Functional connectivity of reward and cognitive control networks predicts body mass index but not binge eating disorder in women

Background Binge eating disorder (BED) is associated with obesity as well as behavioral and neurobiological changes in the reward and cognitive control systems of the brain. To better dissociate neural mechanisms of pathological eating behavior, functional connectivity (FC) analyses have shown promise. However, there is currently no replicable signature of BED derived from fMRI. Methods We investigated FC in 61 women with varying symptoms of binge eating. The three groups included 21 women with BED, 20 women with subsyndromal BED (subBED), and 20 controls without binge eating (noBE) matched in body mass index (BMI) and age. To identify neural signatures of BED and BMI, we used seed-based FC fingerprints (nucleus accumbens, NAcc, for reward and dorsolateral prefrontal cortex, dlPFC, for cognitive control) to predict group or BMI based on resting state and task-based (food bidding) FC. Furthermore, we explored spatial patterns of FC to quantify associations with BED and BMI. Results Both seeds of the reward and cognitive control networks robustly predicted BMI (rs = .33 - .46). The dlPFC seed predicted BMI across conditions (resting state: p=.002; task: p=.012) while the NAcc seed only predicted BMI based on task-based FC (p=.007). In contrast, FC failed to classify binge eating groups better than chance. Conclusions FC within reward and cognitive control networks primarily reflect obesity-related changes. Despite pronounced differences in eating behavior, BED could not be reliably dissociated from subBED or noBE using FC fingerprints. These results highlight challenges in identifying BED-specific functional markers.