Abstract
The reproducibility of activation patterns in the whole brain obtained by functional magnetic resonance imaging (fMRI) experiments at 4 Tesla was studied with a simple finger-opposition task. Six subjects performed three runs in one session, and each run was analyzed separately with the t-test as a univariate method and Fisher's linear discriminant analysis as a multivariate method. Detrending with a first- and third-order polynomial as well as logarithmic transformation as preprocessing steps for the t-test were tested for their impact on reproducibility. Reproducibility across the whole brain was studied by using scatter plots of statistical values and calculating the correlation coefficient between pairs of activation maps. In order to compare reproducibility of "activated" voxels across runs, subjects and models, 2% of all voxels in the brain with the highest statistical values were classified as activated. The analysis of reproducible activated voxels was performed for the whole brain and within regions of interest. We found considerable variability in reproducibility across subjects, regions of interest, and analysis methods. The t-test on the linear detrended data yielded better reproducibility than Fisher's linear discriminant analysis, and therefore seems to be a robust although conservative method. Preliminary data indicate that these modeling results may be reversed by preprocessing to reduce respiratory and cardiac physiological noise effects. The reproducibility of both the position and number of activated voxels in the sensorimotor cortex was highest, while that of the supplementary motor area was much lower, with reproducibility of the cerebellum falling in between the other two areas.