Identifying the effects of methylphenidate on brain network dynamics of cognitive control and motivation in pediatric ADHD

项目总结/摘要 在美国，约9%的青少年被诊断为儿童多动症，并具有长期的精神衰弱症状。 健康、社会和教育影响。ADHD的主要特征是注意力不集中， 多动/冲动行为，哌醋甲酯是缓解症状的第一线治疗。而 一般有效，20-30%的ADHD青少年对哌醋甲酯没有反应。目前未知 为什么哌醋甲酯不能成功地治疗一部分患有ADHD的青少年，也不知道谁会成功。 在治疗开始前作出反应。拟议的工作旨在通过测试效果来填补这一知识空白 哌醋甲酯对两个神经生物学系统被认为是在多动症中断，目的是确定 哌甲酯反应的生物标志物。ADHD的双途径模型提出， 认知控制和动机处理的神经生物学途径引起ADHD 症状，提供了两个候选途径，哌甲酯可能会采取行动。我们建议研究这个问题， 在全脑水平的框架，采用功能连接和图形理论工具来测试 哌醋甲酯对认知控制和奖励反应任务中大脑组织的影响 治疗未接受过药物治疗的ADHD儿童。这项工作将使用最先进的方法来模拟整个大脑 功能连接的数量级秒，以调查动态变化的大脑组织的 在认知任务中假设的路径。使用动态功能连接方法，我们可以 测量大脑区域之间连接的灵活性，以功能连接模式的频率为索引 在整个任务过程中发生变化。我们预测，在认知控制任务中，属于 认知控制网络（额顶叶、扣带-鳃盖、默认模式）的超连接程度将降低 对哌甲酯更灵活（具体目标1）。我们进一步预测，当奖励被引入到一个 认知控制任务，支持动机加工（奖赏，突显，默认模式）的网络，意志 重新配置，变得更加灵活;我们进一步预测，这种重新配置将更加明显， 哌甲酯（具体目标2）。最后，我们从这些假设中预测大脑区域的灵活性， 途径将是对哌醋甲酯反应的强有力的预测因子（通过性能操作化 控制要求认知任务的改善）超过基线行为测量， ADHD神经病学（探索性目标3）。这项工作结合了新的工具（动态功能连接）， 新的方法（建模跨认知任务状态的大脑组织），以形成一个全面的模型， 哌醋甲酯对儿童多动症的影响通过识别大脑网络组织的特征， 通过测试这些特征如何预测行为变化，我们可以确定 新的生物标志物可以为治疗计划提供信息。这项工作有可能贡献新的信息 更有针对性的治疗，最终改善患有ADHD的青少年的结果。

Project Summary/Abstract Pediatric ADHD is diagnosed in ~9% of youths in the United States and has long-term debilitating mental health, social, and educational effects. ADHD is primarily characterized by inattentive and hyperactive/impulsive behaviors, and methylphenidate is a first line of treatment to alleviate symptoms. While generally effective, 20-30% of youth with ADHD do not respond to methylphenidate. It is currently unknown why methylphenidate does not successfully treat a subset of youth with ADHD, nor is it known who will respond before treatment is initiated. The proposed work aims to fill this knowledge gap by testing the effects of methylphenidate on two neurobiological systems thought to be disrupted in ADHD, with a goal of identifying biomarkers of methylphenidate response. The dual pathway model of ADHD proposes that dysfunction in neurobiological pathways underlying cognitive control and motivational processing gives rise to ADHD symptoms, providing two candidate pathways that methylphenidate may act upon. We propose to examine this framework at the whole brain level by employing functional connectivity and graph theoretical tools to test the effects of methylphenidate on brain organization during tasks that tax cognitive control and reward responsivity in medication naïve children with ADHD. This work will use cutting edge methods that model whole brain functional connectivity on the order of seconds to investigate dynamic changes in brain organization of the hypothesized pathways across the cognitive tasks. Using dynamic functional connectivity approaches we can measure flexibility of connections between brain regions, indexed by how often functional connectivity patterns change across the course of a task. We predict that during a cognitive control task, regions belonging to cognitive control networks (fronto-parietal, cingulo-opercular, default mode) will become less hyperconnected and more flexible on methylphenidate (Specific Aim 1). We further predict that when reward is introduced to a cognitive control task, networks supporting motivational processing (reward, salience, default mode) will reconfigure and become more flexible; we further predict that this reconfiguration will be more pronounced on methylphenidate (Specific Aim 2). Lastly, we predict that flexibility of brain regions from these hypothesized pathways will be powerful predictors of response to methylphenidate (operationalized by performance improvement on control demanding cognitive tasks) above and beyond baseline behavioral measures of ADHD symptomology (Exploratory Aim 3). This work combines new tools (dynamic functional connectivity) with new approaches (modeling brain organization across cognitive task states) to form a comprehensive model of the effects of methylphenidate in pediatric ADHD. By identifying features of brain network organization that change on methylphenidate and testing how these features predict behavioral change, we stand to identify novel biomarkers that can inform treatment plans. This work has the potential to contribute novel information towards more targeted treatments, ultimately improving outcomes for youths with ADHD.