Affective Processing and Substance Use Escalation in Adolescence

项目总结/摘要。青春期是一个独特的神经发育时期， 情感过程是明显的，而自上而下的执行控制是在整个年龄范围内。 具体来说，皮层下边缘区对情绪刺激的反应更强烈，并驱动“热”情绪反应。 这些情绪状态可以在冲动和危险行为中表现出来，例如物质使用，并且是一种 慢性复发性物质使用障碍概念的组成理论部分。因此，畸变 在情感处理中，先前与年轻人中有问题的物质使用维持有关 成年期及以后。然而，很少有研究调查这些情感加工畸变是否 尽管理论框架提出了青春期物质使用升级之间的联系， 两个，并建议在其发展的性别差异。了解预防和干预措施 在这一联系中，作为目标至关重要，因为青春期重复使用药物与药物使用有关 疾病，后来的精神病理学和健康问题。相比之下，研究独立地将贫困 工作记忆能力与青春期物质使用的关系如工作记忆和情感加工 包含重叠的大脑功能区域-特别是在额叶区域-它回避了一个问题， 情感处理失常可能会影响“冷”认知处理的有效利用， 存在药物使用升级的风险。尽管有这一系列文献，但没有研究调查过 在关键的情感处理脑区域内，情感刺激引起的神经元激活之间的关系 工作记忆任务期间的刺激对早期物质使用升级结果的影响，并调查性别 在这个轨迹上的差异。更不用说，在大规模和人口统计学上调查这种关系， 不同样本，前瞻性，并在物质使用开始之前。因此，沙利文先生的F31提案旨在 在利用具有里程碑意义的NIH资助的青少年大脑的二次分析中检查这些关系 认知发展（ABCD）研究，在10年内跟踪了11，800多名青少年。功能性神经成像 数据将在整个研究期间使用，沿着大量其他生物心理社会指标， 青少年药物使用增加（9-15岁）。这项奖学金将为沙利文先生提供一个特殊的 有机会在功能性神经成像和成瘾和情感方面的专业知识中建立自己的技能 神经科学，同时也推进纵向和“大数据”分析所需的重要技能。专用 由在这些领域具有专业知识的ABCD研究负责人组成的导师团队将确保提供出色的培训。在 在完成这项研究后，Sullivan先生将实现他发展多样化和高质量技能的目标， 进行F32的建议，并进展到早期的职业生涯作为一个临床研究科学家与专业知识， 成瘾和情感神经科学，功能性神经成像和高级统计技能。这将使 他在团队科学环境中有效地工作，利用复杂的纵向神经成像数据集。

PROJECT SUMMARY/ABSTRACT. Adolescence is a unique neurodevelopmental period where bottom-up affective processes is pronounced while top-down executive control is onboarded throughout this age range. Specifically, subcortical limbic areas are more reactive to emotional stimuli and drive “hot” emotional responding. These emotional states can outwardly appear in impulsive and risky-behavior, such as substance use, and is an integral theoretical component to the notion of chronically relapsing substance use disorders. Thus, aberrations in affective processing have been previously associated with problematic substance use maintenance in young adulthood and onward. Though, few studies have investigated whether these affective processing aberrations predate substance use escalation in adolescence, despite theoretical frameworks proposing a link between the two and suggesting sex differences in their development. Understanding where prevention and interventions could be targeted in this link is critical as repeated substance use in adolescence is linked with substance use disorders, later psychopathology, and health concerns. Comparatively, research has independently linked poorer working memory abilities with substance use in adolescence. As working memory and affective processing contains overlapped functional brain areas—particularly in frontal regions—it begs the question as to whether affective processing aberrations may impact effective utilization of “cold” cognitive processing and potentially represent a risk for escalation of substance use. Despite this line of literature, no studies have investigated the relationship between neuronal activation, within key affective processing brain regions, elicited by affective stimuli during a working memory task on early substance use escalation outcomes, and investigate sex differences in this trajectory. Let alone, investigating this relationship in a large-scale and demographically diverse sample, prospectively, and prior to substance use initiation. Thus, Mr. Sullivan’s F31 proposal seeks to examine these relationships in a secondary-analysis harnessing the landmark NIH-funded Adolescent Brain Cognitive Development (ABCD) Study, following over 11,800 youth across 10 years. Functional neuroimaging data will be utilized across the study period, along with a myriad of other biopsychosocial measures, in predicting adolescent substance use escalation (ages 9-15). This fellowship would provide Mr. Sullivan with an exceptional opportunity to build his skills within functional neuroimaging and expertise in addiction and affective neuroscience, while also advancing vital skills needed for longitudinal and “big data” analysis. A dedicated mentorship team of ABCD Study leaders with expertise in these areas will ensure exceptional training. At the conclusion of this fellowship, Mr. Sullivan will meet his goal of developing a diverse and high-quality skillset to carry into an F32 proposal and progress to an early career as a clinical research scientist with an expertise in addiction and affective neuroscience, functional neuroimaging, and advanced statistical skills. This will enable him to work effectively in a team science setting, utilizing complex, longitudinal neuroimaging datasets.