Research On Brain Structure Differences And Brain Network Dynamics In Patients With Depression

In the current era,the pace of development is fast.The incidence of undergraduate major depressive disorder is exacerbated by the higher and higher pressure of life,learning,interpersonal communication,higher education and employment.Currently,the pathological mechanism of depression is ambiguous and there are still lack of quantitative biological indicators to clearly define depression.Neuroimaging technology has promoted the development of medicine.Brain network is a hot topic in brain science,and the complex network theory provides a theoretical basis for brain network modeling.Based on structural Magnetic Resonance Imaging(sMRI)and Diffusion Tensor Imaging(DTI)data,this paper uses the method of statistical analysis and the complex network theory to research the structure of brain,structural brain network modeling and dynamic evolution of structural brain network in MDD.First,statistical analysis was based on sMRI and DTI data.The experimental results showed that there are obvious gray matter density(GMD)and white matter integrity(WMI)differences in orbitofrontal and temporal lobe in patients with MDD,which validates the role of these brain regions in reward system and emotion regulation circuits.Second,we use machine-learning methods to classify data of gray matter volume in brain regions.The results showed that the highest classification accuracy is up to 81%,suggesting that it has reference value by using gray matter volume information as classification features.Then,we use the complex network theory as the tool to analysis the topological changes of the reward system in MDD.Partial efficiency,clustering coefficient,node degree and node betweenness of reward system in MDD patients showed varying degrees of changes compared to health controls,indicating that MDD patients were with abnormal working patterns among brain regions.Finally,based on the differences of topological properties between groups and the theory of brain network dynamics,a dynamic model of structural brain network evolution is established to simulate the dynamic process of brain lesions.Using the node degree and the Euclidean distance between nodes reproduced the pathological changes of MDD,which provides a new idea for exploring the pathological mechanism of MDD.