Individual Differences in Resting State Connectivity and Self-Regulation Failure

摘要 尽管人类具有令人印象深刻的自我调节能力，但失败是常见的，人们有时 在各种各样的情况下都很难控制他们的行为。这样的失败牵涉到 许多与死亡和疾病相关的可预防的健康问题，包括肥胖、营养不良、 运动不足，酗酒和上瘾，以及危险的性行为。这项研究的首要目标是 是为了更好地理解个体差异的神经基础，在多大程度上人们对 自律失灵。这项拟议的研究考察了最近由 研究人员认为，这是建立在30年社会心理学研究的基础上的。具体地说，该模型 根据当前的情况，审查自我监管失败的情景和背景因素 关于执行控制和奖励敏感性的大脑机制的神经科学文献。这款车 表明成功的自我调节依赖于额叶区域对皮质下的自上而下的控制 涉及奖赏和情绪的区域以及兴奋的皮质下活动有助于自我调节 失败了。该项目使用最近开发的网络分析应用程序来评估休息状态 连通性(RS-fcMRI)及其与自我调节成败的关系。基于网络的RS-fcMRI允许 为了检查大脑网络的功能耦合，整个大脑的统计一致性模式 在整个开发过程中出现的区域，以允许评估网络完整性的方式(即， 网络中节点之间的连接强度)。当受试者没有执行明确的任务时， 可以识别几个可分离和可重复的大脑网络中的连贯活动。其中之一是 额顶网络--初步研究表明，静息状态下该网络中的活动预示着身体 体重和有氧能力(分别进行研究)。这项研究的指导性假设是个体 额顶神经网络完整性的不同与长期的成功或失败有关 自律。这项研究中的目标自我调节行为是节食，因为它可以服从于 功能成像研究，它可以在行为实验室实验中操纵。三项研究是 建议测试该项目的具体目标，包括评估rs-fcmri和大脑奖励活动 预测(1)在实验室对饮食挑战后的食物消费进行评估时的饮食行为，(2) 自我调节衰竭后的脑功能活动，以及(3)饮食成功的长期结果。 检测额顶叶网络和大脑奖励活动中的静息状态连接性将提供新的 对自我监管成败的个体差异的洞察。 好了！

Summary Although humans have an impressive capacity for self-regulation, failures are common and people sometimes have difficulty controlling their behavior across a wide variety of circumstances. Such failures are implicated in many preventable health problems associated with death and disease, including obesity, poor nutrition, inadequate exercise, alcoholism and addiction, and risky sexual activity. The overarching goal of this research is to better understand the neural basis of individual differences in the extent to which people are susceptible to self-regulatory failure. The proposed research examines a recent model of self-regulatory failure developed by the investigators that that builds on three decades of social psychological research. Specifically, the model examines the situational and contextual factors under which self-regulation fails in light of the current neuroscience literature on brain mechanisms underlying executive control and reward sensitivity. This model indicates that successful self-regulation is dependent on top-down control from frontal regions over subcortical regions involved in reward and emotion and that botom-up subcortical activity contributes to self-regulation failure. This project uses recently developed applications of network analysis to assess resting state connectivity (rs-fcMRI) and its relation to self-regulatory success and failure. Network-based rs-fcMRI allows for the examination of functional coupling of brain networks, patterns of statistical coherence across brain regions that arise throughout development, in a manner that permits assessment of a network's integrity (i.e., strength of connections between nodes in the network). When subjects are not performing an explicit task, coherent activity within several separable and reproducible brain networks can be identified. One of these is the fronto-parietal network-preliminary research shows that activity in this network at rest predicts body weight and aerobic capacity (in separate studies). The guiding hypothesis of this research is that individual differences in the integrity of this fronto-parietal network are associated with long-term success or failure in self-regulation. The target self-regulatory behavior in this research is dieting because it is amenable to functional imaging research and it can be manipulated in behavioral laboratory experiments. Three studies are proposed to test the specific aims of this project, which include assessing rs-fcMRI and brain reward activity to predict (1) eating behavior in laboratory assessments of food consumption following dietary challenges, (2) functional brain activity following self-regulatory depletion, and (3) long-term outcomes in dietary success. Examining resting state connectivity in the fronto-parietal network and brain reward activity will provide novel insights into individual differences in self-regulatory success and failure. !