AUTHOR=Guo Yiqun , Xia Yuxiao , Chen Ke 

TITLE=The body mass index is associated with increased temporal variability of functional connectivity in brain reward system

JOURNAL=Frontiers in Nutrition

VOLUME=Volume 10 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/nutrition/articles/10.3389/fnut.2023.1210726

DOI=10.3389/fnut.2023.1210726

ISSN=2296-861X

ABSTRACT=Reward system has been proved to be contributed to the vulnerability of obesity. Previous fMRI studies have showed abnormal functional connectivity of reward system in obesity. However, most studies were based on static index such as resting-state functional connectivity (FC), ignoring the dynamic changes over time. To investigated the dynamic neural correlates of obesity susceptibility, we used a large, demographically well-characterized sample from the Human Connectome Project (HCP) to determine the relationship of body mass index (BMI) with the temporal variability of FC from integrated multilevel perspectives, i.e., regional, within- and between-network levels. Linear regression analysis was used to investigate the association between BMI and temporal variability of FC, adjusting for covariates of no interest. We found that BMI was positively associated with regional FC variability in reward regions, such as ventral orbitofrontal cortex and visual regions. At intra-network level, BMI was positively related to the variability of FC within limbic network (LN) and default mode network (DMN). At inter-network level, variability of connectivity of LN with DMN, frontoparietal, sensorimotor, and ventral attention networks showed positive correlations with BMI. These findings provided novel evidence for abnormal dynamic functional interaction between reward network and the rest of the brain in obesity, suggesting that a more unstable state and over-frequent interaction of the reward network and other attention and cognitive networks. These findings thus provide novel insight into obesity interventions that need to decrease the dynamic interaction between reward network and other brain networks through behavioral treatment and neural modulation.