Stress and MDD effects on mPFC Glutamate and GABA during reward processing

描述（由申请人提供）：重度抑郁症（MDD）的终生患病率为16%，预计到2020年将成为美国第二大死亡和残疾原因。重度抑郁症的一个核心特征是奖励处理缺陷，表现为奖励动机减少和快感缺乏。这些缺陷与MDD患者皮质纹状体网络的改变有关，但对可能导致这些变化的具体机制知之甚少。一种可能的机制是内侧前额叶谷氨酸（Glu）和GABA的改变，这两种物质最近都与重度抑郁症有关，也是重度抑郁症发生的一个关键风险因素——压力。然而，到目前为止，还没有研究提供Glu和GABA功能对重度抑郁症患者或健康对照者的心理社会应激反应的体内评估。为了解决这个问题，这个应用程序的K99阶段提出了以下训练目标。首先，为了培养评估体内Glu和GABA所需的技术技能，候选人将从J. Eric Jensen博士（K99联合导师）和Dost Ong¿r博士（顾问）那里学习mr光谱技术。这将包括完成一项MRS/fMRI联合研究，该研究将探索健康参与者强化学习期间基线Glu和GABA功能与BOLD fMRI信号之间的关系。其次，候选人将通过Kent Berridge博士（顾问）的指导阅读加深他对Glu和GABA功能在奖励处理中的作用的理解，以及通过Ong¿r博士的指导阅读加深他对Glu和GABA功能与情绪障碍病理生理学的相关性的理解。第三，他将通过应用强化学习范式和相关的q -学习模型分析来建立他在研究生院发展的行为建模技能，这将由Michael Frank博士（顾问）监督；候选人还将参加Frank博士每月的实验室会议，以及他的课程“计算认知神经科学”。最后，候选人将接受其主要导师Diego Pizzagalli博士的指导和监督，在多模态成像数据的整合，实验室压力源的设计和分析，以及为独立实验室的发展做准备。在独立阶段，研究人员提出了另外两项多模态成像研究，将Glu和GABA功能的MRS评估与心理社会压力源前后强化学习的fMRI测量相结合。这些研究的第一个重点将是

DESCRIPTION (provided by applicant): With a lifetime prevalence of 16%, Major Depressive Disorder (MDD) is predicted to become the second leading cause of death and disability in the United States by the year 2020. A core feature of MDD is reward- processing deficits in the form of decreased reward motivation and anhedonia. These deficits have been linked to alterations in corticostriatal networks in MDD, but less is known about the specific mechanisms that may contribute to these changes. One candidate mechanism is alterations in medial prefrontal glutamate (Glu) and GABA, both of which have recently been implicated in both MDD, as well as a key risk-factor for the development of MDD, stress. To date however, no study has provided an in vivo assessment of Glu and GABA function in response to psychosocial stress in MDD or in healthy controls. To address this question, the K99 phase of this application proposes the following training goals. First, in order to develop the technical skills needed to assess Glu and GABA in vivo, the candidate will learn MR-Spectroscopy techniques from Dr. J. Eric Jensen (K99 Co-mentor) and Dr. Dost Ong¿r (Consultant). This will involve the completion of a combined MRS/fMRI study that will explore the relationships between baseline Glu and GABA function and BOLD fMRI signals during reinforcement learning in healthy participants. Second, the candidate will deepen his understanding of the role of Glu and GABA function in reward processing through directed readings with Dr. Kent Berridge (Consultant) as well as their relevance to the pathophysiology of mood disorders through readings supervised by Dr. Ong¿r. Third, he will build upon his behavioral modeling skills developed in graduate school through the application of a reinforcement learning paradigm and associated Q-learning model analysis, which will be supervised by Dr. Michael Frank (Consultant); the candidate will also attend Dr. Frank's lab meetings on a monthly basis as well as his course "Computational Cognitive Neuroscience". Finally, the candidate will receive guidance and supervision from his primary mentor, Dr. Diego Pizzagalli, in the integration multimodal imaging data, design and analysis of laboratory stressors, and preparation towards the development of an independent laboratory. During the independent phase, two additional multimodal imaging studies are proposed that will combine MRS assessment of Glu and GABA function with fMRI measures of reinforcement learning both before and after a psycho-social stressor. The first of these studies will be focused on healthy controls, while the second will include a sample of patients with MDD and matched controls. Through its use of multimodal imaging focused on two major neurotransmitters, a pre-post stress manipulation and inclusion of both controls and MDD patients, the proposed research will provide important new insights into the role of Glu and GABA function in the pathophysiology of reward processing deficits in MDD.