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

项目摘要 重度抑郁症（MDD）的终生患病率为16%，预计将成为第二大抑郁症。 到2020年，它将成为美国死亡和残疾的主要原因。MDD的一个核心特征是奖励- 以奖励动机降低和快感缺乏为形式的加工缺陷。这些赤字是 与MDD中皮质纹状体网络的改变有关，但对 可能会促成这些变化。一个可能的机制是内侧前额叶谷氨酸（Glu）的改变。 和GABA，这两种物质最近都与MDD有关，也是MDD的关键风险因素。 MDD的发展、压力。然而，迄今为止，没有研究提供了体内评估Glu和GABA 在MDD或健康对照中，对心理社会应激的反应功能。为了解决这个问题，K99 本应用程序的第一阶段提出了以下培训目标。第一，为了发展技术技能， 需要评估体内Glu和GABA，候选人将从J. Eric博士那里学习MR光谱技术 詹森（K99共同导师）和Dost Ongür博士（顾问）。这将涉及完成一个合并的 MRS/fMRI研究，将探索基线Glu和GABA功能与BOLD fMRI之间的关系 在健康参与者中进行强化学习。其次，候选人将加深他的 了解谷氨酸和GABA功能的作用，在奖励处理通过定向阅读与博士。 肯特贝里奇（顾问），以及他们的相关性，情绪障碍的病理生理学，通过 由Ongür博士监督阅读。第三，他将建立在他的行为建模技能， 研究生院通过应用强化学习范式和相关的Q学习模型 分析，这将是由迈克尔弗兰克博士（顾问）监督;候选人还将参加弗兰克博士的 每月的实验室会议以及他的课程“计算认知神经科学”。最后 候选人将接受他的主要导师Diego Pizzagalli博士的指导和监督， 整合多模态成像数据，设计和分析实验室应激源，并准备 建立独立的实验室。在独立阶段，两个额外的多模态成像 提出了将联合收割机对Glu和GABA功能的MRS评估与fMRI测量相结合的研究， 在心理社会压力源之前和之后的强化学习。这些研究中的第一项将集中在 第二组将包括MDD患者和匹配对照的样本。 通过其使用多模态成像集中在两个主要的神经递质，一个前后应力操纵 包括对照组和MDD患者，拟议的研究将提供重要的新见解 Glu和GABA功能在MDD奖赏处理缺陷的病理生理学中的作用。

Project Summary 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 Ongür (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. Ongür. 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.