Neural Network Dysregulation in Female Abdominal Obesity: Distinct Functional Connectivity in Different Appetite Subtypes
Authors' conclusion
Distinct brain network patterns characterize appetite subtypes in AO. SA showed more pronounced FC reductions in networks previously linked to self-regulation and visual processing, which may contribute to appetite dysregulation based on correlations with obesity indicators. In contrast, MA exhibited increased DMN-FPN_L FNC, potentially reflecting adaptive internetwork interactions.
Study context
- Population
- Women with abdominal obesity (AO) and healthy controls
- Participants
- 30 / 30 / 30
- Exposure
- Women with abdominal obesity, moderate appetite (MA) vs strong appetite (SA) subtypes, vs healthy controls (HCs)
- MAn = 30
- SAn = 30
- HCsn = 30reference
- Outcome
- Resting-state functional connectivity (FC) and functional network connectivity (FNC)
Methodological detailsresting-state fMRI, independent component analysis
- Resting-state fMRI
- Independent component analysis
Main finding
As reported in the abstract
- Both MA and SA vs HCs: reduced functional connectivity (FC) in default mode network (DMN) and visual network (VN) (p < 0.05, FDR-corrected)
- SA additionally: decreased FC in frontoparietal network (FPN) and lower angular gyrus FC than MA (p < 0.05, FDR-corrected)
- MA: increased DMN-left FPN (FPN_L) functional network connectivity (FNC) (p < 0.001)
- FDR-corrected
Observational data: associations, not effects.
Further findings
Correlations of FC/FNC with obesity-related indicators
- SA: negative correlations between FC and BMI/appetite visual analog scale (VAS) scores in FPN and with body weight/BMI/appetite VAS in VN (p < 0.05)
- HCs: DMN-FPN_L FNC positively correlated with BMI; pattern not observed in MA
Original publication
Neural Network Dysregulation in Female Abdominal Obesity: Distinct Functional Connectivity in Different Appetite Subtypes. Obesity (Silver Spring). Published 23 October 2025. doi:10.
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