Inducing Mirth to Improve Memory in Depression

诱发欢乐以改善抑郁症患者的记忆力

• 批准号: 10675752
• 负责人: Arkadiy Leonidovich Maksimovskiy
• 金额: $ 17.44万
• 依托单位: MCLEAN HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-01 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10675752
• 关键词: Adult; Affect; American; Clinical; Computer Models; Data; Depressed mood; Development; Diagnosis; Diffusion; EP300 gene; Electroencephalography; Emotional; Environment; Event; Event-Related Potentials; Exhibits; Expectancy; Feeling hopeless; Fire - disasters; Goals; Grant; Happiness; Healthcare Systems; Hippocampus; Hospitals; Hour; Image; Individual; Intervention; Interview; Knowledge; Laughter; Learning; Link; Major Depressive Disorder; Measures; Mediating; Memory; Memory impairment; Mental Depression; Mentors; Methods; Modeling; Moods; Neurons; Norepinephrine; P300 Event-Related Potentials; Participant; Performance; Persons; Pilot Projects; Process; Psychological reinforcement; Research; Retrieval; Sampling; Sensory; Severities; Signal Transduction; Speed; Stimulus; Stream; Symptoms; System; Techniques; Testing; Training; Translating; Translational Research; Ventral Tegmental Area; Writing; clinically significant; depressive symptoms; design; dopaminergic neuron; improved; locus ceruleus structure; long term memory; member; memory consolidation; memory encoding; memory recognition; memory retrieval; neural; neuroimaging; neuromechanism; positive mood; reconstruction; response; skills

Major Depressive Disorder (MDD) impacts an estimated 17.3 million adult Americans per year, which places an enormous burden on the affected individuals as well as our healthcare system. An understudied but pernicious component of depression is its harmful impact on people’s ability to remember happy events. If we gained a clear understanding of neural processes that underly this positive memory deficit, we would be better equipped to alleviate this disruption. A promising model of this memory deficit posits that encoding of positive memories is weakened by depression because of dampened dopaminergic (DA) bursts that typically help encode positive information (Dillon & Pizzagalli, 2018). Furthermore, pleasant events might not effectively translate into long-term memory storage (and consequently be harder to retrieve) because of their incongruity with depressed individuals’ dysphoric mood. The goals of the current proposal are to use Event-Related- Potentials (ERPs) and computational modeling to test and extend this model by determining whether positive mood induction (via mirth) can alleviate the positive memory deficit in individuals with MDD. The PI will evoke a P300 ERP in adult participants (96 MDD and 96 Healthy Controls; HCs) during a memory encoding task and examine whether its amplitude (i.e. strength of neural response) relates to participants’ diagnosis and memory performance. All subjects will complete a clinical interview on day 1 (Session 1), complete a positive mood induction (or a control task) and encode 120 pictures day 2 (Session 2). On day 3, following 24-hours to allow for memory consolidation, participants will complete a memory recognition test (Session 3). P300 ERP will be triggered in response to positive, negative, and neutral images during memory encoding, by presenting these pictures at an infrequent (9%) rate intermixed with squares (91% rate). This design will allow us to measure whether P300 amplitude (which signals DA mediated prediction errors) is lowed in participants with MDD, relative to HCs, when they encode positive pictures (Aim 1). We will also apply the Hierarchical Drift Diffusion Model to memory recognition data, in order to test the prediction that adults with MDD will exhibit slower evidence accumulation (thus, impaired memory reconstruction) as they retrieve positive images, in contrast to HCs (Aim 2). Finally, we will test the prediction that a mirth induction will raise positive affect, boost P300 responses to positive pictures, and reduce the positive memory deficit in adults with MDD (Aim 3). By completing this project, the PI will obtain excellent training in applying electroencephalography (EEG), computational modeling, and mood induction techniques towards translational research. This training will build on the PI’s expertise in structural neuroimaging and enable him to conduct more clinically impactful research. McLean Hospital will provide the PI with a world-class environment for conducting this study, with full support for the PI’s training. Completion of this project and training will ultimately enable the PI to accomplish his goal of becoming a leader in translational research with a focus on alterations in positive affect.

重度抑郁症（MDD）每年影响约1730万成年美国人， 对受影响的个人以及我们的医疗保健系统造成巨大负担。一个替补演员， 抑郁症的有害成分是它对人们记忆快乐事件的能力的有害影响。如果我们 如果我们对这种积极记忆缺陷背后的神经过程有了清楚的了解， 有能力缓解这种混乱。这种记忆缺陷的一个有希望的模型假设， 抑郁症会削弱记忆力，因为多巴胺能（DA）爆发的抑制通常有助于 编码积极信息（Dillon & Pizzagalli，2018）。此外，愉快的事件可能不会有效地 由于它们的不协调性， 抑郁症患者的烦躁情绪当前提案的目标是使用事件相关- 电位（ERP）和计算建模来测试和扩展这个模型， 情绪诱导（通过欢笑）可以减轻MDD患者的积极记忆缺陷。PI将唤起一个 成年参与者（96名MDD和96名健康对照; HC）在记忆编码任务期间的P300 ERP， 检查其幅度（即神经反应的强度）是否与参与者的诊断和记忆有关 性能所有受试者将在第1天（第1阶段）完成临床访谈，完成积极情绪 诱导（或控制任务）并在第2天（会话2）编码120张图片。在第3天，24小时后， 为了巩固记忆，参加者将完成记忆识别测试（第3节）。P300 ERP将成为 在记忆编码过程中，通过呈现这些积极的、消极的和中性的图像， 图片在罕见的（9%）率与正方形（91%率）混合。这个设计可以让我们测量 是否P300振幅（信号DA介导的预测错误）在MDD参与者中降低， 相对于HC，当它们编码正图像时（目标1）。我们还将应用分层漂移扩散 对记忆识别数据进行建模，以测试MDD成人将表现出更慢的预测 证据积累（因此，受损的记忆重建），因为他们检索积极的图像，而不是 HC（目标2）。最后，我们将测试一个预测，即欢笑诱导将提高积极的影响，提高P300 对积极图片的反应，并减少MDD成人的积极记忆缺陷（目标3）。通过 完成该项目后，PI将获得应用脑电图（EEG）的出色培训， 计算建模和情绪诱导技术对翻译研究。本次培训将建立 PI在结构神经成像方面的专业知识，使他能够进行更具临床影响力的研究。 姆克林医院将为PI提供开展本研究的世界级环境，并提供全力支持 私家侦探的培训完成本项目和培训将最终使PI实现其目标 成为转化研究的领导者，专注于积极影响的改变。