Objective:To investigate the dynamic functional network connectivity(dFNC)chan-ges of the triple network model(central executive network,salience network,and default mode net-work)in patients with alcohol dependence(AD)in the resting state.Methods:First,resting-state fMRI data of 15 alcohol-dependent patients and 15 healthy controls(normal control group)were collected from February 2020 to March 2021.Secondly,independent component analysis was performed on the preprocessed fMRI data to obtain brain network components,and dynamic functional connectivity ma-trices of the brain network were generated by sliding window method.Then,k-means clustering algo-rithm was applied to all dFNC matrices to determine the brain network connection pattern and obtain the temporal properties of the subject's brain network.Finally,Spearman correlation analysis was used to evaluate the relationship between abnormal time properties(fractional time,mean dwell time,num-ber of transition)and alcohol dependence scale(ADS)scores.Results:Finally,15 HCs and 12 AD pa-tients were included in this study,and four recurring functional connectivity states were obtained by cluster analysis.Compared with the control group,the AD group spent longer time in the weak connec-tivity state,but less time in the strong connectivity state between the central executive network and the salience network(all P＜0.05).The two-sample t-test results showed that the functional connec-tivity between IC38 and IC49 within the central control network of AD patients was significantly en-hanced(P＜0.05,FDR corrected).Conclusion:The functional connectivity of the central executive net-work was altered in AD patients,and this study provided some insights for exploring the complex neu-ropathological mechanisms of alcohol dependence.
维普
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