Increased modularity of the resting‐state network in children with nonsyndromic cleft lip and palate after speech rehabilitation

Brain and Behavior

Renji Chen¹  Wenjing Zhang¹  Yun Peng²  Hua Cheng²  Bo Rao³ 

[1] Department of Oral and Maxillofacial Plastic and Trauma Surgery Center of Cleft Lip and Palate Treatment Beijing Stomatological Hospital Beijing China;Department of Radiology Beijing Children's Hospital National Center for Children's Health Capital Medical University Beijing China;Departments of Radiology Zhongnan Hospital of Wuhan University Wuhan China;

关键词: graph theory;    modularity;    nonsyndromic cleft lip and palate;    resting‐state functional MRI;    speech therapy;   

DOI  :  10.1002/brb3.2094

来源: DOAJ

【 摘 要 】

Abstract Introduction Speech therapy is the primary management followed the physical management through surgery for children with nonsyndromic cleft lip and palate (NSCLP). However, the topological pattern of the resting‐state network after rehabilitation remains poorly understood. We aimed to explore the functional topological pattern of children with NSCLP after speech rehabilitation compared with healthy controls. Methods We examined 28 children with NSCLP after speech rehabilitation (age = 10.0 ± 2.3 years) and 28 healthy controls for resting‐state functional MRI. We calculated functional connections and the degree strength, betweenness centrality, network clustering coefficient (Cp), characteristic path length (Lp), global network efficiency (Eg), local network efficiency (Eloc), modularity index (Q), module number, and participation coefficient for the between‐group differences using two‐sample t tests (corrected p < .05). Additionally, we performed a correlation analysis between the Chinese language clear degree scale (CLCDS) scores and topological properties in children with NSCLP. Results We detected significant between‐group differences in the areas under the curve (AUCs) of degree strength and betweenness centrality in language‐related brain regions. There were no significant between‐group differences in module number, participation coefficient, Cp, Lp, Eg, or Eloc. However, the Q (density: 0.05–0.30) and QAUC (t = 2.46, p = .02) showed significant between‐group differences. Additionally, there was no significant correlation between topological properties of statistical between‐group differences and CLCDS scores. Conclusions Although nodal metric differences existed in the language‐related brain regions, the children with NSCLP after speech rehabilitation had similar global network properties, module numbers, and participation coefficient, but increased modularity. Our results suggested that children with NSCLP achieved speech rehabilitation through function specialization in the language‐related brain regions. The resting‐state topology pattern could be of substantive neurobiological importance and potential imaging biomarkers for speech rehabilitation.

【 授权许可】

Unknown