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.

项目总结/摘要 重度抑郁症（MDD）是一种非常普遍和昂贵的心理健康疾病。一个潜在的重要 MDD的一个重要贡献者是受损的基于奖励的强化学习（RBRL）。RBRL是一组流程 反映了学习哪些行为可能导致有益结果的困难，并且具有临床意义 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MDD症状相关-特别是精神发育迟滞 (PmR)，这是MDD的一个未被充分研究但有损害的方面，可能对RBRL特别有害。尽管 PmR和RBRL之间的神经回路重叠，没有研究评估PmR对RBRL的影响- 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 并且在MDD中改变哪些RBRL过程可以取决于PmR。此外，这是高度临床化的。 相关，因为改善MDD中与PmR相关的RBRL缺陷可能取决于靶向特定的RBRL 流程.因此，建议的K23的总体目标是阐明PmR对MDD中RBRL缺陷的作用 使用创新的计算模型来解析特定的RBRL过程和功能磁共振成像。建立在正在进行的 R01（PI：Shankman博士、Mittal、Walther [本K23的导师]），目标1将测试是否通过实验 操纵对心理速度的需求会影响个体RBRL的行为和神经指标 (ages 18 - 60）与MDD（N = 66）对比健康对照（N = 44）。目标2将测试是否一个细粒度的实验室 MDD中PmR的评估可预测RBRL的行为和神经指标， PmR和RBRL之间的关系在需要更快的心理速度时更强。目标3将审查是否 MDD患者PmR相关RBRL损伤可预测1年以上抑郁症病程提议的职业 发展奖还旨在为Letkiewicz博士提供经验和培训活动， 她的目标是增加她对（1）MDD中精神功能的神经和行为基础的了解， (2)先进的计算模型，以评估强化学习的背景下，精神症状， (3)研究精神病理学机制的多方法RDoC方法，以及（4）granitary和 指导技能。她的培训目标将主要通过正式的教学法来完成， 导师团队，以及西北大学的跨学科中心和研究所。她的指导 团队由MDD和跨诊断研究（Shankman博士），强化学习， 和计算建模（Kahnt博士），神经成像和运动系统（Mittal博士），以及心理学 评估（瓦尔特博士），所有这些人都有积极的NIH赠款和良好的指导记录 早期的科学家该奖项将准备博士Letkiewicz提交R01赠款申请，并提供 她与所需的技能，以实现她的长期职业目标，研究独特的，结合 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。