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Hi, I didn't receive a response to this post; apologies for re-posting if this is quite basic but I'm having trouble finding a practical discussion of these issues. Any help would be invaluable, With thanks, Chris --------------------------- Hi Spmmers, I'm removing artefact from event-related fMRI data using Sue Whitfield Gabrieli's automated artifact detection toolbox (http://web.mit.edu/swg/software.htm). I'm wondering if people are using any standard criteria for removal of images in terms of - 1. Image signal variation (i.e., deviation of signal from the series mean); 2. Participant movement, and 3. Participant rotation. In terms of criteria I've seen, 1. often seems to be used to exclude images that deviate from the mean by more than two or three standard deviations; (which I think makes sense); 2. to exclude images in which movement beyond .5 or 1mm occurred, and for 3. exclusion of iamges where rotation of more than .05 radians occurred. I realise there are unlikely to be rigid criteria, especially given the limitations inherent in scanning some populations, but I'd greatly appreciate anyone point me to a stand-out reference/discussion... With thanks Christopher