The Topological Properties Of Cerebellum Functional And Morphology Network In Chronic Insomnia Patients:A Graph Theoretical Analysis

ObjectiveThe resting state functional magnetic resonance and high-resolution structural magnetic resonance were used to construct the cerebellar functional network and morphological network based on the graph theory of complex brain network analysis.Then,to explore the possible topological attribute changes in the cerebellar functional network and morphological network of patients with chronic insomnia(CI)patients,and further explore the potential correlation between the abnormal topological attribute and clinical sleep and cognitive function,so as to provide clinical evidence of neurological function and structural imaging.Cognitive function was assessed using cognitive scales and tests in all subj ects.Materials and MethodsIn this study,102 patients with CI were recruited and 101 healthy control(HC)subjects matched with age,sex and education level of CI group were selected.CI patients sleep condition was evaluated by sleep scale and sleep behavior was evaluated by polysomnography.Image acquisition uses 3.0T MRI scanner for resting-state functional MRI scanning and high-resolution structural MRI scanning.The brain function analysis software package was used to preprocess the data,and the cerebellar function and structure network matrix was constructed,and then the topological attribute index was calculated based on the complex brain network analysis of graph theory,including:(1)global topology attribute indicators:clustering coefficient,characteristic path length,normalized clustering coefficient,normalized characteristic path length;(2)local topology attribute indicators:node degree,nodal betweenness centrality.Appropriate statistical analysis methods were selected to compare the differences between the two groups of global and local topological attribute indicators,using gender,age and education level as covariates,and further analyzed with clinical sleep and cognitive function indicators.Results1.Cerebellar functional network topology attribute results:(1)global topology attribute indicators:normalized clustering coefficient of cerebellar functional network in CI group was higher than that in HC groups 0.008);(2)local topology attribute indicators:nodal betweenness centrality of Crus Ⅱ vermis region in the CI group was higher than that in the HC group(p<0.001).2.Cerebellar topological network topology attribute results:(1)global topology attribute indicators:normalized clustering coefficient of cerebellar morphological network in CI group was lower than that in HC group(p=0.010);(2)local topology attribute indicators:nodal degree of Lobule Ⅶb vermis region in the CI group was higher than that in the HC group(p=0.002),nodal degree of Lobule Ⅷa right region in the CI group was lower than that in the HC group(p<0.001).3.After multiple comparison correction,there was no obvious correlation between the different network topology attribute indicators and the clinical sleep and cognitive function scales(Corrected p>0.05).ConclusionThe topological properties of cerebellar functional network and morphological network in CI group were changed compared with those in HC group,indicating that long-term sleep disorder was an important factor leading to cerebellar functional and structural damage.The extensive information processing and transmission enhancement of the cerebellar functional network suggests hyperarousal in the CI nervous system,and there may be some compensatory mechanism to alleviate impairment of sleep and cognitive function.Abnormal changes in the morphological network of the cerebellum may be the structural basis of cognitive dysfunction and sleep disturbances.In summary,the findings of this study may provide new insights into the pathophysiology of CI and contribute to the development of new biomarkers for clinical diagnosis and treatment.