Empirically investigating the statistical validity of SPM, FSL and AFNI for single subject fMRI analysis

The software packages SPM, FSL and AFNI are the most widely used packages for the analysis of functional magnetic resonance imaging (fMRI) data. Despite this fact, the validity of the statistical methods has only been tested using simulated data. By analyzing resting state fMRI data (which should not contain specific forms of brain activity) from 396 healthy controls, we here show that all three software packages give inflated false positive rates (4%-96% compared to the expected 5%). We isolate the sources of these problems and find that SPM mainly suffers from a too simple noise model, while FSL underestimates the spatial smoothness. These results highlight the need of validating the statistical methods being used for fMRI.