Research On Individual Analysis And Functional Gradient Of Functional Brain Networks In Schizophrenia

Schizophrenia is a severe brain disease.The dysconnectivity hypotheses of schizophrenia suggests that the disorder relates to abnormalities in neuronal connectivity.Resting-state functional magnetic resonance imaging shows that spontaneous neural activity based on blood oxygen level-dependent signals is correlated among brain regions and organized into spatially separated functional networks,which are known to be associated with cognitive impairment in schizophrenia.Consequently,functional connectivity analysis of brain networks based on magnetic resonance imaging has the potential to reveal the pathogenesis of schizophrenia and guide the early diagnosis and prevention of the disease.However,there are still scientific problems to be solved with traditional brain network analysis techniques.For example,most previous studies were based on group level analysis,which failed to fully consider individual differences in imaging,thus unable to promote the development of personalized clinical treatment.Besides,traditional studies failed to integrate brain function and spatial distribution pattern of brain structure,which couldn’t provide researchers with more complete information.In order to detect biological markers of prevention and treatment strategies for schizophrenia and to understand its pathogenesis,individual functional connectivity analysis and functional gradient analysis were used to solve the above problems respectively.In the first part of this study,individual-specific functional brain regions were identified using individual-based and highly sensitive functional mapping techniques,and the functional connectivity among these individual functional brain regions were calculated to predict the severity of symptoms before treatment and the improvement of symptoms after 8 weeks of risperidone treatment in first-episode schizophrenia.The results showed that the two groups of different individual specific functional connections were respectively related to the positive and negative symptoms before the medication,and these connections could also be used to track the improvement of the corresponding symptoms after the trial drug.Among them,the frontoparietal network contributed the most to the prediction of positive symptoms.And for negative symptoms,the combination of the default network and the frontoparietal network had the significant contribution to the prediction model.This research has discovered individualized biological markers that can be used to predict the effect of psychotropic drug treatment at the individual level,which will help advance the process of personalized drug treatment in the field of clinical psychiatry.In the second part of this study,the functional connections between the striatum and the cerebral cortex were first constructed,and then the functional gradients of the striatum were obtained by using a diffusion map embedding technique with nonlinear dimensionreduction to identify spatial axes in connection changes between different brain regions.The results showed that compared with normal controls,the gradient of the striatum of patients with schizophrenia was significantly abnormal,and these abnormalities were correlated with the patient’s multi-dimensional clinical characteristics;In addition,the gradient of the striatum increased gradually in the caudate,pallidus and putamen of the three nuclei.These findings suggest that disturbances in the functional gradient or functional hierarchy of the striatum in schizophrenia may lead to a range of impairments that are related to the level of impaired cognition,providing new insights into the functional organization of the striatum in schizophrenia.In summary,based on the limitations of traditional brain functional analysis,two emerging technologies combined with traditional functional connectivity technology were used to explore the pathological mechanism of patients with schizophrenia,which provides a direction for the further development of functional connectivity technology and also reveals the pathogenesis of schizophrenia to a certain extent.