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 该项目的目标是研究预测破坏性行为的功能和结构大脑网络 儿童的行为。破坏性行为障碍（DBD）影响着全球超过1.13亿的青少年， 其特征在于易怒/愤怒、攻击性、不顺从和/或反社会行为。这些疾病 因为他们是高度预测的少年犯罪，犯罪，和药物滥用，在以后的 青春期和成年期。DBD也同时发生在超过50%的自闭症谱系障碍（ASD）儿童中。一 大量证据表明，DBD与支持认知控制的额顶叶回路的扰动有关 情绪（即，情绪调节），特别是背侧和腹侧前额叶区域之间的联系 皮质（d/vPFC）和杏仁核。然而，目前还不清楚情绪调节回路的失调是否会 在有和没有ASD的儿童中，有助于DBD的生物标志物。重点放在杏仁核-d/vPFC电路上， 这项研究将是第一个研究情绪调节中大脑连接和结构的破坏 网络作为DBD和破坏性行为问题的跨诊断生物标志物在儿童中更广泛。 首先，我们将在青少年脑认知障碍中开发和测试DBD的多模式成像生物标志物。 发育研究数据集，其中包含11，878名9-12岁奥尔兹的临床和fMRI数据， 第二次解放。接下来，我们将使用功能磁共振成像任务来测试假设的情绪调节回路中断 在一个新的，具有破坏性行为的儿童的跨诊断样本中， 自闭症这项研究将利用与NIMH的几项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组学，多模态成像，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生物标志物，可以指导靶向行为的发展。 干预措施，完善现有的治疗方法，或确定可能对特定治疗有反应的儿童。 Karim Ibrahim博士将成为一名独立的临床研究人员， 儿童期精神病患者情绪调节的跨诊断脑生物标志物的生态位和专业知识 使用连接组学、多模式成像和预测建模方法来评估疾病。为了实现这一点， 拟议的培训将为卡里姆·易卜拉欣博士提供网络方面的多学科培训， 神经科学/连接组学，机器学习/预测建模，生物统计方法分析 大型成像数据集和情绪调节电路。培训和研究得到加强， 在耶鲁儿童研究中心和心理学系的智力严谨的环境。的 一个多学科团队的指导，在功能磁共振成像，连接组学和儿童 精神病理学确保研究和培训目标的实现。