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

项目摘要 这项提议的项目的目标是研究预测破坏性的功能和结构的大脑网络。 儿童的行为。颠覆性行为障碍(DBD)影响着全球超过1.13亿名青少年， 以易怒/愤怒、攻击性、不服从和/或反社会行为为特征。这些障碍是 非常有趣，因为它们高度预测以后的犯罪、犯罪和药物滥用 青春期和成年期。在患有自闭症谱系障碍(ASD)的儿童中，DBD也共存于50%以上。一个 大量证据将DBD与支持认知控制的额顶回路的扰动联系在一起 情绪(即情绪调节)，特别是前额背侧和腹侧区域之间的联系 皮质(d/vPFC)和杏仁核。然而，目前尚不清楚情绪调节回路中的失调是否可以 在患有和不患有ASD的儿童中，对DBD的生物标志物做出贡献。重点关注杏仁核-d/vPFC回路， 这项研究将首次研究情绪调节中全脑连接和结构的中断 网络作为DBD和更广泛的儿童破坏性行为问题的跨诊断生物标记物。 首先，我们将开发和测试青少年大脑认知中DBD的多模式成像生物标记物 发展研究数据集，其中包含11,878名9-12岁儿童的临床和功能磁共振数据 第二次放映。接下来，我们将使用fMRI任务来测试情绪调节电路中假想的干扰 对有和没有破坏性行为的儿童进行新的跨诊断样本的认知重新评估 ASD.这项研究将利用与几项NIMH研究产生共鸣的尖端神经成像分析 优先事项：网络神经科学或连接学、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。拟议中的研究将推动 基于大脑的破坏性行为生物标记物的发展可以指导靶向行为的发展 干预措施，改进现有治疗，或确定可能对特定治疗有反应的儿童。 拟议的项目将使卡里姆·易卜拉欣博士准备成为一名独立的临床研究人员，具有独特的 儿童首发精神病患者情绪调节的跨诊断脑生物标志物的利基和专业知识 使用连接学、多模式成像和预测建模方法的疾病。要做到这一点， 拟议的培训将为Karim Ibrahim博士提供网络方面的多学科培训。 神经科学/连接学、机器学习/预测建模、用于分析的生物统计学方法 大型成像数据集和情绪调节电路。培训和研究得到了加强 耶鲁大学儿童研究中心和心理学系的智力严酷环境。这个 指导多学科团队，在功能磁共振成像、连接学和儿童方面具有互补的专业知识 精神病理学确保了研究和培训目标的实现。

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.