The Study Of Students’ Brain Information Model With Depression

Depression is a global disease all over the world. According to the report from the World Health Organization, there are about350patients suffering with depression in the world. Depression may affect people’s lives seriously, which may even lead to suicide. About one million of people dying from suicide caused by depression in WHO report. The early diag-nosis of treatment for depression and other mental diseases has very important significance. Functional magnetic resonance imaging (fMRI) technology as a new living brain examina-tion method, can obtain high quality of the information in the brain. This technology provides new way of modeling brain information processing. Further more, it also offers new means for diagnosis of early depression.In this thesis, we study the difference of information processing in brain functional net-work between the teenagers with depression distinguishes and normal teenager as control group, based on the background of functional magnetic resonance imaging. In this thesis, we will do research on functional image as object, from two aspects of distribution of brain activation and independent components of time series. So that we can conclude the brain information processing model with depression. Experiment method is to use conflict Stroop effect experiment design paradigm, the depression of Stroop class information of brain in-formation processing model.In this paper two brain function experiment has been adopted. They are mental arithmetic stress experiment and the Stroop effect experiment. Then the result will be discussed by two methods,activation results imaging studies and the brain regions, for discovering the depressions’impact on the brain information processing model different from normals’. The correlation among different brain regions will be analyzed from two aspects, whose methods are WICA algorithm and ICA algorithm. WICA method mainly use the traditional related analysis for correlation analysis among various regions. On the other side, the correlation will be analyzed by ICA algorithm from the opposite approach, which should be concerned that different brain area in various independent components are independent for each other, but the brain area in same independent component are correlation. So, ICA method are used for analyzing the correlation between various brain areas.Result:The results of WICA analysis suggest that the negative mood generate to be stronger than the subjects of normal group when the subjects of depression group working in the mental arithmetic stress task, therefore more working memory load generated by the subjects of depression group.ICA result show that the depression group of working memory load is higher than the normal group.This situation cause a problem, which let the subjects of depression cost more resources on focus, but the normal control group participants spend less resources to concentrate.