Resting state connectivity signatures of obsessive compulsive symptoms

项目摘要 强迫症（OCD）是一种致残性疾病，其发病时间呈双峰型， 儿童时期的病例。亚临床强迫症状（OCS）通常发生在 发展临床上显著的强迫症，尽管随着时间的推移，一些儿童的症状会自然缓解。 然而，OCS的神经基础及其在发育过程中的变化却知之甚少。充分利用 大型，公开可用的数据集和复杂的计算方法，我建议检查功能 儿童和青少年OCS的MRI特征及其纵向轨迹。具体来说，我将申请 青少年大脑认知发展（ABCD）研究的公开数据， 前瞻性社区样本在美国21个不同地点进行纵向跟踪，以揭示 与OCS严重程度相对应的全脑功能MRI模式。基线数据已从 约12，000名9-10岁的儿童，他们的家庭承诺持续跟踪。然后我将使用 来自独立的健康大脑网络（HBN）研究的数据，其中包括来自大约2500名 来自纽约市地区的儿童，以统计学和临床验证这些模式（目标1）。然后我将 将联合收割机基线神经影像学和临床数据与ABCD研究的纵向随访临床数据相结合 检查预测后续OCS轨迹的神经签名（目标2）。最后，我将利用数据 收集自患有临床严重性OCS的儿童（即，强迫症）之前和之后的金标准认知 行为疗法在纽约州精神病研究所（NYSPI），以确定治疗前的预测因素， 缓解和缓解（探索性目的）。总的来说，这些目标将确定大脑连接特征， 对应于OCS共变的可靠模式，这可能暗示了底层的共同机制。 多种症状，并涉及特定的电路，可以针对未来的研究，旨在发展 并测试新的治疗方法和预防策略。此外，这项研究计划还包括一个 详细的培训计划，这将使我更接近我的目标，成为一个医生，科学家专注于临床 和计算精神病学由哥伦比亚大学欧文医学中心的资源支持 和NYSPI，我将加深我在MRI图像处理，神经成像分析和机器方面的技术技能， 学习，同时也提高了我的科学写作，口头陈述和临床技能。

PROJECT SUMMARY Obsessive-compulsive disorder (OCD) is a disabling illness that exhibits bimodal timing of onset, with up to half of cases beginning in childhood. Subclinical obsessive-compulsive symptoms (OCS) often precede the development of clinically significant OCD, though symptoms in some children remit naturally over time. However, the neural bases of OCS and their changes over development are poorly understood. Capitalizing on large, publicly available datasets and sophisticated computational methods, I propose to examine functional MRI signatures of OCS and their longitudinal trajectories in children and adolescents. Specifically, I will apply machine learning to publicly available data from the Adolescent Brain Cognitive Development (ABCD) study, a prospective community sample tracked longitudinally at 21 diverse sites across the United States, to reveal whole-brain functional MRI patterns that correspond to OCS severity. Baseline data is already available from approximately 12,000 children aged 9-10 whose families have committed to ongoing follow-up. I will then use data from the independent Healthy Brain Network (HBN) study, which includes data from approximately 2,500 children from the New York City area, to statistically and clinically validate these patterns (Aim 1). I will then combine baseline neuroimaging and clinical data with longitudinal follow-up clinical data from the ABCD study to examine neural signatures that predict subsequent OCS trajectories (Aim 2). Finally, I will leverage data collected from children with clinical-severity OCS (i.e., OCD) before and after gold-standard cognitive behavioral therapy at the New York State Psychiatric Institute (NYSPI) to identify pre-treatment predictors of response and remission (Exploratory Aim). Collectively, these aims will identify brain connectivity features that correspond to reliable patterns in which OCS co-vary, which could hint at common mechanisms underlying multiple symptoms and implicate specific circuits that can be targeted in future studies aimed at developing and testing novel treatments and prevention strategies. Furthermore, this research proposal integrates a detailed training plan that will bring me closer to my goal of becoming a physician-scientist focused on clinical and computational psychiatry. Supported by the resources of both Columbia University Irving Medical Center and the NYSPI, I will deepen my technical skills in MRI image processing, neuroimaging analysis, and machine learning, while also improving my scientific writing, oral presentation, and clinical skills.