Structural And Functional MRI Data Analysis

As the most effective instrument for brain research, imaging techniques can provide visible measures of brain structure and function. Through certain statistical processing, some information of interest revealing the essence of brain structure and function can be extracted from neuroimages. Recurring to these techniques of neuroimage analysis, an appropriate model of brain depicting its structure and function can be constructed, which helps us to make further exploration.This paper is mainly about the methodology and its application of MRI data analysis. Firstly, the history and mechanism of MRI technique are briefly introduced as background knowledges. Secondly, following the explanation of experimental design and data preprocessing, the morphometry methods for structural imaging data analysis, as well as the univariate and multivariate methods for functional imaging data analysis, are overviewed. Thirdly, a detailed discussion is given about the theory and mathematic model of Voxel-Based Morphometry (VBM), Statistic Parameter Mapping (SPM) and Partial Least Squares (PLS). Then a new combined method based on single-frame is presented. As a combination of univariate and multivariate methods, this approach can not only detect the spatiotemporal activations but reveal more subtle spatial patterns within the functional regions. In a certain extent the new approach has syncretized the two ideas of functional segregation and functional integration. Lastly, these methods are applied to several brain data acquired from different experimental designs. A specific decrease of gray matter concentration in PTSD patients is found using Optimized-VBM, and a comparison on analyses of the auditory experimental data with factorial design is made between SPM and PLS. Furthermore, SPM is applied to"n-back"task experimental data to explore the brain mechanism of working memory and the specific functional injury of schizophrenic patients. At last, the new combined method is validated by analyzing the finger movement experimental data.