Null Data Study

Having established the accuracy of MCFLIRT on artificial data, we ran both our scheme and SPM99 on a number of real fMRI studies. In all instances, the subjects had been exposed to no stimulus (null data). The underlying assumption was that after motion correction on a null data study, we would expect the overall variation of the data to be lower than before correction as subject motion-induced variablity had been minimized. Again, results were masked according to the SPM data to give a fair comparison. Results, given in Figure 16, show considerable changes induced by SPM (both beneficial and detrimental) but only minimal changes induced by MCFLIRT. This is due to the fact that the amount of actual motion that occurred in these studies is very low, so that the changes in intensity in each voxel (as a result of motion correction) are also low -- in fact lower than the expected changes induced by physiological processes. Consequently, these test results are inconclusive since the test measure does not purely measure motion-induced changes but also physiological changes which dominate in this case. The only way one could expect to obtain quantitative analysis for real data would be to incorporate some form of position measurement into the scanner -- a facility not available to us.

Figure 16: Summary MARV statistics for three sets of real data, comparing MCFLIRT w. CR, and SPM99 correction using full quality, sinc interpolation and interpolation error adjustment. The results show the range of percentage changes in residual variance as a result of the motion correction (i.e. comparing it to the uncorrected variance).