ArticleCerebral cortex (New York, N.Y. : 1991)2025
Regional, but not brain-wide, graph theoretic measures are robustly and reproducibly linked to general cognitive ability.
Article in Cerebral cortex (New York, N.Y. : 1991), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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2 citing papers in PubMed.
- Resting-state brain function and its modulation by intranasal oxytocin in antisocial personality disorder with and without psychopathy.Scientific reports · 2026Article
- An EEG-network-metric based approach to real-time trust inference in human-autonomy teaming.Frontiers in neuroergonomics · 2025Article
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15 authors.
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Abstract
General cognitive ability (GCA), also called "general intelligence," is thought to depend on network properties of the brain, which can be quantified through graph theoretic measures such as small worldness and module degree. An extensive set of studies examined links between GCA and graphical properties of resting state connectomes. However, these studies often involved small samples, applied just a few graph theory measures in each study, and yielded inconsistent results, making it challenging to identify the architectural underpinnings of GCA. Here, we address these limitations by systematically investigating univariate and multivariate relationships between GCA and 17 whole-brain and node-level graph theory measures in individuals from the Adolescent Brain Cognitive Development Study (n = 5937). We demonstrate that whole-brain graph theory measures, including small worldness and global efficiency, fail to exhibit meaningful relationships with GCA. In contrast, multiple node-level graphical measures, especially module degree (within-network connectivity), exhibit strong associations with GCA. We establish the robustness of these results by replicating them in a second large sample, the Human Connectome Project (n = 847), and across a variety of modeling choices. This study provides the most comprehensive and definitive account to date of complex interrelationships between GCA and graphical properties of the brain's intrinsic functional architecture.
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