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 重度抑郁症（MDD）是一种高度普遍且昂贵的精神健康障碍。潜在的重要 MDD的贡献者是基于奖励的强化学习（RBRL）。 RBRL是一组过程 反映难以学习哪些行动可能导致奖励结果，并且在临床上具有重要意义 MDD的特征可预测未来的抑郁症状和较差的治疗反应。但是，MDD是 异质和RBRL可能与特定的MDD症状有关 - 特别是心理障碍 （PMR），这是MDD的大量研究但损害的方面，可能对RBRL尤其有害。尽管 PMR和RBRL之间的重叠神经回路，尚无研究评估PMR对RBRL-的影响 MDD中的相关行为和神经活动。这是一个关键的问题，因为RBRL受损的程度 在MDD中改变了哪些RBRL过程可能取决于PMR。此外，这在临床上是高度的 与MDD中与PMR相关的改善RBRL缺陷相关，可能取决于针对特定的RBRL 过程。因此，提出的K23的总体目标是阐明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RBR过程和fMRI。建立在一个正在进行的 R01（PIS：Shankman博士，Mittal，Walther [此K23上的导师]），AIM 1将测试是否在实验上 操纵对精神运动速度的需求会影响个体RBRL的行为和神经指标 （18-60岁）使用MDD（n = 66）与健康对照（n = 44）。 AIM 2将测试是否是细粒实验室 MDD中PMR的评估可以预测RBRL的行为和神经指标，以及是否关联 当需要更快的精神运动速度时，PMR和RBRL之间的强度更强。 AIM 3将检查是否 MDD中与PMR相关的RBRL损伤预测了1年的抑郁症。拟议的职业 开发奖还旨在为Letkiewicz博士提供将支持的经验和培训活动 她增加了对（1）MDD心理运动功能的神经和行为基础知识的目标， （2）在心理症状的背景下评估强化学习的高级计算建模， （3）多途径RDOC研究心理病理学机制的方法，以及（4）赠款和赠款和 指导技能。她的培训目标将主要通过正式的教学法来实现，并与她一起训练 指导团队以及西北大学的跨学科中心和机构。她的指导 团队由MDD和Transdegnostic Research（Shankman博士）的领先专家组成，强化学习 和计算建模（Kahnt博士），神经影像学和运动系统（Mittal博士）和心理运动 评估（Walther博士），所有人都拥有活跃的NIH赠款和指导的出色记录 早期职业科学家。该奖项将为Letkiewicz博士准备提交R01赠款申请并提供 她具有实现她长期职业目标所需的技能，以检查独特而合并的能力 认知和运动系统对精神病理学作为独立临床科学家的贡献。