Bulimia nervosa (BN) is an often-chronic eating disorder associated with high rates of disability and premature death. There is a critical need to identify brain-based factors that perpetuate BN symptoms and that may serve as mechanistic targets for novel treatments. Most studies have focused on binge eating and purging behaviors in BN and have linked these symptoms to inhibitory control deficits and reduced frontostriatal activation. However, individuals with BN typically oscillate between states of problematic under- and over-control? excessive eating and restricted intake/fasting. Neurobiological research to date has failed to account for this oscillation. The goal of this mentored patient-oriented research career development award is to better understand the computational underpinnings of inhibitory control in these two states in BN. Specifically, the proposed study combines functional magnetic resonance imaging (fMRI) with dynamic Bayesian modeling to examine whether eating and fasting abnormally impact how the brains of women with BN prepare for and exert inhibitory control. This study will compare neural responses of 30 women with BN to those of 30 group- matched controls during an inhibitory control paradigm after a 16-h fast and after a standardized meal. This well-controlled design will test the following hypotheses: 1) In BN, frontostriatal signals for the expected need to inhibit, Bayesian prediction error signals, and activation during response inhibition are abnormally blunted in a fed state, and abnormally enhanced in a fasted state (Aim 1); 2) Altered response to the fed state promotes out-of-control eating and purging, whereas altered response to the fasted state perpetuates prolonged restriction between binge/purge episodes (Aim 2). Data from this project will substantiate an explanatory model of BN symptoms, pinpoint which components of the inhibition process are altered in BN, and identify states in which control-focused interventions may be most effective. This work ultimately will inform precisely targeted and context-dependent interventions that can more effectively interrupt the cycle of binge eating, purging, and restriction. The study will also serve as a vehicle for mentorship and hands-on training in concepts and skills critical to the candidate?s next steps. Specifically, within a resource-rich environment, the proposed training will give the candidate new expertise in three domains: 1) repeated-measures neuroimaging methods and associated analyses, 2) neurocomputational modeling and computational psychiatry, and 3) the neurobiology of the full spectrum of disordered eating symptomatology in BN. This project and the completion of training goals will launch the candidate?s independent career in the translational neuroscience of eating disorders and lay groundwork for high-impact studies that combine neuroimaging and sophisticated analytic approaches to improve eating disorder diagnosis and treatment.
Bulimia nervosa (BN) has been linked to deficits in inhibitory control, but it is not known how these deficits explain both the debilitating binge eating and dangerous dietary restriction characteristic of BN. The proposed novel application of computational neuroimaging to the study of inhibitory control will examine fed- and fasted- state-dependent mechanisms that could drive cyclical, bulimic symptoms and interfere with response to treatment. Data from this project will inform a more precise explanatory model of BN symptoms and identify new, state-specific targets for psychosocial and pharmacotherapeutic interventions for this chronic and costly disorder.
