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Life sciences · Journal article
Behavioral and Brain Functions · September 9, 2026
Encouraging direction, but not yet definitive.
This cross-sectional analysis of resting-state fMRI data finds that higher BMI is associated with poorer working memory performance and reduced efficiency of synergistic information processing within brain networks. The associations are modest in magnitude (β ≈ −0.13 to −0.15) and mechanistic, demonstrating correlation rather than causation; replication and longitudinal or intervention studies are needed to establish clinical relevance.
Cross-sectional observational analysis. Participants from the Human Connectome Project; eligibility criteria and demographic composition not specified in abstract..
Higher BMI was associated with poorer WM performance (β = −0.149, 95% CI [−0.256, −0.041]) Higher BMI associated with reduced efficiency of synergistic information processing (β = −0.134, 95% CI [−0.241, −0.026]) Reduced synergistic connectivity between anterior insula and dorsomedial prefrontal cortex was associated with weaker negative BMI–WM relationship (p = 0.032, Cohen's d = 0.308)
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Clinicians should view these findings as exploratory evidence linking obesity to cognitive function through a network-level mechanistic pathway. The modest effect sizes and correlational design do not yet support changes to clinical practice; this work provides a framework for future investigation rather than actionable guidance.
A well-designed cross-sectional analysis of large-scale resting-state fMRI data using an information-theoretic framework reports associations between BMI, synergistic brain connectivity, and working memory performance with modest effect sizes; the findings are mechanistic and need prospective or intervention validation.
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Clinicians should view these findings as exploratory evidence linking obesity to cognitive function through a network-level mechanistic pathway. The modest effect sizes and correlational design do not yet support changes to clinical practice; this work provides a framework for future investigation rather than actionable guidance.
Graded across the dimensions that decide whether you should act, each from what the source actually supports. There is no single score, and where a dimension was not assessed it says so.
Abstract Background Obesity has been increasingly linked to differences in working memory (WM), yet the neurophysiological mechanisms linking metabolic state to cognitive function remain unclear. Here, we investigated whether alterations in cortical information transmission are associated with obesity-related differences in working memory. Methods Using resting-state fMRI data from the Human Connectome Project, we applied an information-theoretic framework to quantify synergistic and redundant connectivity among key brain regions supporting working memory. We examined whether network-level and edge-level connectivity features were associated with BMI and working memory performance and further assessed their moderating relationships with the BMI–WM association, together with exploratory indirect-effect analyses. Results Higher BMI was associated with poorer WM performance (β = − 0.149, 95% CI [− 0.256, − 0.041]) and reduced efficiency of synergistic information processing within large-scale brain networks (β = − 0.134, 95% CI [− 0.241, − 0.026]). Reduced synergistic connectivity between the anterior insula and dorsomedial prefrontal cortex ( p = 0.032, Cohen's d = 0.308) was associated with a weaker negative relationship between BMI and working memory. Different connectivity measures also revealed different patterns of association with BMI and WM performance. Conclusions These findings suggest that BMI is associated with working memory through different patterns of network-level information processing, including reduced efficiency of synergistic information integration and connectivity patterns that influence the relationship between BMI and WM. Together, our results highlight synergistic information processing as a potential marker of network-level information organization and provide a framework for investigating links between metabolic status and cognitive function.
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