatric disorders, is associated with significant long-term impairment. Despite extensive research, the causes and brain basis of ADHD remain poorly understood. Attempts to delineate `core deficits' in ADHD have remained elusive, in part because of the heterogeneous nature of the disorder but also because of relative weaknesses in methods so far used to characterize cognitive function in children with ADHD. We propose a new EEG source imaging approach that identifies independent sources of EEG information in identifiable cortical areas and permits highly time-resolved network analysis, both at the group and individual levels. We will apply this approach to a large set of NIMH-funded existing EEG and behavioral data collected from children with and without ADHD. Our goal is to develop effective biomarkers that can both improve ADHD diagnosis and to advance the broader NIMH goal of better understanding ADHD pathophysiology at a non-categorical, individual subject level by identifying the position occupied by each ADHD subject in a broad landscape of individual differences linking brain function and symptomology. This will be possibly the most comprehensive look to date at EEG cortical network activation during cognitive performance in children. This comprehensive assessment, with near- millisecond time resolution, in a large sample will clarify the mechanisms underlying cognitive deficits in ADHD. The results will test and demonstrate the ability of emerging EEG source imaging to better characterize individual and group differences in brain and behavior. If successful, this new approach may enable more sensitive diagnosis, individualized treatment, and treatment monitoring for ADHD, and could be applied to study of other psychiatric pathologies, both by mining large existing but still under-exploited EEG data sets and by informing new study designs and analyses.