Delineating The Functional Connectivity Characteristics Of Insula In Schizophrenia Patients

Schizophrenia is a severe mental disease which always associates with physiology disorder,cognition dysfunction and affective dysfunction.In recently years,neuroimaging methods are more and more applying to the patients to detect the lesion in human brain.The MRI neuroimaging method has several advantages such as non-invasive,high spatial resolution.The maturation of MRI technology has given the chance to researchers to detect the abnormal brain lesion in nervous and mental diseases patients.Researches showed that the patients would have structural and functional brain abnormalities for different extent.According to those reasons,this research tried to build the meta-analysis covariant model to discover the covariant relationship between brain regions in nervous and mental diseases patients by using meta-analytic connectivity modeling method.This research also used schizophrenia patients' fMRI and structural data to delineate the insula functional connectivity features by calculating the functional connectivity,dynamic functional connectivity.First,we chose insula region as research starting region,then we got the 13 center nodes of brain regions from the result of meta-analysis by using RtWB(region-to-whole brain)method.This research chose those center nodes of brain regions as the first layer of covariant model.Then we separately used 6mm,4mm as the sphere radius of center nodes of brain regions and used MACM(meta-analytic connectivity modeling)method to construct the covariant relationship between brain regions.Finally we got the functional and structural covariant model.We then calculated the FC(functional connectivity)between 13 regions,functional connectivity between bilateral insula and whole brain voxels,dFC(dynamic functional connectivity)between 13 regions and structural covariance between 13 regions.The first layer of insula covariant model includes bilateral insula,bilateral amygdala,bilateral hippocampus,bilateral caudate,bilateral thalamus,left inferior frontal gyrus,right middle frontal gyrus and anterior cingulate cortex.The functional meta-analysis covariant model results showed that 1.the primary sensory processing network and cognitive related network exist abnormal activation covariant change relationship;2.inside the emotion-memory related network exists abnormal activation covariant change relationship;3.inside the cognitive related network exists abnormal activation covariant change relationship;4.inside the primary sensory processing network exists abnormal activation covariant change relationship.The structural meta-analysis covariant model results show that 1.inside the emotion-memory related network exists grey matter abnormalities covariant change relationship;2.the primary sensory processing network could predict the emotion-memory related network grey matter abnormalities covariant change relationship with it;3.the cognitive related network could predict the emotion-memory related network grey matter abnormalities covariant change with it.The functional connectivity between brain regions results showed increased connectivity in bilateral amygdala,left amygdala and left thalamus,left amygdala and right thalamus,right amygdala and left caudate of schizophrenia patients compared with healthy controls.The dFC between brain regions results showed decreased connectivity between right amygdala and left thalamus,left thalamus and left IFG in schizophrenia patients compared with healthy controls.The structural covariance result showed decreased covariance relationship between bilateral insula,bilateral thalamus,left insula and left thalamus in patients compared with healthy people.From the meta-analysis functional covariant model,this research revealed the abnormal activation covariant relationships can be predict bidirectional in primary sensory processing network and cognitive related network.The structural covariant model results showed that primary sensory processing network and cognitive related network can predict the emotion-memory related network gray matter abnormal covariant change relationship with them.From the schizophrenia MRI data,this research revealed decreased structural covariance inside the primary sensory processing network in patients compared with healthy controls.The functional connectivity revealed increased functional connectivity between primary sensory processing network and emotion-memory related network in schizophrenia groups compared with controls.The dynamic functional connectivity revealed steady time variability between emotion-memory related network and primary sensory processing network.