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.
Self-regulation failures are implicated in many preventable health problems associated with death and disease. This research tests a model that integrates research in social psychology and cognitive neuroscience to characterize the neural mechanisms underlying self-regulation and its failure. The model is tested using network analyses of resting state functional connectivity and functional magnetic resonance imaging of reward sensitivity to predict self-regulatory success and failure. Ultimately, this may inform behavioral interventions and psychological treatments for many health-relevant behaviors, such as obesity, risky sexual behavior, and addiction.
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