An integrative framework of cognitive control and reward modulation in children with ADHD: from brain dynamics to clinical symptoms

项目摘要 注意缺陷多动障碍(ADHD)是最常见的神经发育障碍之一， 全球患病率从5%到10%不等。在过去的二十年里，随着诊断率的上升，童年 ADHD已成为受影响的个人、家庭和社会的重大社会和经济负担 大号的。ADHD的特点是认知控制障碍，对 学术和社会功能。认知控制需要主动和被动的动态参与 控制过程，这些过程中的异常是行为缺陷的基础，包括升高 响应变化无常，停车速度慢。一项相关的研究表明，奖励可能会增加 ADHD患者的停车速度和反应变异性降低，一些人甚至达到了类似的 表现为典型的发展中儿童(TDC)。然而，潜在的认知和大脑机制 ADHD患者的主动性和反应性控制、奖赏调节及其与临床症状的关系 未知。在这里，我们开发了一种创新的多成分认知、神经科学和 解决这一差距并促进对大脑功能障碍的基本理解的计算框架 连接ADHD儿童认知控制和奖励系统的回路。认知和认知功能的最新进展 计算神经科学已经证明，认知控制依赖于动态的大脑状态 以大脑功能回路中的动态相互作用为特征。拟议中的研究将严格测试 注意缺陷多动障碍的理论认知和神经科学模型 反应性控制以及涉及认知控制、默认模式和奖励系统的动态大脑回路 在患有多动症的儿童中。我们将整合我们正在进行的认知研究的多个高影响线 控制，多动症儿童，和大脑回路动力学。重要的是，我们将利用多部小说 揭示认知和大脑过程动力学的计算模型。建议的研究将会：(1) 研究奖励如何调节ADHD儿童的主动性和反应性控制，(2)确定如何 主动性和反应性控制奖赏调节的异常与核心临床症状相关 儿童主动性和反应性控制奖赏调节的动态脑回路特征 对于ADHD，(4)确定动态大脑回路的奖赏调制如何涉及认知控制和 奖赏系统与核心症状有关，(5)识别多变量认知和神经生物学特征 用于儿童ADHD的分类和ADHD核心临床症状的预测。建议进行的研究 将有助于更深入地理解潜在的奖赏调节的认知和大脑机制 认知控制，这将有助于开发更有效和更精确的干预儿童ADHD在 未来。我们在这里开发的认知、神经科学和计算框架可以广泛应用于 研究许多表现出类似认知缺陷的精神障碍，如精神分裂症和自闭症。

Project Summary Attention deficit hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders, with prevalence rates ranging from 5-10% globally. With rising diagnosis rates in the last two decades, childhood ADHD has become a significant social and financial burden to affected individuals, families, and society at large. ADHD is characterized by impairments in cognitive control, with adverse life-long consequences for academic and social functioning. Cognitive control requires dynamic engagement of proactive and reactive control processes, and aberrancies in these processes underlie behavioral deficits, including elevated response variability and slow stopping speed. A related line of research suggests that rewards may increase stopping speed and reduce response variability in ADHD, with some individuals even reaching similar performance as typically developing children (TDC). However, the cognitive and brain mechanisms underlying proactive and reactive control, their modulation by reward and relation to clinical symptoms in ADHD are unknown. Here we develop an innovative multi-componential cognitive, neuroscience, and computational framework to address this gap and advance fundamental understanding of dysfunctional brain circuits linking cognitive control and reward systems in children with ADHD. Recent progress in cognitive and computational neuroscience has demonstrated that cognitive control relies on dynamic brain states characterized by dynamic interactions in functional brain circuits. The proposed studies will rigorously test theoretical cognitive and neuroscience models of ADHD by examining reward modulation of proactive and reactive control as well as dynamic brain circuits involving cognitive control, default mode and reward systems in children with ADHD. We will integrate multiple high-impact lines of our ongoing research on cognitive control, children with ADHD, and brain circuit dynamics. Importantly, we will leverage multiple novel computational models to uncover dynamics of cognitive and brain processes. The proposed studies will: (1) investigate how reward modulates proactive and reactive control in children with ADHD, (2) determine how aberrations in reward modulation of proactive and reactive control are related to core clinical symptoms, (3) characterize dynamic brain circuits underlying reward modulation of proactive and reactive control in children with ADHD, (4) determine how reward modulation of dynamic brain circuits involving cognitive control and reward systems are related to core symptoms, (5) identify multivariate cognitive and neurobiological features for classification of childhood ADHD and prediction of core clinical symptoms of ADHD. The proposed studies will facilitate a deeper understanding of cognitive and brain mechanisms underlying reward modulation of cognitive control, which will facilitate developing more effective and precise intervention for childhood ADHD in the future. Our cognitive, neuroscience and computational framework developed here can be widely applied to study many psychiatric disorders that manifest similar cognitive deficits, such as schizophrenia and autism.