Clarifying the Role of Psychomotor Retardation in Reward-Based Reinforcement Learning Deficits in MDD: A Computational and fMRI Study

阐明精神运动迟缓在 MDD 奖励强化学习缺陷中的作用：一项计算和功能磁共振成像研究

• 批准号: 10591880
• 负责人: Allison Letkiewicz
• 金额: $ 18.16万
• 依托单位: NORTHWESTERN UNIVERSITY AT CHICAGO
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-12-15 至 2027-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10591880
• 关键词: Adult; Age; Antidepressive Agents; Applications Grants; Award; Basal Ganglia; Behavior; Behavioral; Blood flow; Clinical; Cognitive; Computer Models; Corpus striatum structure; Data; Diagnostics Research; Disease; Disease remission; Dorsal; Exhibits; Functional Magnetic Resonance Imaging; Future; Goals; Grain; Grant; Impairment; Individual; Interview; K-Series Research Career Programs; Knowledge; Laboratories; Learning; Life; Major Depressive Disorder; Measures; Mental Depression; Mental disorders; Mentors; Mentorship; Methods; Motor; Neurobiology; Outcome; Parameter Estimation; Parkinson Disease; Play; Principal Investigator; Process; Psychological reinforcement; Psychomotor Performance; Psychopathology; Recurrence; Reporting; Research; Research Domain Criteria; Research Methodology; Research Personnel; Research Project Grants; Rest; Rewards; Role; Schizophrenia; Scientist; Speed; Symptoms; System; Task Performances; Testing; Training; Training Activity; United States National Institutes of Health; Universities; Ventral Striatum; behavior prediction; career; clinically relevant; clinically significant; cognitive process; cost; depressive symptoms; experience; innovation; neural; neural circuit; neural correlate; neuroimaging; prevent; prospective; response; skills; social; treatment response

PROJECT SUMMARY/ABSTRACT Major depressive disorder (MDD) is a highly prevalent and costly mental health disorder. A potentially important contributor to MDD is impaired reward-based reinforcement learning (RBRL). RBRL are a set of processes reflecting difficulty learning which actions are likely to lead to rewarding outcomes, and are clinically significant features of MDD that predicts future depressive symptoms and worse treatment response. MDD, however, is heterogeneous and RBRL may relate to particular MDD symptoms - specifically psychomotor retardation (PmR), a vastly understudied but impairing aspect of MDD that may be especially detrimental for RBRL. Despite overlapping neural circuitry between PmR and RBRL, no study has assessed the impact of PmR on RBRL- related behavior and neural activity in MDD. This is a critical question, as the degree to which RBRL is impaired and which RBRL processes are altered in MDD may depend on PmR. Furthermore, this is highly clinically relevant as ameliorating RBRL deficits related to PmR in MDD may depend on targeting specific RBRL processes. Thus, the overall goal of the proposed K23 is to clarify the role of PmR on RBRL deficits in MDD using innovative computational modeling to parse specific RBRL processes and fMRI. Building on an ongoing R01 (PIs: Dr. Shankman, Mittal, Walther [mentors on this K23]), Aim 1 will test whether experimentally manipulating the demand for psychomotor speed impacts behavioral and neural indicators of RBRL in individuals (ages 18-60) with MDD (N=66) vs. healthy controls (N=44). Aim 2 will test whether a fine-grained laboratory assessment of PmR in MDD predicts behavioral and neural indicators of RBRL, and whether associations between PmR and RBRL are stronger when faster psychomotor speed is required. Aim 3 will examine whether PmR-related RBRL impairment in MDD predicts the course of depression over 1-year. The proposed career development award also aims to provide Dr. Letkiewicz with experiences and training activities that will support her goals of increasing her knowledge of (1) the neural and behavioral basis of psychomotor functioning in MDD, (2) advanced computational modeling to assess reinforcement learning in the context of psychomotor symptoms, (3) multimethod RDoC approaches to studying mechanisms of psychopathology, and (4) grantsmanship and mentorship skills. Her training goals will primarily be accomplished through formal didactics, training with her mentorship team, and the interdisciplinary centers and institutes at Northwestern University. Her mentorship team consists of leading experts in MDD and transdiagnostic research (Dr. Shankman), reinforcement learning and computational modeling (Dr. Kahnt), neuroimaging and motor systems (Dr. Mittal), and psychomotor assessment (Dr. Walther), all of whom have all have active NIH grants and an excellent track record of mentoring early career scientists. This award will prepare Dr. Letkiewicz to submit an R01 grant application and provide her with the skills needed to achieve her long-term career goal of examining the unique and combined contribution of cognitive and motor systems to psychopathology as an independent clinical scientist.

项目摘要/摘要 严重抑郁障碍(MDD)是一种非常普遍且代价高昂的精神健康疾病。一个潜在的重要 MDD的诱因是基于奖赏的强化学习受损(RBRL)。RBRL是一组进程 反映学习困难，哪些行动可能导致有回报的结果，并具有临床意义 MDD的特征，预测未来的抑郁症状和更差的治疗反应。然而，MDD是 异质性和RBRL可能与特定的MDD症状有关-特别是精神运动发育迟缓 (PMR)，MDD的一个极少被研究但具有损害作用的方面，可能对RBRL特别有害。尽管 PMR和RBRL之间的神经回路重叠，还没有研究评估PMR对RBRL的影响。 MDD的相关行为和神经活动。这是一个关键问题，因为RBRL受损的程度 MDD中哪些RBRL过程被更改可能取决于PMR。此外，这是高度临床上的。 与改善MDD中与PMR相关的RBRL缺陷相关可能取决于针对特定的RBRL 流程。因此，拟议的K23的总体目标是澄清PMR对MDD中RBRL缺陷的作用 使用创新的计算建模来解析特定的RBRL流程和功能磁共振成像。建立在正在进行的 R01(PI：Dr.Shankman，Mittal，Walther[这个K23的导师])，Aim 1将在实验中测试 操纵精神运动速度需求对个体RBRL的行为和神经指标的影响 年龄18-60岁的MDD患者(N=66)与健康对照组(N=44)。目标2将测试一个细粒度的实验室 对MDD患者PMR的评估可以预测RBRL的行为和神经指标，以及是否存在关联 当需要更快的精神运动速度时，PMR和RBRL之间的差异更强。目标3将考察 MDD患者PMR相关的RBRL损害可预测1年以上抑郁症的病程。计划中的职业 发展奖还旨在为Letkiewicz博士提供经验和培训活动，以支持 她的目标是增加她关于(1)MDD精神运动功能的神经和行为基础的知识， (2)在精神运动症状的背景下评估强化学习的高级计算建模， (3)研究精神病理学机制的多方法RDoC方法，以及(4)施展精神和 指导技能。她的训练目标将主要通过正式的教学、与她一起训练来实现 导师团队，以及西北大学的跨学科中心和研究所。她的导师身份 团队由MDD和跨诊断研究(Shankman博士)、强化学习方面的领先专家组成 和计算建模(卡恩特博士)、神经成像和运动系统(米塔尔博士)和精神运动 评估(Walther博士)，所有人都有NIH的有效拨款和良好的指导记录 早期职业科学家。该奖项将为Letkiewicz博士提交R01拨款申请做好准备，并提供 她用所需的技能实现了她的长期职业目标，并结合了独特的 作为一名独立的临床科学家，认知和运动系统对精神病理学的贡献。