论文部分内容阅读
Introduction Major depressive disorder(MDD)is a serious mental disorder that negatively affects the quality of life of many individuals,and is a heavy economic burden to society(Belmaker,2008).Disorganized brain activity and un-modulated emotion responses were considered the key neuropathologies underlying depression(Liao,2013).Here we investigated the network alterations in early MDD patients using an eigenvector centrality mapping(ECM)approach,which is voxel-based and free of region-of-interest selection bias.Methods We recruited 28 MDD patients in the present study.Unipolar depression was diagnosed according to DSM-Ⅳ criteria by an experienced psychiatrist.Scores of the Hamilton Rating Scale for Depression(HRSD),Beck Depression Index(BDI),and the Mini-Mental State Examination(MMSE)were obtained from all subjects.All patients were first-episode,drug-nave patients with short disease durations.Twenty-seven normal controls(NC)were also enrolled.All the subjects signed written informed consent before taking part in the study.This research was approved by the Medical Ethic Committee of the Second Affiliated Hospital,School of Medicine,Zhejiang University.Preprocessing was performed using the DPARSF(http://www.restfmri.net)and SPM8(www.fil.ion.ucl.ac.uk/spm/).The first 10 images were excluded from the analysis.The remaining images were corrected for slice timing with the middle slice used as a reference,realigned to remove head motion,normalized into the standard space,and resampled to a 3×3×3 mm3 voxel size.The resulting images were then smoothed using a 4-mm Gaussian kernel before proceeding to the next step.ECM of the preprocessed image data was performed using the fast ECM tool(Wink,2012,https://code.google.com/p/bias/source/browse/matlab/fastECM).Eigenvector centrality differences between the two groups were compared using a two-sample t-test performed in SPM8.The threshold for ECM analysis was set at p<0.001,voxel size >10,corrected using the false discovery rate method.By using ECM,we successfully identified several brain regions where there was a significant difference of nodal centrality.Mean signals were then extracted from all significant clusters,and Pearson correlation was calculated in a pair-wise manner.The correlation coefficients were transformed into z distribution using Fisher r-to-z transformation.A two-sample t-test was used to examine the difference between the two groups.Multiple comparison correction was performed using the Bonferroni method.Results There is no significant differences in age and sex between the two groups.Compared with healthy controls,the patients groups had lower functional connectivity in the bilateral middle frontal gyrus(MFG),insula,hippocampus,amygdala,thalamus,and cerebellum.Meanwhile,the patients had increased functional connectivity in the mPFC.Furthermore,functional connectivity strength at the left thalamus,the right hippocampus and the right insula negatively correlated with the severity of the disease(HRSD).Then we explored the frontal-subcortical connectivity and insula-mPFC connectivity.Ten connections were calculated and compared between the two groups.We found that frontal-subcortical connections were significantly reduced in the patient group.In contrast,the connection between left insula and mPFC was significantly increased in the patients group.Conclusion In general,our study revealed reduced functional connectivity within several important nodes of emotional networks.These results are consistent with two main theories about brain network disruptions in MDD patients,and suggest that functional brain network had already been interrupted in the early stages of MDD.