ArticleCommunications medicine2026
Machine learning-based identification of abnormal functional connectivity in obesity across different metabolic states.
Article in Communications medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Machine learning-based identification of abnormal functional connectivity in obesity across different metabolic states.Communications medicine · 2026Article
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Authors and funding
8 authors.
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Abstract
backgroundObesity is a major health concern linked to chronic conditions such as diabetes and cardiovascular disease. However, most neurological studies have focused on specific metabolic states, limiting understanding of how brain function changes from fasting to satiety. Furthermore, hypothesis-driven approaches may introduce bias and fail to capture complex neural interactions. This study aimed to identify brain connectivity patterns associated with obesity across different metabolic states using a data-driven approach.
methodsElectroencephalography data were collected from 30 women with obesity and 30 women without obesity over a four-hour period encompassing fasting and post-meal states. All subjects were aged 20 to 65 years. Functional connectivity was calculated from source-localized signals, and a machine learning framework incorporating a feature selection method was applied to identify the most discriminative connectivity features between groups.
resultsHere we show that six connectivity features classify obesity with 95% accuracy across metabolic states. Reduced connectivity are observed within food-reward processing regions in the obese group, with the dorsal anterior cingulate cortex emerging as a central hub. This pattern reflects a persistent alteration in energy prediction and craving regulation that is independent of metabolic state.
conclusionsThese findings demonstrate that disrupted brain connectivity is a fundamental characteristic of obesity. The results highlight the dorsal anterior cingulate cortex as a key region underlying maladaptive reward processing and suggest that targeting this area through neuromodulation therapies may offer a promising intervention for obesity treatment.
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