Neural Correlates of Error Monitoring in Anxiety, Depression, and Comorbid Anxiet

描述（由申请人提供）：焦虑症（GAD）是一种普遍存在的慢性疾病，影响4%至7%的人口。广泛性焦虑症经常与重度抑郁症（MDD）共病，其终生诊断共发生的时间在40%至75%之间。目前的建议旨在阐明GAD如何与错误处理，以及抑郁症状如何影响焦虑相关的过程中使用的错误相关的负性（ERN），偏转事件相关的脑电位（ERP）后，一个错误的反应。许多研究报告说，焦虑和担心的人群中ERN增加。然而，迄今为止还没有研究在广泛性焦虑症的临床样本中检查ERN，也没有系统地评估共病抑郁症对错误相关脑活动的影响。在本研究中，我们的工作模型是，虽然广泛性焦虑症将与ERN增加，抑郁症特有的症状将与ERN减少。我们正在测试一个新的假设，即MDD的存在可能掩盖，甚至改变，GAD和增强的ERN之间的关系。我们还将探讨这种假设关系的机制，从而建立ERN作为一种神经措施，是敏感的消极和积极的影响之间的相互作用。与美国国家精神卫生研究所神经科学和基础行为科学部的使命一致，本研究的目的是使用两种直接的神经活动测量方法，ERPs和脑电图（EEG）的频谱分析来检查GAD和共病GAD/MDD中错误监测的神经相关性。拟议的研究有四个具体的目标：（a）检查与对照组相比，GAD个体的错误监测的神经相关性;（B）检查与MDD共病个体的错误监测的神经相关性;（c）探索ERN和每种疾病的特定症状之间的关系;（d）使用错误相关脑活动的频谱分析来检查这些假设。将招募150名成人（50名GAD、50名GAD/MDD共病患者和50名对照）。在Hajcak博士的指导下，将在旨在引起错误的实验室任务期间记录头皮记录的ERP和振荡EEG活动。我们将得到响应锁定的ERP，和复杂的小波分解将被用来执行EEG信号的频谱分析。在此之后，源定位程序将用于识别潜在的神经发生器。目前的培训计划将允许申请人整合来自具有ERN和焦虑（Hajcak博士）专业知识的共同导师的培训，以及焦虑和抑郁之间的共病模型（Klein博士），以及来自具有时频分析（Keil博士）专业知识的顾问的培训，以及ERP/EEG信号的源定位（Pizzagalli博士）。 公共卫生相关性：广泛性焦虑症（GAD）是一种普遍存在的慢性疾病，但其病理生理学研究相对不足。对抑郁症的研究进展可能会因与重度抑郁症（MDD）的高共病率而复杂化。目前的建议旨在利用神经活动的多种措施，以解开焦虑和抑郁对错误监控的复杂影响，特别是关注抑郁如何影响焦虑相关的神经过程。识别特定的神经反应错误的影响可能支持这两种疾病的临床概念化，以及解释从一种疾病到另一种疾病的过渡。此外，本研究的结果可能对未来的纵向研究特别有用，这些纵向研究旨在探索GAD和MDD的病程和共病。

DESCRIPTION (provided by applicant): Anxiety Disorder (GAD) is a pervasive and often chronic disorder affecting between 4% and 7% of the population. GAD is frequently comorbid with Major Depressive Disorder (MDD), with which lifetime diagnoses co-occur between 40% and 75% of the time. The present proposal aims to shed light on how GAD relates to error processing, as well as how depressive symptoms impact anxiety-related processes using the error-related negativity (ERN), a deflection in the event-related brain potential (ERP) subsequent to an erroneous response. A number of studies have reported increased ERNs in anxious and worried populations. However, no studies to date have examined the ERN in a clinical sample of GAD, nor has the influence of comorbid depression on error-related brain activity been systematically evaluated. In the present study, our working model is that although GAD will be related to an increased ERN, symptoms specific to depression will relate to a decreased ERN. We are testing the novel hypothesis that the presence of MDD may mask, or even alter, the relationship between GAD and an enhanced ERN. We will also explore mechanisms of this hypothesized relationship, thereby establishing the ERN as a neural measure that is sensitive to the interaction between Negative and Positive Affect. Consistent with the mission of the Division of Neuroscience and Basic Behavioral Science at the National Institute of Mental Health, the goal of this study is to examine neural correlates of error-monitoring in GAD and comorbid GAD/MDD using two direct measures of neural activity, ERPs and spectral analysis of the electroencephalogram (EEG). The proposed study has four specific aims: (a) to examine neural correlates of error-monitoring in individuals with GAD compared to controls; (b) to examine neural correlates of error-monitoring in individuals with comorbid MDD; (c) to explore relationships between the ERN and specific symptoms of each disorder; and (d) to examine these hypotheses using spectral analyses of error-related brain activity. One hundred and fifty adults (50 GAD, 50 comorbid GAD/MDD, and 50 control) will be recruited. Under the guidance of Dr. Hajcak, scalp-recorded ERPs and oscillatory EEG activity will be recorded during a laboratory task designed to elicit errors. We will derive response-locked ERPs, and complex wavelet decomposition will be used to perform spectral analysis of the EEG signal. Following this, source localization procedures will be used to identify potential neural generators. The current training proposal will allow the applicant to integrate training from co-mentors with expertise in ERN and anxiety (Dr. Hajcak), and models of comorbidity between anxiety and depression (Dr. Klein), as well as training from consultants with expertise in time-frequency analyses (Dr. Keil), and source localization of ERP/EEG signals (Dr. Pizzagalli). PUBLIC HEALTH RELEVANCE: Generalized Anxiety Disorder (GAD) is a pervasive and often chronic disorder, but its pathophysiology is relatively understudied. Advances in research on the disorder may be complicated by high rates of comorbidity with Major Depressive Disorder (MDD). The current proposal seeks to utilize multiple measures of neural activity in order to unravel the complex influences of anxiety and depression on error-monitoring, particularly focusing on how depression might impact anxiety-related neural processes. Identification of symptom-specific influences on neural response to errors may support clinical conceptualization of the two disorders, as well as explain transitions from one disorder to another. Additionally, the results of the present proposal may be particularly useful for future longitudinal studies seeking to explore the course and comorbidity of GAD and MDD.