Study On The Correlation Between The Corpus Callosum And Brain Functional Connection In Patients With Schizophrenia

Schizophrenia(SCZ)is a chronic and persistent major mental illness with a variety of clinical symptoms,including hallucinations,delusions,behavioral abnormalities,cognitive disorders and other variable patterns.The etiology and pathology of schizophrenia are not yet clear.Some studies have suggested that schizophrenia affects the structure of the corpus callosum and the communication of brain function.The corpus callosum(CC),located between the left and right hemispheres,is the main white matter fiber bundle in the brain and plays an important role in integrating the functional activities of both hemispheres.Brain functional connection is a technology that uses non-invasive brain imaging techniques such as functional magnetic resonance imaging to draw the brain functional interaction into the corresponding functional connection matrix.it is a powerful tool to study the functional communication and intensity of various regions of the brain.Although schizophrenia has been studied from various aspects,the relationship between the characteristics of corpus callosum and cross-midline functional connection between left and right hemispheres remains to be explored.In this thesis,we use a sparse canonical correlation analysis(SCCA)method,which can calculate the correlation between two groups of high-dimensional data,and use this method to obtain the correlation between the characteristics of the corpus callosum and the cross-midline functional connection between the left and right hemispheres and the correlation patterns.In this thesis,we first select the functional connection between the left and right brain from the brain functional connection and use the double sample t-test to select the feature to reduce the dimension,then standardize the data,and then use grid search to find the two hyperparameters needed to set SCCA,that is,as two 1-norm penalty factors for regularization,and then use the best parameters for SCCA analysis.Finally,the Permutation test is used to verify whether the canonical correlation coefficient is statistically significant.As a supplement,the generalized additive model is used to analyze the age and gender effects of the functional connections,and the support vector machine is used to establish a classification model with the functional connections between the left and right brain as input features.Our final result is that five groups of canonical vectors are obtained,and their correlation coefficients are 0.82,0.77,0.77,0.76 and 0.76 respectively.These correlation coefficients have been tested for significance,and their P values are all less than 0.05.The five groups of canonical correlation vectors given by sparse canonical correlation analysis show that there is a high correlation between the FA value of corpus callosum and the cross-midline functional connection between the left and right hemispheres in patients with schizophrenia.Moreover,the five canonical correlation vectors are strongly correlated with the five parts of the corpus callosum and the cross-midline functional connections between the left and right hemispheres.In addition,the partial correlation and correlation pattern between corpus callosum and functional connection in patients with schizophrenia were significantly different from those of patients’ age and sex.Finally,the accuracy of the support vector machine classification model is 0.8146.