Neurobehavioral metrics for the assessment and treatment of depression

描述（由申请人提供）：为了推进抑郁症的多维评估和治疗，该提案的广泛创新有三个方面。首先，我们将使用功能性磁共振成像（fMRI），和一个大样本量的受试者内设计，以确定抑郁症的情绪，社会功能和奖励反应的神经行为措施。其次，我们将评估认知行为治疗后这些指标的变化，并评估这些指标预测特定领域治疗结果的实用性。第三，我们将使用这些措施来开发基于情绪衍生的大脑状态的fMRI引导的神经反馈，并测试神经反馈引起情绪改善的能力。 该项目的首要目标是确定定量的神经行为内表型，可用作评估和治疗重性抑郁症的多维指标。伴随的假设是，重度抑郁症中的快感缺失、社交障碍和消极情绪可能分别映射到奖励、社会功能和基于情感的任务中诱发的神经活动。我们相信，这些措施可以用来定制个人的治疗方案，并开发新的个性化的神经行为治疗抑郁症。具体目标如下：目标1：识别和完善重度抑郁症患者的快感缺乏、社会功能和消极情绪的神经行为测量。我们将使用三种不同的任务和功能磁共振成像来量化神经行为反应的情绪刺激，奖励，和社会功能，在一个受试者内的设计与抑郁症的个人。我们将检验这一假设，即重性抑郁症的各个方面可以在这三个领域的定量神经行为异常谱上进行测量。 目的2：识别认知行为疗法治疗反应的特定领域变化和预测因素。我们将在12周的精神支持认知行为治疗（CBASP）前后扫描重度抑郁症患者，以确定a）治疗反应的特定领域神经行为预测因子和B）CBASP引起的症状变化的神经行为伴随物。本目标将检验以下假设：目标1中确定的基于奖赏、社会功能和情绪的神经反应将为特定领域变化提供差异预测效用。 目的3：评估受试者调节由情绪状态产生的神经反馈界面的能力，并评估神经反馈后的情绪变化。受试者将在积极或消极情绪激发期间接受源自神经反应的神经反馈。这一目标将检验以下假设：a）个体可以学会分别调节与积极和消极情绪相关的分布式大脑模式，以及B）通过神经反馈，抑郁个体将实现情绪改善。

DESCRIPTION (provided by applicant): To advance the multi-dimensional assessment and treatment of major depression, the broad innovations of this proposal are threefold. First, we will use functional magnetic resonance imaging (fMRI), and a within-subjects design with large sample sizes to identify neurobehavioral measures of mood, social functioning, and reward response in depression. Second, we will evaluate changes in these measures following cognitive behavioral therapy and assess the utility of these measures for predicting domain-specific treatment outcomes. Third, we will use these measures to develop fMRI-guided neurofeedback based on mood-derived brain states and test the capacity of the neurofeedback to elicit mood improvement. The overarching goal of this project is to identify quantitative neurobehavioral endophenotypes that may be used as multi-dimensional metrics in the assessment and treatment of major depressive disorder. The accompanying hypothesis is that anhedonia, social impairment, and negative mood in major depression may be mapped onto neural activity evoked during reward-, social functioning-, and emotion-based tasks, respectively. We believe that these measures may be used both to tailor individuals' treatment regimens and to develop novel personalized neurobehavioral therapies for depression. The specific aims are below: Aim 1: Identify and refine neurobehavioral measures of anhedonia, social functioning, and negative mood in individuals with major depressive disorder. We will use three distinct tasks and fMRI to quantify neurobehavioral responses to emotional stimuli, reward, and social functioning, in a within-subjects design in individuals with depression. We will test the hypothesis that aspects of major depression may be measured on a quantitative neurobehavioral spectrum of anomalies in these three domains. Aim 2: Identify domain-specific changes and predictors of treatment response to cognitive behavioral therapy. We will scan individuals with major depressive disorder before and after 12 weeks of empirically-supported cognitive behavioral therapy (CBASP) to identify a) domain-specific neurobehavioral predictors of treatment response and b) neurobehavioral concomitants of symptom changes elicited with CBASP. This Aim will test the hypothesis that the reward-, social-functioning, and mood- based neural responses identified in Aim 1 will serve differential predictive utility for domain-specific changes. Aim 3: Assess subjects' ability to modulate a neurofeedback interface developed from mood states and evaluate mood changes following neurofeedback. Subjects will receive neurofeedback derived from neural responses during positive or negative mood provocation. This aim will test the hypotheses that a) individuals can learn to modulate distributed brain patterns associated with positive and negative emotion, respectively, and that b) through neurofeedback, depressed individuals will achieve mood improvements.