Links - Realignment
E-mail thread (1999) between Field and Ashburner about entering motion parameters into your design matrix (click 'Next in Topic' once you're there to follow the thread along) Thread
E-mail thread (2000) between Flaisch, Henson, and others, more about motion parameters in the design (click 'Next in Topic' once you're there to follow the thread along) Thread
Summary: For both of these: Including your motion parameters in your design matrix is like regressing out motion-correlated signal, which can reduce your false positives at the expense of reducing your true positives. Values derived from the parameters (sines, squares, etc.) can also be useful.
Bottom line: Including these depends heavily on your own study - how much motion, how big your signal is. Some objective tests (like Skudlarski et. al PDF have shown, in general, that it doesn't make a huge difference either way. Probably worth testing on your own studies...
E-mail thread (2003) from Jesper Andersson, who wrote the unwarping code, and others, about why unwarping is useful and how it differs from including your motion parameters in your matrix. (click 'Next in Topic' once you're there to follow the thread along) Thread
Summary: Good overview of unwarping from the guy that wrote it.
Bottom line: If you use EPI, it can be useful. Unwarping is a more highly targeted version of including your motion parameters in your design matrix - instead of taking out ALL motion-correlated variance (including real activations), it only knocks out motion-by-susceptibility artifacts, and those hopefully account for a good chunk of your motion artifact, particularly in high-susceptibility regions.