Effective connectivity of brain regions based on brain data (e.g. EEG, fMRI, etc.) is a focused research at present. Many
researchers tried to investigate it using different methods. Granger causality model (GCM) is presently used to
investigate effective connectivity of brain regions more and more. It can explore causal relationship between time series,
meaning that if a time-series y causes x, then knowledge of y should help predict future values of x. In present work,
time invariant GCM was applied to fMRI data considering slow changing of blood oxygenation level dependent
(BOLD). The time invariant GCM often requires determining model order, estimating model parameters and significance
test. In particular, we extended significance test method to make results more reasonable. The fMRI data were acquired
from finger movement experiment of two right-handed subjects. We obtained the activation maps of two subjects using
SPM'2 software firstly. Then we chose left SMA and left SMC as regions of interest (ROIs) with different radiuses, and
calculated causality from left SMA to left SMC using the mean time courses of the two ROIs. The results from both
subjects showed that left SMA influenced on left SMC. Hence GCM was suggested to be an effective approach in
investigation of effective connectivity based on fMRI data.
Spatial normalization is a very important step in the processing of magnetic resonance imaging (MRI) data. So the quality of brain templates is crucial for the accuracy of MRI analysis. In this paper, using the classical protocol and the optimized protocol plus nonlinear deformation, we constructed the T1 whole brain templates and apriori brain tissue data from 69 Chinese pediatric MRI data (age 7-16 years). Then we proposed a new assessment method to evaluate our templates. 10 pediatric subjects were chosen to do the assessment as the following steps. First, the cerebellum region, the region of interest (ROI), was located on both the pediatric volume and the template volume by an experienced neuroanatomist. Second, the pediatric whole brain was mapped to the template with affine and nonlinear deformation. Third, the parameter, derived from the second step, was used to only normalize the ROI of the child to the ROI of the template. Last, the overlapping ratio, which described the overlapping rate between the ROI of the template and the normalized ROI of the child, was calculated. The mean of overlapping ratio normalized to the classical template was 0.9687, and the mean normalized to the optimized template was 0.9713. The results show that the two Chinese pediatric brain templates are comparable and their accuracy is adequate to our studies.