Dynamic Brain Mechanisms of Proactive and Reactive Control in Childhood ADHD

儿童多动症主动和反应控制的动态大脑机制

• 批准号: 9090153
• 负责人: Weidong Cai
• 金额: $ 16.9万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-07-01 至 2019-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9090153
• 关键词: Address; Adult; Affect; Age; Algorithms; Anterior; Attention deficit hyperactivity disorder; Autistic Disorder; Behavioral Symptoms; Biological Markers; Brain; Child; Childhood; Classification; Clinical; Clinical Psychology; Clinical assessments; Development; Diagnosis; Disease; Event; Functional Magnetic Resonance Imaging; Future; Goals; Health; Image; Impairment; Impulsivity; Individual Differences; Insula of Reil; Knowledge; Lead; Machine Learning; Measures; Mentored Research Scientist Development Award; Mentors; Modeling; National Institute of Mental Health; Neurodevelopmental Disorder; Neurosciences; Neurosciences Research; Parietal; Parietal Lobe; Prefrontal Cortex; Process; Psychiatry; Psychology; Recruitment Activity; Research; Research Domain Criteria; Research Personnel; Research Project Grants; Schizophrenia; Severities; Signal Transduction; Symptoms; System; Training; Training and Education; United States National Institutes of Health; Variant; Work; associated symptom; base; cingulate cortex; cognitive control; cognitive neuroscience; computerized tools; diagnosis evaluation; experience; inattention; insight; neuroimaging; novel; social; temporal measurement

 DESCRIPTION (provided by applicant): This is an application under the NIH K01 Mentored Research Scientist Development Award Mechanism. The overall goal of the research project is to understand brain mechanisms underlying proactive and reactive control and their relation to individual differences in behavioral symptoms associated with childhood attention deficit hyperactivity disorder (ADHD). Childhood ADHD is characterized by significant impairments in academic and social domains, and deficits in cognitive control are at the core of these impairments. Recent research suggests that cognitive control operates via two distinct modes: proactive and reactive. However, the extent to which proactive and reactive control processes influence behavioral symptoms associated with ADHD remains unknown. This proposal will address this fundamental question by assessing how imaging-defined constructs for proactive and reactive control affect inattention and impulsivity in children with and without ADHD using the NIMH Research Domain Criteria (RDoC) strategy. The candidate will use a novel systems neuroscience approach to investigate dynamic brain mechanisms of proactive and reactive control in children and their relation to symptoms associated with ADHD. The Specific Aims of this project are: (1) To investigate dynamic causal interactions in brain networks during reactive and proactive control in children, (2) To investigate how aberrant dynamic causal interactions during reactive and proactive control affect impulsivity and inattention in children using the RDoC approach, (3) To examine whether dynamic causal interactions during reactive and proactive control can differentiate children with clinically diagnosed ADHD from typically-developing children, and (4) To explore biomarkers for symptom prediction and classification using multivariate imaging-defined constructs of reactive and proactive control. The proposed studies will deepen our understanding of fundamental brain mechanisms underlying individual differences in cognitive control in children with and without ADHD. It will also advance the use of new computational tools in clinical neuroscience research and provide a systems neuroscience framework for future studies of cognitive control in other neurodevelopmental disorders, including autism and schizophrenia. The candidate will undergo a rigorous education and training plan to increase expertise in clinical aspects of ADHD research, advanced brain network analyses and machine learning algorithms for symptom prediction. The candidate will be mentored and trained by leading experts in the fields of clinical psychology, psychiatry, developmental and cognitive neuroscience, brain network analyses and machine learning. The candidate will also gain critical experience in clinical assessments necessary for successfully working with children with ADHD. Formal coursework and attendance at seminars in psychology, psychiatry, connectomics and machine learning will assist in achieving this goal. Completing the proposed project will enable the candidate to become a successful independent investigator in the fields of clinical and developmental cognitive neuroscience.

 描述（由申请人提供）：这是根据NIH K01指导研究科学家发展奖励机制的申请。该研究项目的总体目标是了解主动控制和反应控制的大脑机制，以及它们与儿童注意力缺陷多动障碍（ADHD）相关的行为症状的个体差异的关系。儿童多动症的特点是在学术和社会领域的显着障碍，和认知控制的缺陷是这些障碍的核心。最近的研究表明，认知控制通过两种不同的模式运作：主动和反应。然而，主动和反应性控制过程在多大程度上影响与ADHD相关的行为症状仍然是未知的。这项提案将通过评估如何使用NIMH研究领域标准（RDoC）策略，在患有和不患有ADHD的儿童中，成像定义的主动和反应控制结构如何影响注意力不集中和冲动来解决这个基本问题。 候选人将使用一种新的系统神经科学方法来研究儿童主动和反应控制的动态大脑机制及其与ADHD相关症状的关系。该项目的具体目标是：（1）研究儿童在反应性和主动性控制过程中大脑网络中的动态因果相互作用，（2）使用RDoC方法研究反应性和主动性控制过程中异常的动态因果相互作用如何影响儿童的冲动性和注意力不集中，（3）研究反应性和主动性控制过程中的动态因果相互作用是否可以区分临床诊断为ADHD的儿童和典型发育儿童，和（4）探索使用多变量成像定义的反应性和主动控制结构进行症状预测和分类的生物标志物。拟议的研究将加深我们对ADHD儿童和非ADHD儿童认知控制个体差异的基本大脑机制的理解。它还将促进使用 新的计算工具在临床神经科学研究和提供一个系统的神经科学框架，为未来的研究认知控制在其他神经发育障碍，包括自闭症和精神分裂症。候选人将接受严格的教育和培训计划，以增加ADHD研究，先进的大脑网络分析和机器学习算法的临床方面的专业知识，用于症状预测。候选人将由临床心理学，精神病学，发展和认知神经科学，大脑网络分析和机器学习领域的领先专家指导和培训。候选人还将获得成功与ADHD儿童合作所需的临床评估方面的关键经验。正式的课程和参加心理学，精神病学，连接组学和机器学习的研讨会将有助于实现这一目标。完成拟议的项目将使候选人成为临床和发展认知神经科学领域的成功独立研究者。