Hello, After running a seed-based connectivity 1st level analysis on an individual subject, is it possible to pull out the mean BOLD activation (across all time-points; all runs) in a way that any “noise” in the time-series has already been regressed out (i.e., motion, ventricle, csf, wm, global mean, high/low pass filter)? I imagine it is one of the outputs in the analysis folder and not found within any particular FC seed sub-folder (containing pcc.nii.gz, etc.). In other words, one may run different seed-based connectivity analyses, but the mean activation estimate will not change so long as the nuisance parameters stay the same.
The meanfunc overlay looks to be what I’m interested in, but unclear if this is created after regressing out nuisance parameters.
Thanks. -Louis
Hi Louis, yes, meanfunc is after all regresssions, etc. doug
On 3/28/2023 12:08 PM, Vinke, Louis N.,PHD wrote:
Hello,
After running a seed-based connectivity 1^st level analysis on an individual subject, is it possible to pull out the mean BOLD activation (across all time-points; all runs) in a way that any “noise” in the time-series has already been regressed out (i.e., motion, ventricle, csf, wm, global mean, high/low pass filter)? I imagine it is one of the outputs in the analysis folder and not found within any particular FC seed sub-folder (containing pcc.nii.gz, etc.). In other words, one may run different seed-based connectivity analyses, but the mean activation estimate will not change so long as the nuisance parameters stay the same.
The meanfunc overlay looks to be what I’m interested in, but unclear if this is created after regressing out nuisance parameters.
Thanks.
-Louis
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Douglas N. Greve -
Vinke, Louis N.,PHD