PROBABILISTIC ANALYSIS OF FUNCTIONAL MAGNETIC-RESONANCE-IMAGING DATA

Probability theory is applied to the analysis of fMRI data. The poster ior distribution of the parameters is shown to incorporate all the inf ormation available from the data, the hypotheses, and the prior inform ation. Under appropriate simplifying conditions, the theory reduces to the standard statistical test, including the general linear model. Th e theory is particularly suited to handle the spatial variations in th e noise present in fMRI, allowing the comparison of activated voxels t hat have different, and unknown, noise. The theory also explicitly inc ludes prior information, which is shown to be critical in the attainme nt of reliable activation maps.