Analyzing fMRI data based on multi-resolution factorial kriging

Functional magnetic resonance imaging (fMRI) is a harmless technology for studying the human brain functions that has been developed recently. Multi-resolution analysis, which is applied to fMRI, is a new dealing method. In statistical analysis, many statistical algorithms identify whether each pixel is activated by counting the serial time of them dependently, or by taking the spatial relativity of pixels into account. Factorial kriging based on multi-resolution analysis count the spatial relativity of pixels by the serial time of each one. The spatial relativity can be approximated using the orthogonal least square method and standard different scale variation structure models. It counts the spatial relativity among pixels and factorialy analyze the spatial relativity of different scales in order to get the contribution to the main factors of slice pixels in different scales and indicate the activated areas of brain by the given threshold. In the paper, the cross-variograms, cross-covariance, standard variogram structure function and cooperating regional matrixes are studied and the regional factors estimation and identifying parts of brain activated by factorial kriging are carried out. The results give a primary conclusion to prove the validity of the methods.