Global approach to multivariate correlation analysis of brain positron emission tomographic images

In this paper, we propose a multivariate correlation analysis of PET brain images. PET images provide the means to understand the functionality of brain. By examining the correlations between the PET images and external variables, such as emotional or psychosensory experiences, it is possible to determine which parts of the brain are related to the given external variables. So far, most correlation analyses have concentrated on one variable at a time. However, this type of univariate approach rapidly becomes impractical as the number of external variables increases because the analysis produces an overwhelming amount of data. In this paper, we extend the correlation analysis to multiple variables. The technique makes it possible to analyze a large number of variables and shows the importance of each variable.