Clustering Analysis Of FMRI Activation Area

The performance of logical operation on data plays an important role in fMRI studies. With the development of the technology of human brain mapping such as PET and fMRI etc., scientists have obtained much useful information about localization of functional brain regions, functions of some brain regions and the relationship among various functional regions. fMRI data analysis has become an important field. A number of mathematic methods have been realized by means of advanced computer languages and become successful algorithms in the field of neuroimaging.In this article, we explored the application of clustering analysis with dendrogram sharpening in the analysis of fMRI data and obtained satisfying results. We first modeled the time series of activation area in order to save computer's running time. The dendrogram sharpening has been applied to the cluster analysis to form the algorithm of cluster analysis with dendrogram sharpening. After applying the algorithm to artificial data and real fMRI data seperately, we get the satisfying result. Lastly, we statistically analized the valuable and statistical variables designed on the basis of neurology using the soft named SPSS and get the result that there are distinguishabilities between clusters,so this validate the availability of the discussed algorithm of clustering analysis with dendrogram sharpening.