Multimodal imaging biomarkers of cognitive control network deficits in youths with disruptive behavior

具有破坏性行为的青少年认知控制网络缺陷的多模态成像生物标志物

• 批准号: 10705654
• 负责人: Karim Ibrahim
• 金额: $ 19.24万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-16 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10705654
• 关键词: 12 year old; Achievement; Adolescence; Adolescent; Adult; Advanced Development; Affect; Aggressive behavior; Amygdaloid structure; Anger; Area; Behavior; Behavior Disorders; Big Data Methods; Biological Markers; Biometry; Brain; Buffers; Child; Childhood; Clinical; Computer Models; DSM-V; Data; Data Set; Development; Diagnosis; Diagnostic; Dimensions; Disease; Disruptive Behavior Disorder; Dorsal; Emotions; Ensure; Environment; Exhibits; Functional Magnetic Resonance Imaging; Functional disorder; Generations; Goals; Image; Impairment; Individual Differences; Intervention; Link; Machine Learning; Magnetic Resonance Imaging; Mental disorders; Mentorship; Modality; Modeling; Multimodal Imaging; National Institute of Mental Health; Neurobiology; Neurosciences; Outcome; Prefrontal Cortex; Problem behavior; Psychology; Psychopathology; Public Health; Research; Research Design; Research Domain Criteria; Research Personnel; Research Priority; Rest; Risk; Sampling; Services; Severities; Sex Differences; Site; Structure; Subgroup; Substance abuse problem; Surface; Symptoms; Testing; Thick; Training; Work; Youth; adolescent with autism spectrum disorder; antisocial behavior; autism spectrum disorder; autistic children; biomarker development; biotypes; boys; brain based; callous unemotional trait; cognitive control; cognitive development; cognitive reappraisal; cognitive task; connectome; data modeling; diagnostic biomarker; disorder control; disorder subtype; emotion regulation; girls; gray matter; imaging biomarker; interest; multidisciplinary; neuroimaging; non-compliance; novel; open data; predictive modeling; recruit; sex; translational neuroscience; translational potential

Project Summary The goal of the proposed project is to investigate functional and structural brain networks that predict disruptive behavior in children. Disruptive behavior disorders (DBD) affect over 113 million youths worldwide and are characterized by irritability/anger, aggression, noncompliance, and/or antisocial behavior. These disorders are of great interest because they are highly predictive of delinquency, criminality, and substance abuse in later adolescence and adulthood. DBD also co-occur in over 50% of children with autism spectrum disorder (ASD). A large body of evidence links DBD with perturbations in frontoparietal circuitry that support the cognitive control of emotion (i.e., emotion regulation), particularly connections between regions of the dorsal and ventral prefrontal cortex (d/vPFC) and amygdala. However, it is unclear if dysregulation in emotion regulation circuitry can contribute to a biomarker of DBD in children with and without ASD. With a focus on the amygdala-d/vPFC circuit, this study will be the first to examine disruptions in brain-wide connectivity and structure in emotion regulation networks as a transdiagnostic biomarker of DBD and disruptive behavior problems more broadly in children. First, we will develop and test a multimodal imaging biomarker of DBD in the Adolescent Brain Cognitive Development study dataset, which contains clinical and fMRI data for 11,878 9-12 year olds in the first and second releases. Next, we will test the hypothesized disruptions in emotion regulation circuitry using a fMRI task of cognitive reappraisal in a new, transdiagnostic sample of children with disruptive behavior with and without ASD. This study will leverage cutting-edge neuroimaging analytics that resonate with several NIMH research priorities: network neuroscience or connectomics, multimodal imaging, computational modeling (machine learning), big data analytics, and the RDoC domain of cognitive control. The proposed research will push forward the development of brain-based biomarkers of disruptive behavior that could guide development of targeted interventions, refinement of existing treatments, or identify children likely to respond to a particular treatment. The proposed project will prepare Dr. Karim Ibrahim to become an independent clinical researcher with a unique niche and expertise in transdiagnostic brain biomarkers of emotion regulation in childhood-onset psychiatric disorders using connectomics, multimodal imaging, and predictive modeling approaches. To accomplish this, the proposed training will provide Dr. Karim Ibrahim with multidisciplinary training in network neuroscience/connectomics, machine learning/predictive modeling, biostatistical approaches for the analysis of large imaging datasets, and emotion regulation circuitry. The training and research are enhanced by the intellectually rigorous environment at the Yale Child Study Center and Department of Psychology. The mentorship of a multidisciplinary team with complementary expertise in fMRI, connectomics, and child psychopathology ensures achievement of the research and training aims.

项目摘要 拟议项目的目的是研究预测破坏性的功能和结构性大脑网络 儿童的行为。破坏性行为障碍（DBD）在全球范围内影响超过1.13亿年轻人 以烦躁/愤怒，侵略性，不合格和/或反社会行为为特征。这些疾病是 引起极大的兴趣，因为他们高度预测了违法，犯罪和滥用毒品 青春期和成年。 DBD也同时发生50％的自闭症谱系障碍儿童（ASD）。一个 大量证据将DBD与支持认知控制的额叶电路中的扰动联系起来 情绪（即情绪调节），特别是背侧和腹前额叶区域之间的联系 皮质（D/VPFC）和杏仁核。但是，尚不清楚情绪调节电路中的失调是否可以 在患有和没有ASD的儿童中有助于DBD的生物标志物。重点是杏仁核D/VPFC电路， 这项研究将是第一个检查脑部连通性和情绪调节结构中断的干扰 在儿童中，网络是DBD的转诊生物标志物和破坏性行为问题。 首先，我们将开发和测试青少年脑认知中DBD的多模式成像生物标志物 开发研究数据集，其中包含第一个9-12岁的11,878 9-12岁的临床和fMRI数据 第二版。接下来，我们将使用fMRI任务测试情绪调节电路中假设的破坏 在有和没有的新的，具有破坏性行为的儿童的新的经诊断样本中，认知重新评估 ASD。这项研究将利用尖端的神经影像学分析，与几项NIMH研究产生共鸣 优先级：网络神经科学或连接组学，多模式成像，计算建模（机器 学习），大数据分析和认知控制的RDOC领域。拟议的研究将推动 开发基于大脑的破坏性行为的生物标志物，可以指导目标发展 干预措施，对现有治疗方法的改进或确定可能对特定治疗的儿童。 拟议的项目将使Karim Ibrahim博士准备成为一名独特的临床研究人员 在童年时期的精神病患者的转诊性脑生物标志物中的利基和专业知识 使用连接组学，多模式成像和预测建模方法的疾病。为此， 拟议的培训将为Karim Ibrahim博士提供网络中的多学科培训 神经科学/连接学，机器学习/预测建模，生物统计学方法，用于分析 大型成像数据集和情绪调节电路。培训和研究通过 耶鲁儿童学习中心和心理学系的智力严格环境。这 具有互补专业知识的多学科团队的指导 心理病理学确保实现研究和培训目的。