Neuroscience of Reward-Related Learning and Memory in Depression

描述(由申请人提供)：严重抑郁障碍(MDD)是一个代价高昂的公共卫生问题，MDD的诊断异质性使治疗复杂化。一种方法是研究内表型，这是MDD的关键方面，可能涉及离散神经回路的功能障碍。快感缺乏(快感丧失)是一种很有前途的内表型，但MDD这一核心症状背后的神经认知机制尚不清楚。目前的应用将检验这样一个假设，即刺激-奖励和行动-奖励学习的失败会导致快感缺失。在为期两年的K99阶段，申请者将追求四个目标。首先，为了发展关于MDD如何影响强化学习的定量假设，他将向Michael Frank博士(K99共同导师)学习计算建模。在Frank博士和Diego Pizzagalli博士(K99导师)的指导下，K99研究基金将支持从执行奖励巴甫洛夫条件作用任务的控制组收集功能磁共振数据。这将为R00阶段的MDD受试者的研究奠定基础，同时也提供了有价值的数据，将用于测试强化学习的时间差分算法。为了学习R00阶段的其他技能，申请者还将完成由Frank博士提供的为期一学期的“计算认知神经科学”课程。其次，尼古拉斯·兰格博士将培训申请者进行扩散张量成像分析，以探索与记忆和奖励处理有关的大脑区域的结构完整性和连通性，这可能会在MDD中退化。第三，申请者将接受诊断面试方面的重点培训，当他过渡到独立并开始领导一个专注于以患者为中心的研究的实验室时，这将是非常宝贵的。第四，在Pizzagalli博士和Frank博士的帮助下，申请者将形成有效的工作谈话，并进行教师求职，以建立一个专注于MDD与奖励相关的学习和记忆的实验室。在独立阶段，将对对照组和MDD受试者进行三项与奖励相关的学习和记忆的功能磁共振成像(FMRI)研究。第一项研究将集中在腹侧纹状体，并将使用巴甫洛夫条件反射来检验MDD对线索-奖赏应急学习的影响。第二项研究将集中在背侧纹状体，并将使用工具性条件反射来检查MDD患者的动作奖赏学习。第三项研究将包括对刺激-奖赏关联的显式编码，然后在两个时间点的延迟回忆，以探讨MDD在奖赏信息的编码和巩固过程中如何影响海马纹状体的相互作用。最后，这些研究的MRI数据将被汇集起来，以确定快感缺乏是否反映了纹状体、海马体和前额叶皮质区域之间功能或结构上的弱联系，这些区域以前与奖励处理的不同方面有关。提出的严格范例、计算模型和前沿连通性分析的组合有可能显著提高对MDD病理生理学的理解。 公共卫生相关性：抑郁症是一个代价高昂的公共卫生问题，由于其病理生理机制尚未得到很好的了解，因此很难治疗。快感缺乏是抑郁症的一个关键症状，指的是丧失快感或对愉悦的刺激缺乏反应性。这个项目的目的是调查快感缺乏所涉及的神经认知机制，以便最终能够针对这些疾病进行治疗。

DESCRIPTION (provided by applicant): Major Depressive Disorder (MDD) is a costly public health problem, and the diagnostic heterogeneity of MDD complicates treatment. One approach is to study endophenotypes, key facets of MDD that may involve dysfunction in discrete neural circuits. Anhedonia (loss of pleasure) is a promising endophenotype, but the neurocognitive mechanisms underlying this core symptom of MDD are unclear. The current application would test the hypothesis that failures of stimulus-reward and action-reward learning contribute to anhedonia. During the two-year K99 phase, the applicant will pursue four aims. First, in order to develop quantitative hypotheses about how MDD affects reinforcement learning, he wil learn computational modeling from Dr. Michael Frank (K99 co-mentor). With guidance from Dr. Frank and Dr. Diego Pizzagalli (K99 mentor), the K99 research funds will support collection of fMRI data from controls performing a rewarded Pavlovian conditioning task. This will lay the foundation for a study with MDD subjects in the R00 phase, while also providing valuable data that will be used to test temporal difference algorithms of reinforcement learning. To learn additional skills for the R00 phase, the applicant will also complete a semester-long "Computational Cognitive Neuroscience" course offered by Dr. Frank. Second, Dr. Nicholas Lange wil train the applicant to conduct diffusion tensor imaging analyses in order to probe the structural integrity and connectivity of brain regions implicated in memory and reward processing, and that may be degraded in MDD. Third, the applicant will pursue focused training in diagnostic interviewing, which will be invaluable when he transitions to independence and begins directing a laboratory focused on patient-oriented research. Fourth, with input from Dr. Pizzagalli and Dr. Frank, the applicant will develop an effective job talk and conduct a faculty jo search in order to establish a laboratory focused on reward-related learning and memory in MDD. During the independent phase, three functional magnetic resonance imaging (fMRI) studies of reward- related learning and memory in controls and MDD subjects will be conducted. The first study will focus on the ventral striatum and will use Pavlovian conditioning to examine effects of MDD on cue-reward contingency learning. The second study will focus on the dorsal striatum and will use instrumental conditioning to examine action-reward learning in MDD. The third study will involve explicit encoding of stimulus-reward associations, followed by delayed recall at two time-points, to investigate how MDD affects hippocampal-striatal interactions during encoding and consolidation of rewarding information. Finally, the MRI data from these studies will be pooled to determine whether anhedonia reflects weak functional or structural connections among the striatum, hippocampus, and regions of prefrontal cortex previously implicated in different facets of reward processing. The proposed combination of rigorous paradigms, computational models, and cutting-edge connectivity analyses has the potential to significantly advance understanding of the pathophysiology of MDD. PUBLIC HEALTH RELEVANCE: Depression is a costly public health problem, and it is difficult to treat because its pathophysiology is not well- understood. Anhedonia is a key symptom of depression that refers to the loss of pleasure or lack of reactivity to pleasurable stimuli. The gol of this project is to investigate the neurocognitive mechanisms implicated in anhedonia, so that these can ultimately be targeted for treatment.