The Research Of Independent Component Analysis And Itsapplication In Schizophrenic For Resting State FMRI

The functional activity of brain can keep basic physiology state and finish the basic of advanced function activity. The abnormal or disorder of brain functional activity may lead to the happening of the disease in the brain or other parts. Therefore, the study of brain function is always a hotspot in biomedical research. Functional magnetic resonance imaging can observe function activity of brain in non-invasive under normal physiological state, it has been widely used in basic research of brain and gets many important research results. As rest state functional magnetic resonance imaging has sample operation and patients can cooperate easily. It has been widely used in brain research, especially for patients with difficult to complete tasks.For rest state f MRI, though the statistical analysis of data, such as functional connectivity, brain network analysis, etc. In these analysis methods need to decide one or more region of interest in advance. Currently, the common methods of ROI selection are determined by researcher which based on prior knowledge and extracted by independent component analysis which based on data driven. Among all the methods, Independent component analysis. ICA has advantage of high objectivity and without depending on prior knowledge. However, ICA also has some disadvantage, such as, when the number of component is different, there are difference in the components isolated by ICA, which will cause the instability of the component result. Therefore, according to different research needs, how to determine the effective independent component from the components isolated by ICA is the problem to be solved. This thesis takes different component numbers to get the effective independent components objectively, which is isolated by different component number making no difference.Besides, when the f MRI data analysis is proceeded, the approach of filtering always is used to remove the noise information. The current f MRI data analysis in rest state f MRI is focusing within 0.01-0.08 Hz. When the research of brain function is different, there are difference in the frequency band of neural activity. Different frequency band contains different brain functional information. Therefore, all the researches which use the same frequency band for analysis will cause the loss of effective information. This thesis takes spectrum method to proceed ICA for the rest state functional magnetic resonance imaging datas within the range of frequencies, which can decide the best frequency band for the different researches.Finally, this thesis combine the above two methods to explore the schizophrenia. Through the research conclusion of this paper finds that the function of the regions of left inferior temporal gyrus, right inferior temporal gyrus, right orbitofrontal cortex superior, left superior frontal gyrus medial have abnormal. The region of left inferior temporal gyrus has significance abnormal functional connection with others in schizophrenia. It turns out that we can use the method of this paper to determine these dysfunctional regions with mood disorders, memory impairment exactly, which is connect with clinical symptoms of schizophrenia.