The effects of motion on parametric fMRI analysis techniques

Subject motion during the time course of functional activation studies has been shown to cause spurious signals which can mimic 'true' activation. The refore, the importance of motion correction has been widely recognized. Cor rection with post-processing using image registration software is common pr actice in functional imaging and analysis. Many image registration algorith ms, developed for analysis requirements other than fMRI, assume rigid body motion. Although these techniques are now routinely used by a number of gro ups, rigid body coregistration has not yet been shown to reduce the effects of motion to an acceptable level in fMRI analysis, i.e. the effects on res ulting correlation analysis directly. In this paper we have used volume dat a to assess rigid body co-registration in terms of motion artefacts for the different correlation approaches used in fMRI. We have developed a new way of visualizing motion effects in correlation analysis based on generating a scatter plot of correlation score against local image gradient. This tech nique has been tested an fMRI data sets from a functional paradigm sufferin g from motion correlated artefacts, with and without rigid body motion corr ection. Although we do not attempt to estimate the actual residual motion, this technique can be used to verify the results of analysis and select reg ions of relatively unambiguous activation. This paper assesses directly the rigid body assumption and proves the need for, and effectiveness of, co-re gistration for all correlation based analysis techniques. The specific diff erences between the popular correlation forms used are investigated and exp lained. We show that for certain forms of correlation analysis the effects of motion, while not removed altogether, are effectively statistically elim inated.