Neural Mechanisms of Emotional Memory Modulation in Major Depression

描述(申请人提供)：拟议研究的目标是调查健康个体海马体记忆情绪调节的神经机制，以及杏仁核-海马体网络的变化如何在严重抑郁障碍(MDD)的病理生理学中起作用。严重抑郁障碍(MDD)是最常见的终生精神疾病之一，终生患病率为16.5%。它的特点是一系列症状，从抑郁的情绪到自杀的想法，并持续两周以上。记忆障碍是MDD的一种核心内表型，被认为是由于海马区和杏仁核的异常，这两个区域的体积和功能活动都发生了变化。海马体通常被认为是我们学习新的陈述性记忆的能力的基础，而杏仁核被认为在记忆的情绪调节中发挥着重要作用。海马体(尤其是齿状回和CA3亚区)在模式分离中起着至关重要的作用，这是一种使用不同的神经代码将相似或重叠的记忆正交化的计算，这样即使存在干扰的可能性，学习也是可能的。模式分离为通过操纵助记干扰测试海马体功能提供了一个可靠的经验框架。如果将刺激情绪性作为一个参数包括在内，它还可以作为测试杏仁核对海马区记忆的调制的平台。除了更好地了解健康大脑中的记忆网络动态，这个框架还可以用来测试抑郁症患者的假设，并评估这个网络的各个组成部分的功能完整性。为了实现这些目标，我们将使用强大的高分辨率fMRI(1.5 mm各向同性)方法，这些方法能够分离特定于子场的信号，并结合同时处理干扰和情感内容的参数设计。我们将使用这一设计来检查健康大脑中记忆的情绪调节，以及MDD患者这些认知过程中的异常。我们还将使用尖端的超高分辨率(1 Mm)结构和扩散成像方法来更好地了解MDD中杏仁核-海马区的异常。被提出的检验记忆和情绪的经验框架是高度创新的，并且以前从未完成过对MDD的应用。结合最先进的神经成像技术，该项目将对学习、记忆和情绪科学以及对MDD的神经生物学理解产生高度影响。我们使用研究领域标准(RDoC)框架来研究抑郁症和共病焦虑的常见病理生理机制，这些机制将沿着连续的维度进行评估。该项目的成功完成将揭示杏仁核-海马体网络中记忆和情绪处理的神经基础，并提供对抑郁症发生的网络变化的更好理解，为改进诊断和确定新的干预目标铺平道路。

DESCRIPTION (provided by applicant): The goal of the proposed study is to investigate the neural mechanisms underlying the emotional modulation of hippocampal memory in healthy individuals and how alterations in the amygdala-hippocampal network contribute to the pathophysiology of Major Depressive Disorder (MDD). Major depressive disorder (MDD) is one of the most prevalent lifetime psychiatric disorders with a lifetime prevalence of 16.5%. It is characterized by a cluster of symptoms that range from depressed mood to suicidal ideation and persist for a period of over two weeks. Memory impairment is a core endophenotype of MDD and has been attributed to abnormalities in the hippocampus and amygdala, with both regions exhibiting changes in volume and functional activity. The hippocampus is generally believed to underlie our capacity for learning new declarative memories, while the amygdala is thought to play an important role in the emotional modulation of memories. The hippocampus (particularly the dentate gyrus and CA3 subfield) is critically involved in pattern separation, a computation by which similar or overlapping memories are orthogonalized using distinct neural codes, such that learning is possible despite the potential for interference. Pattern separation provides a robust empirical framework for testing hippocampal function by manipulating mnemonic interference. It can further be used as a platform for testing amygdala modulation of hippocampal memory if stimulus emotionality is included as a parameter. In addition to providing a better understanding of memory network dynamics in healthy brains, this framework can also be used to test hypotheses in depressed individuals and assess the functional integrity of various components of this network. To achieve these goals, we will use powerful high-resolution fMRI (1.5 mm isotropic) methods that are capable of dissociating subfield-specific signals, coupled with a parametric design manipulating interference and emotional content concurrently. We will use this design to examine emotional modulation of memory in the healthy brain, as well as abnormalities in these cognitive processes in MDD. We will also employ cutting-edge ultrahigh-resolution (<1mm) structural and diffusion imaging methods to better understand amygdala-hippocampal abnormalities in MDD. The proposed empirical framework for examining memory and emotion is highly innovative and the application to MDD has never been previously accomplished. Coupled with state-of-the-art neuroimaging techniques, this project will have a high impact on the science of learning, memory, and emotion as well as the neurobiological understanding of MDD. We use a Research Domain Criteria (RDoC) framework to investigate common pathophysiological mechanisms in depression and co-morbid anxiety, which will be assessed along continuous dimensions. Successful completion of this project will shed light on the neural basis of memory and emotional processing in the amygdala-hippocampal network and provide a better understanding of the network changes that occur in depression, paving the way to improving diagnosis and defining novel targets for intervention.