ArticleAddiction biology2026
Abnormal Brain Structural Covariance Networks of Cortical Thickness in Cocaine Use Disorder.
Article in Addiction biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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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8 authors.
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Abstract
Cocaine use disorder (CUD) is a serious global public health problem, characterized by compulsive drug seeking and impaired cognitive control. Previous studies using voxel-based morphometry (VBM) or surface-based morphometry (SBM) have identified regional alterations in grey matter volume and cortical thickness (CT); purely local morphological analyses are insufficient to capture coordinated patterns of interregional change. In this study, we employed structural covariance networks (SCNs) analysis to investigate abnormalities in the macroscopic topological organization of the brain in individuals with CUD, based on CT measures. A total of 68 patients with CUD and 52 healthy controls (HCs) were included from the OpenNeuro database. The results demonstrated that the CUD group exhibited a significantly reduced global clustering coefficient and a shift in small-world properties, with network topology becoming more closely aligned with a lattice-like configuration. In addition, CUD showed disrupted rich-club connectivity, particularly within core frontoparietal regions. Notably, no significant group differences were observed in network robustness against random failure or targeted attack. Together, these findings indicated an imbalance between network integration and segregation in the structural brain networks of individuals with CUD, providing a novel network-level perspective on the pathophysiology of addiction and suggesting potential utility as a diagnostic neurobiological marker.
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