The Rest-State Network Functional PPI Analysis Of MDD

Background:Major Depressive Disorder(MDD)is considered a complex system of dysfunction interlinked neural circuits,within these circuits is thought to be associated with the shift of specific neurotransmitters or structural of the neural substrate.However,previous study just focus on functional connectivity MRI research,which only assessed the functional connectivity degree within a specific network or between some regions of interested(ROI)without consider the modulatory effects come from other region,therefore,we adopt a method which is called physiophysiolocal interaction analyze to find the efficiency from other regions.Methods : The PPI analysis was conducted using a voxel-wise statistic using the general linear model(GLM)framework in SPM8.By defining two ROIs,standing for a network.PPI analysis identified regions where the connectivity with one selected ROI was correlated with the increasing or decreasing activity of the second selected ROI,consequently get the modulatory effects of others regions.Results : The modulatory interaction effects of brain network inpatients with depression compare with controlled group network adjustment is totally different.Insular gyrus and supramarginal gyrus of depression patients revealed the key function of sick brain,but healthy people showed another result.The difference between healthy group and depression patients further explains the disorder of brain network,in another way,this result would support research figure brain function better.Conclusions : The result of PPI analyze to rest-state networks indicate that the modulatory effects between healthy and sick cohort are different and by using the interaction analyses in neuroimaging will have utility in understanding the neural disruptions to emotion process in these disorders.We also find the disorder connected RSNs of MDD patient.These phenomena provide a persuasive evidence to prove the difference between major depression disorder and healthy people.