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Aberrant single-subject morphological cerebellar connectome in chronic insomnia

BACKGROUND: To systematically investigate the topological organisation of morphological networks of the cerebellum using structural MRI and examine their clinical relevance in chronic insomnia (CI). METHODS: One hundred and one patients with CI and 102 healthy controls (HCs) were recruited in this s...

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Detalles Bibliográficos
Autores principales: Ma, Yuqin, Fu, Shishun, Ye, Xi, Yang, Yuping, Yin, Yi, Xu, Guang, Liu, Mengchen, Jiang, Guihua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10458694/
https://www.ncbi.nlm.nih.gov/pubmed/37603949
http://dx.doi.org/10.1016/j.nicl.2023.103492
Descripción
Sumario:BACKGROUND: To systematically investigate the topological organisation of morphological networks of the cerebellum using structural MRI and examine their clinical relevance in chronic insomnia (CI). METHODS: One hundred and one patients with CI and 102 healthy controls (HCs) were recruited in this study. Individual morphological networks of the cerebellum were constructed based on regional grey matter volume, and topologically characterised using weighted graph theory-based network approaches. Between-group comparisons were performed using permutation tests, and Spearman’s correlation was used to examine the relationships between topological alterations and clinical variables. RESULTS: Compared with HCs, patients with CI exhibited a lower normalised clustering coefficient. Locally, CI patients exhibited lower nodal efficiency in the cerebellar lobule VIIb and vermis regions, but higher nodal efficiency in the right cerebellar lobule VIIIa regions. No correlations were observed between network alterations and clinical variables. CONCLUSIONS: Individual morphological network analysis provides a new strategy for investigating cerebellar morphometric changes in CI, and our findings may have important implications in establishing diagnostic and categorical biomarkers.