Wanqing Liu, Dan Ma, Chuanlong Cao, Sai Liu, XinMao Ma, Fenglin Jia, Pei Li, Hui Zhang, Yimin Hua, Yi Liao, Haibo Qu
Developmental stuttering is a neurodevelopmental speech disorder characterized by speech disfluency and variable persistence into adolescence. While white matter and functional connectivity abnormalities have been widely reported, the topological organization of gray matter (GM) networks in affected children remains unclear. This study investigated GM morphological network alterations in children with persistent developmental stuttering (CWS) and examined their relationships with stuttering severity. Thirty-three CWS and thirty age- and sex-matched healthy controls underwent T1-weighted MRI. Individual GM morphological networks were constructed using Kullback-Leibler divergence of voxel-based morphometry data across 90 brain regions. Graph-theoretical analyses quantified global and local topological properties, and network-based statistics (NBS) were used to identify alterations in morphological connectivity. Both groups exhibited small-world topology; however, CWS showed significantly higher clustering coefficient(Cp), local efficiency (Eloc), and modularity (Q) (P < 0.05), indicating a hyper-segregated GM organization. NBS revealed reduced morphological connectivity within a subnetwork encompassing the default mode, sensorimotor, basal ganglia-thalamic, and visual regions. Greater network segregation (Cp, Eloc, Q) was positively correlated with stuttering severity, whereas reduced subnetwork connectivity was negatively correlated with stuttering severity (FDR-corrected P < 0.05). These findings suggest that children with persistent stuttering exhibit excessive local specialization and decreased interregional integration, reflecting a network-level imbalance that may underlie the persistence and severity of stuttering. Altered GM network topology may represent a potential neurostructural biomarker for early identification and targeted intervention.