Dynamic functional network connectivity alterations in obesity

AIMS: Obesity involves both metabolic and neural dysfunction, yet the temporal dynamics of brain connectivity remain unclear. This study applied dynamic functional network connectivity (dFNC) analysis to reveal time-varying brain network patterns in obesity. MATERIALS AND METHODS: Eighty-three individuals with obesity and 40 normal-weight controls underwent resting-state functional magnetic resonance imaging. After preprocessing and group independent component analysis, dFNC was estimated using a sliding-window approach and clustered into distinct connectivity states. Temporal metrics (fraction time, dwell time and transitions) were compared between groups, and correlations with clinical characteristics were analysed. RESULTS: Three recurring connectivity states were identified. Compared with controls, individuals with obesity showed enhanced coupling among the default mode, attention and visual networks, with reduced network flexibility-manifested as prolonged dwell time and fewer transitions. Uncontrolled eating correlated positively with time spent in maladaptive states, whereas cognitive restraint was negatively associated with participation in integrative states. CONCLUSIONS: Obesity is characterised by state-dependent reorganisation of large-scale brain networks and diminished temporal flexibility. These dynamic connectivity alterations are closely related to eating behaviour and metabolic characteristics, suggesting that dFNC provides a valuable neuroimaging framework for understanding impaired self-regulation in obesity and for guiding future intervention studies.