I have an experimental design with multiple between and within-subjects factors, split across multiple experimental runs (by runs, I mean separate fMRI time series acquisitions, separated by a minute or so during which no MRI data are collected). The multiple runs share a common baseline condition, but vary in the attentional load for the experimental condition. It would make the analysis of these data much less cumbersome to concatenate the fMRI data together into a single run and submit this concatenated file to GLM. This practice has been discouraged multiple times on this listserv, but I have not been able to determine from these posts if concatenation is *always* a problem, or if it is a problem only in some instances – namely, before pre-stats have been carried out (motion correction and temporal filtering). My questions:
1) If one were to run pre-stats on each fMRI time series, then register them together (either directly or by placing all of them in MNI space), would it then be acceptable to concatenate them for submission to GLM?
2) If not, why not? What problems would remain that were not handled by running pre-stats separately on each time series?
3) Are there any additional preprocessing steps that could fix these problems?
Thanks,
John
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