A Study Of Effective Connectivity And Its Application In Schizophrenic For FMRI

The human brain is a complex dynamic system. Task-related brain regions areactivated when stimulated by external tasks, then complete a series of informationprocessing through coordination and integration, enabling people brain to achieveadvanced features. The study of human brain function dependent on the developmentand progress of a imaging techniques. Functional magnetic resonance imaging whichgrows depends on MRI has the advantages of non-invasive, repeatable measurements,high spatial resolution and high temporal resolution. In recent years, fMRI has beenwidely used in the study of brain functions, especially in the research of psychiatry hasconsiderable potential and provides a powerful research tool.fMRI studies of brain function has two directions: functional segregation andfunctional integration, functional segregation studies the task-related brain areas,functional integration explores how brain regions accomplish a task. Functionalintegration is usually based on functional connectivity and effective connectivity.functional connectivity is defined as statistical dependencies among brain areas,Effective connectivity explores the correlation, the reaction causal mechanism ofinformation transfer and the connection strength between brain regions. The study ofeffective connectivity depends on the causal effects model. Many methods commonlyare used to research the effective connectivity, such as dynamic causal modelingmethods (DCM), Granger causality model (GCM), structural equation modeling(SEM), and so on. At present, Dynamic causal model becomes the most widely usedmethod because it combines neural dynamics model with hemodynamic model to builda dynamic, non-linear and more realistic model from the level of neuron, and alsoconsiders the external disturbance factors. DCM has some shortcomings althoughDCM reveals the dynamic flow of information, such as, DCM relies on pre-determinedbrain regions. At present, the region of interest (ROI) are determined by priorknowledge, ROI may be related to brain disease in previous studies, we can not find new brain regions, in addition, previous studies have find that brain regions are notuniform and the selected brain regions in the present study are not necessarily activated.To solve this proble，this paper combines data-driven with model-driven to determinethe ROIs. The way identifies the effective connectivity based on the viewpoint of wholebrain from a more global and objective view, then applies to explore the effectiveconnectivity in schizophrenia to study its pathophysiology and provide a theoreticalbasis for the prevention of disease.Schizophrenia is a serious mental illness, most of them have cognitive impairment,Currently, there is still no clear conclusion on the pathogenesis of schizophrenia andbrain regions involved, schizophrenia is generally considered poor integration of brainfunction. In this paper,25patients with schizophrenia and27healthy volunteersparticipated to complete the fMRI data acquisition under the N-back task, then exploresthe different of effective connectivity of the two groups at the completion of cognitivetask by the method established in the paper and determines the abnormal pathologicalmechanism of functional integration of brain in schizophrenia, this paper provides apreliminary conclusion: schizophrenic patients and normal controls have oppositeeffective connectivity among the left of Superior frontal gyrus medial(MPFC), the leftof posterior cingulate gyrus(PCC) and the left of the middle cingulate gyrus(DCG),implying abnormal effective connectivity may be the pathophysiological basis of brainfunction in schizophrenia.The regions of interest are identified on the left, suggestingthat cognitive impairment may be specific in the left hemisphere of the brain. Theprefrontal functional abnormalities of schizophrenia may be associated with a declinein working memory, the abnormal effective connectivity in schizophrenia suggestingthat the patient’s unconscious experience is flawed, leading to a neutral event occursexcessive error.