A Study On Resting-state Functional Networks Based On Magnetic Resonance Imaging And Its Application In Major Depressive Disorder

Major depressive disorder(MDD)is a common psychiatric disease.With the progress on MDD research,MDD is increasingly understood as a disorder of distributed effects of abberrant interaction in the brain.With the Development of functional magnetic resonance imaging(fMRI)analysis method,brain is seperated into functional networks which is spatially seperated but functionally connected.These networks has the same pattern in both resting state and task state.The functional network architechture could simplify the study of functional brain organization from infinite variety of task states to the state space constrained by functional network architecture.Therefore,investigating the structure and interaction of the resting-state functional network is import to the understanding of the functional organization of the brain and its abnormality in the psychiatric disorders.The abnormal functional connectivity has been reported in patients with MDD.The abnormality has been detected in many functional networks including the default mode network(DMN),central executive network(CEN)and salience network(SN),the abnormality could be normalized after antidepressent treatment.The altered function in one region could be transfer to another region through the neural interactions.Thus,investigating the direction of the connection between the nodes within the functional networks is crucial for understanding the neural mechanism of the disease.Effective connectivity analysis method could provide the direction and coupling strength,but prior information is needed to construct the valid model.Therefore,investigating the effective conectivity between the nodes within the functional networks is a hot topic.The active level of functional network is different due to the brain state.The functional connectivity between networks can be assessed using the time courses of active level for the functional networks.The functional network connecvity can reflect the swiching and syncronization between the networks.The abberrant swiching and syncronization between the networks is detected in various psychiatric disorder.Therefore,investigating the interaction between the functional networks is also a hot issue.The subcortical area has rich neural projection to the cortical area.The cortical region functionally connected with certain subcortical area is defined as functional projected network.The subcortical area could modulate the activity of the functional projected networks.We can subdivide the subcortical area based on the fucntional connectivity between the voxel of the subcortical area and the functional networks.Investigating the connectivity between the subcortical area and functional networks,and the corresponding subdivision of the subcortical area is important for the physical interference of the subcortical area with deep brain stimulation(DBS).In accordance with the previous topic,we investigate the functional network in patients with MDD from prospective of connectivity within network,connectivity between network and connectivity between the voxel and functional projected network.The main works including the following parts:In the first chapter,we analyzed the effective connectiviy within the functional networks.Previous study has showed abnormal connectivity in DMN,CEN and SN.To investigate the causal interactions between the nodes within the functional networks.We introduced spectral dynamic causal modeling(spDCM)to investigate the effective connectivity within the functional networks mentioned above.First,we used independent component anaylsis to decompose the functional networks.Then,the networks closely related to MDD were selected including DMN,CEN,ventral SN and anterior SN.Then,choosing the nodes of the functional network based on the spatial pattern of the functional networks.Finally,we constructed the dynamic causal model based the on the chosen nodes,and estimated the model using spectral DCM mehtod.The result indicates that the effective connectivity altered in SN,CEN and DMN.Based on the pattern of the altered conncetivity,we found that the reduced causal influence from left parietal cortex(LPC)to other nodes are the key alteration in DMN.Similarly,the reduced casual influence from right anterior insula(RAI)to other nodes of SN is the key alteration within SN.In the CEN,the increased modulate effect from left frontal cortex(LFC)to other nodes is the key alteration.In the second chapter,the dynamic causal modeling(DCM)was introduced to model the interactions between the networks.The stochastic and spectral DCM were performed to evaluate the effective connectiviy between the functional networks that are related to MDD including anterior SN,ventral SN,anterior DMN,posterior DMN,left CEN and right CEN.We compared the results of existing method including Pearson correlation method and maximum lagged correlation method in pre-treatment group,post-treatment group and healthy control group.The result from the model optimaztion of DCM indicated that the ICA time course is causally connected with each other.The effective conectivity pattern from spectral DCM indicated that the modulation effects of SN on DMN and CEN were abnormal in the patients with MDD.We also discovered the modulation loop between the DMN and CEN.The opposite modulation effects that ventral SN and posterior DMN performed on the anterior DMN were impaired in the patients with MDD.Abnormal stimulation effect from posterior DMN to left CEN and right CEN were detected.The abnrmality could be normalized after the treatment.In the third chapter,we used functional topography method to analyze the relationship between the voxels in thalamus and the networks.First,we calculated the functional connectivity maps for all the thalamus voxels.Then,the spatial ICA method was used to identify the functional topography pattern,the anterior SN,ventral SN,anterior DMN,posterior DMN,left CEN,right CEN and motor network were selected.We modified the multiple regression method,and performed the constrained spatial multiple regression on the functional networks,resulting the connections between each thalamus voxel and networks.The results indicated that the subdivision of thalamus share the same pattern with the previous study.Voxels in the anterior part of right thalamus showed signifcant decreased functional connecivity with right CEN,which leading to the right thalamus showed decreased functional connectivity with the right CEN.Voxels in the ventral part of lateral thalamus showed signifcant decreased functional connecivity with motor network,but this result did not servive from the false discovery correction.Aiming to the problems on the brain functional network analysis,we investigated the functional networks from three prospective including the effective connectivity within the networks,connectivity between the networks,the connectivity between the voxel and networks.We located the key region of the abnormal functional networks by using the effective connectivity analysis within the networks.The altered causal interations between networks are identified by performing the analysis of functional network connectivity.The abnormal projections from thalamus to cortical regions through the functional topography analysis.We provide a framework to investigate the functional networks which could be used in other research.