Global integration of the hot-state brain network of appetite predicts short term weight loss in older adult.

摘要: Obesity is a public health crisis in North America. While lifestyle interventions for weight loss (WL) remain popular, the rate of success highly variable. Clearly, self-regulation eating behavior challenge and patterns activity across brain may be an important determinant success. The current study prospectively examined whether integration Hot-State Brain Network Appetite (HBN-A) predicts WL after 6-months treatment older adults. Our metric network was global efficiency (GE). present work sub-study (n = 56) ongoing randomized clinical trial involving WL. Imaging involved baseline food-cue visualization functional MRI (fMRI) scan following overnight fast. Using graph theory to build networks, we demonstrated that regions HBN-A (insula, anterior cingulate cortex (ACC), superior temporal pole (STP), amygdala parahippocampal gyrus) were integrated as evidenced by results principal component analysis (PCA). After accounting known correlates (baseline weight, age, sex, self-regulatory efficacy) condition, which together contributed 36.9% variance WL, greater GE associated with additional 19% variance. ACC primary driver this effect, 14.5% when entered stepwise regression covariates, p 0.0001. comprised limbic processing emotions visceral sensations key translating such into behavioral consequences. improved these enhance awareness body emotional states leading more successful This first among adults demonstrate that, fast, during food task predictive