Resting State and Task-Evoked Neural Bases of Rumination and Affective Dysfunction

 描述（由申请人提供）：[抑郁症是一种常见的疾病，具有重大的公共卫生影响。]最近的研究已经将抑郁症与功能异常联系在默认模式网络（DMN）中，这是一个通常在休息时活跃，在认知任务中失活的区域网络。[抑郁症与静息态功能磁共振成像中DMN连接增加有关]，当个体看到负面图像时，相对无法抑制DMN。此外，抑郁的人表现出增强和延长杏仁核反应的负面图像。[This导致了这样一种理论，即DMN异常可能会干扰抑郁症患者大脑区域调节杏仁核的募集。[抑郁症患者的这些神经标记也与沉思反刍有关，这是一种涉及重复消极思想的适应不良应对方式。这项工作提出了测试这个模型，使用跨模态比较的fMRI数据在个人在休息状态扫描，而参与者正在查看负面图像。将检验两个主要假设：1）静息态DMN [功能]将预测在观看负面图像期间自上而下的情绪调节降低，以及2）静息态DMN [功能]增加，以及在观看负面图像期间自上而下的情绪调节降低，将通过增加的特质[沉思]来预测。在负性图像观看期间自上而下的情绪调节的评估将是多模态的，并且将集中在图像偏移后的6- 12秒的时间段，捕获从负性图像的“恢复”，同时控制响应于图像的最初6秒的活动（“反应性”）。测量指标包括杏仁核活动、杏仁核-前额连接和皱眉肌的肌电图，皱眉肌是一种可靠的负面情绪体验指标。[In此外，将使用多变量模式分析（MVPA）对阴性与中性图像进行分类，作为神经反应的替代测量。DMN [功能]将以两种方式进行评估。首先，使用基于相关性的方法计算DMN的两个主要节点（内侧前额叶皮层和后扣带皮层）之间的功能连接。第二，DMN在认知控制网络中的优势度将按照其他研究人员以前使用的方法计算。为了评估静息态DMN函数如何预测自上而下的情绪调节，这些DMN指标将回归到所有上述情绪调节指标上。为了评估这些指标如何对应于特质育雏，将使用标准化指标（反刍反应量表; RRS）评估育雏[并回归到上述结果指标]。这项工作将阐明DMN活动的关系，情绪调节和沉思的神经相关性与情感障碍的风险和治疗的影响。

 DESCRIPTION (provided by applicant): [Depression is a common disorder with a major public health impact.] Recent research has linked [depression with abnormal function] in the default-mode network (DMN), a network of regions that is typically active at rest, and deactivates during cognitive tasks. [Depression has been linked with increased DMN connectivity] during resting-state fMRI, and a relative failure to suppress DMN when individuals view negative images. In addition, depressed individuals demonstrate enhanced and prolonged amygdala responses to negative images. [This has led to the theory that DMN abnormalities might interfere with recruitment of brain regions to regulate amygdala in depressed individuals.] [These neural markers in depressed individuals have also been related to brooding rumination, a type of maladaptive coping involving repetitive negative thoughts.] This work proposes to test this model using cross-modal comparison of fMRI data in individuals during a resting-state scan and while participants are viewing negative images. Two main hypotheses will be tested: 1) resting-state DMN [function] will predict decreased top-down regulation of emotion during viewing of negative images, and 2) increased resting-state DMN [function], and decreased top-down emotion regulation during negative-image-viewing, will be predicted by increased trait [brooding]. Assessment of top-down emotion regulation during negative-image-viewing will be multimodal and will focus on the time period 6-12s after image offset, capturing "recovery" from the negative image, while controlling for initial 6 s of activity in response to the image ("reactivity"). Measures will include amygdala activity, amygdala-prefrontal connectivity, and electromyography of the corrugator supercilii, a muscle that is a reliable indicator of the experience of negative emotion. [In addition, multivariate pattern analysis (MVPA) will be used to classify negative vs. neutral images as an alternative measure of neural responses.] DMN [function] will be assessed in two ways. First, functional connectivity between two major nodes of the DMN (medial prefrontal cortex and posterior cingulate cortex) will be calculated using correlation-based methods. Second, [a metric of DMN dominance over a cognitive control network will be calculated following methods used previously by other researchers. In order to assess how resting-state DMN function predicts top-down emotion regulation, these DMN metrics will be regressed onto all of the above metrics of emotion regulation. In order to assess how these measures correspond to trait brooding, brooding will be assessed using a standardized measure (the Ruminative Responses Scale; RRS) [and also regressed onto the outcome measures above]. This work will elucidate the relationship of DMN activity, [neural correlates of] emotion regulation and [brooding] with implications for risk and treatment of affective disorders.