Investigating emotional reactivity in depression using event-related potentials

描述（由申请人提供）：重度抑郁症（MDD）由于其高患病率、早发性、慢性和功能障碍而具有巨大的公共卫生重要性。虽然行为和外周生理学研究已经确定了与MDD相关的情绪反应性的缺陷，导致情绪背景不敏感（ECI）的理论模型，神经成像研究已经产生了根据感兴趣的区域和使用的情感刺激的类型的低活性和多活性的证据。一种可能性是，MDD中的情绪反应是由刺激的个人相关性调节的，这样对规范刺激的反应是迟钝的，对具体刺激的反应是增加的，尽管这还有待于在单个样本中进行测试。这项拟议中的研究试图使用三种直接测量大脑活动的方法来研究这个问题：事件相关电位（ERP），脑电图（EEG）的频谱分析和功能性磁共振成像（fMRI）。通过整合这三种方法，本研究将很好地装备，以提高我们的理解的病理生理机制的异常情绪处理的MDD，这是符合使命的部门的神经科学和基本行为科学在国家精神卫生研究所。此外，通过寻求系统地表征MDD中的特定神经异常，目前的研究可以提供客观的生物学指标，可以为未来的临床问题（如治疗选择，跟踪治疗进展和预测恢复）提供信息。为了检验个人相关性对抑郁症患者异常情绪加工的影响，本研究将考虑30名抑郁症患者和30名从未抑郁过的对照者的神经活动，有三个具体目标：（a）比较ERP/EEG对规范和具体情绪刺激的反应;（B）比较ERP/EEG对奖励和绩效反馈的反应;以及（c）使用功能性磁共振成像来检查神经对情绪面孔和奖励的激活。这项研究还包括几个基本的培训组成部分，这将为申请人提供在几个领域获得进一步的临床和方法学专业知识的机会。作为本申请的共同发起人，丹尼尔克莱因博士将提供情绪障碍评估方面的高级培训。Lilianne Mujica-Parodi博士也是共同赞助者，将提供fMRI数据采集、分析和解释方面的培训。本提案中还包括两名顾问，以提供高级统计培训：Joseph Dien博士在将主成分分析和源定位技术应用于ERP/EEG数据集方面具有专业知识，Andreas Keil博士在使用时频方法分析振荡EEG数据方面具有专业知识。最后，拟议的研究和培训的实施将由Greg Hajcak博士监督，他是该提案的发起人和申请人的主要学术导师。 公共卫生相关性：重性抑郁症（MDD）是一种具有巨大公共卫生重要性的疾病，因为其患病率高，发病早，慢性和功能障碍。目前的项目旨在研究大脑活动对情绪刺激的特定模式，以揭示MDD异常情绪反应的神经机制。这样做，这将有助于最近的研究工作，以确定与MDD相关的生物标志物，可用于促进有效的治疗选择，跟踪治疗进展，并预测恢复。

DESCRIPTION (provided by applicant): Major depressive disorder (MDD) is of immense public health importance because of its high prevalence, early onset, chronicity, and functional impairment. While behavioral and peripheral physiological studies have identified a deficit in emotional reactivity associated with MDD, leading to an emotion context insensitivity (ECI) theoretical model, neuro imaging studies have yielded evidence of both hypo- and hyperactivity depending on the region of interest and the type of affective stimuli used. One possibility is that emotional reactivity in MDD is moderated by the personal relevance of stimuli, such that reactivity to normative stimuli is blunted and reactivity to idiographic stimuli is increased, although this has yet to be tested within a single sample. The proposed study seeks to examine this issue using three direct measures of brain activity: event-related potentials (ERPs), spectral analysis of the electroencephalogram (EEG), and functional magnetic resonance imaging (fMRI). By integrating these three methods, this study will be well-equipped to enhance our understanding of the pathophysiological mechanisms underlying abnormal emotional processing in MDD, which is consistent with the mission of the Division of Neuroscience and Basic Behavioral Science at the National Institute of Mental Health. Further, by seeking to systematically characterize specific neural abnormalities in MDD, the current study may provide objective biological measures that can inform future work on clinical issues such as treatment selection, tracking treatment progress, and predicting recovery. To examine the influence of personal relevance on abnormal emotional processing in MDD, the proposed research will consider neural activity among 30 adults with current MDD and 30 never-depressed controls, with three specific aims: (a) to compare ERP/EEG responses to normative and idiographic emotional stimuli; (b) to compare ERP/EEG responses to reward- and performance-based feedback; and (c) to use fMRI to examine neural activation to emotional faces and rewards. This research also incorporates several essential training components that will provide the opportunity for the applicant to attain further clinical and methodological expertise in several domains. As a co-sponsor of this application, Dr. Daniel Klein will provide advanced training in the assessment of mood disorders. Dr. Lilianne Mujica-Parodi, also a co-sponsor, will provide training in the acquisition, analysis, and interpretation of fMRI data. Two consultants are also included in this proposal to provide advanced statistical training: Dr. Joseph Dien has expertise in the application of principal components analysis and source localization techniques to ERP/EEG data sets, and Dr. Andreas Keil has expertise in using time-frequency approaches to analyze oscillatory EEG data. Finally, the implementation of the proposed research and training will be overseen by Dr. Greg Hajcak, the sponsor of this proposal and the primary academic mentor of the applicant. PUBLIC HEALTH RELEVANCE: Major depressive disorder (MDD) is an illness that is of immense public health importance because of its high prevalence rate, early onset, chronicity, and functional impairment. The current project seeks to use examine specific patterns of brain activity in response to emotional stimuli, in order to shed light on the neural mechanisms underlying abnormal emotional reactivity in MDD. In doing so, this will aid recent research efforts to identify biological markers associated with MDD that can be used to facilitate effective treatment selection, track treatment progress, and predict recovery.