Hi everyone, In a previous discussion on this list (http://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg17681.html), Pablo Polosecki was asking the best way to perform hypothesis testing using functional data within an ROI. The final opinion was that it was best to average all of the time courses in the ROI, and re-run the analysis from scratch, so that all of the appropriate whitening, etc. occurred.
I was considering doing this, creating a small volume (say, 10 voxels total) that had each voxel holding the average time course from one of 10 ROIs. I would then set up and run a usual fsfast analysis using these tiny volumes. I am using freesurfer 4.5. I have a few questions. 1) Is this reasonable? 2) One area where I expect to run into problems is with the whitening. If I set -acfbins to the total number of my dummy voxels, and -acffwhm to 0, will this use the autocorrelation function of the average timecourse within each individual ROI? Is that an appropriate approach? How sensitive will this be to the number of actual voxels averaged to get each ROI (for instance, would this bias me to finding more significant results in ROIs containing fewer voxels?). 3) Are there other steps that depend upon the spatial arrangement of voxels that I am forgetting, and will these steps choke on these small volumes (or worse, fail in silent but pernicious ways). Thanks for all of the help, Clark
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