Hi all,
For PPI, when would you recommend extracting the time series for seed ROIs? The issue I have revolves around wanting to add the standard motion parameters (and outlier matrix) as confound EVs, however, this step can only be done when combining Prestats/1stLevel together. Because the ROI timeseries must also be entered in this step, there is no preprocessed (filtered_func) data to extract the time series from.
I have found two threads that seem to be related (one of which asks about using already pre-processed/1st Level data from a non-PPI analysis):
Using non-PPI data/filtered_func:
https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=FSL;ae85ed75.1203
Using res4d:
https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=FSL;2cbeb48.1404
In both of these cases, it seems that it is necessary to run the 1st Level model twice: One for pre-processing/applying ROI to subject space/extract time series, and the other for running the full PPI model with PSYC, PHYS regressors. Further, for both 1st Level models, it seems proper to ensure motion confounds are included so that the ROI time series is accurate.
If this all makes sense and is correct, I have two questions:
1. What is the recommended data file from the initial 1st Level model to apply ROI to subject space and extract time series?
2. What would you use as the INPUT for the second 1st Level analysis (which now includes PSYC, PHYS regressors)?
Thank you for any input!
Erin
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