Neural Correlates of Error Monitoring in Anxiety and Depression

描述（由申请人提供）：焦虑症（GAD）是一种普遍的慢性疾病，影响4%至7%的人口。广泛性焦虑症经常与重度抑郁症（MDD）合并症，终生诊断在40%到75%之间同时发生。本研究旨在阐明广泛性焦虑症与错误处理的关系，以及抑郁症状如何利用错误相关负性（error-related negative， ERN）影响焦虑相关过程，错误反应后事件相关脑电位（event-related brain potential， ERP）的偏转。许多研究报告称，焦虑和忧虑人群的ern增加。然而，到目前为止，还没有研究在广泛性焦虑症的临床样本中检查ERN，也没有对共病抑郁症对错误相关脑活动的影响进行系统评估。在目前的研究中，我们的工作模型是，尽管广泛性焦虑症将与ERN增加有关，但抑郁症特有的症状将与ERN减少有关。我们正在测试一种新的假设，即重度抑郁症的存在可能掩盖甚至改变广泛性焦虑症和ERN增强之间的关系。我们还将探索这种假设关系的机制，从而建立ERN作为一种神经测量，对消极和积极情感之间的相互作用敏感。与美国国家心理健康研究所神经科学和基础行为科学部的使命一致，本研究的目的是利用神经活动的两种直接测量方法，erp和脑电图（EEG）的频谱分析，来检查广泛性焦虑症和共病广泛性焦虑症/重度抑郁症中错误监测的神经相关性。拟议的研究有四个具体目的：(a)与对照组相比，检查广泛性焦虑症患者错误监测的神经相关性；(b)检查共病重度抑郁症患者错误监测的神经相关性；(c)探讨ERN与每种紊乱的特定症状之间的关系；(d)使用与错误相关的大脑活动的频谱分析来检验这些假设。150名成人（50名广泛性焦虑症患者，50名共病性广泛性焦虑症/重度抑郁症患者，50名对照组）将被招募。在hajak博士的指导下，在一个旨在诱发错误的实验室任务中，将记录头皮上记录的erp和振荡脑电图活动。我们将推导响应锁定的erp，并使用复小波分解对脑电图信号进行频谱分析。在此之后，源定位程序将用于识别潜在的神经发生器。目前的培训建议将允许申请人整合来自具有ERN和焦虑专业知识的共同导师（Hajcak博士）、焦虑和抑郁共病模型（Klein博士）的培训，以及来自具有时频分析专业知识的顾问（Keil博士）和ERP/EEG信号源定位（Pizzagalli博士）的培训。

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).