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help > RE: Original data replaced after preprocessing?
Mar 10, 2023 04:03 PM | Alfonso Nieto-Castanon - Boston University
RE: Original data replaced after preprocessing?
Hi Jeremy,
All secondary datasets and related options have been moved from the 'Functional data' section (in Setup.functional) to the 'Other imaging data' section (in Setup.Other), mainly because the use of secondarydatasets has been extending over time to cover more and more things which were not limited to just "functional" data any longer (e.g. fieldmaps files, VDM files, subject-specific TPM files, etc.)
Hope this helps
Alfonso
Originally posted by Jeremy Smith:
All secondary datasets and related options have been moved from the 'Functional data' section (in Setup.functional) to the 'Other imaging data' section (in Setup.Other), mainly because the use of secondarydatasets has been extending over time to cover more and more things which were not limited to just "functional" data any longer (e.g. fieldmaps files, VDM files, subject-specific TPM files, etc.)
Hope this helps
Alfonso
Originally posted by Jeremy Smith:
Apologies for
resurrecting this old thread, but I'm wondering where the "move"
option and the "datasets dropdown menu" can be found in version
21.b...
Kind regards,
Jeremy Smith.
Originally posted by Alfonso Nieto-Castanon:
If you want to redo
preprocessing from scratch you should first move the data listed in
the 'original data' dataset to the 'primary dataset' (you can do
that selecting the 'move' option in the datasets dropdown menu),
and then preprocess all subjects again
Kind regards,
Jeremy Smith.
Originally posted by Alfonso Nieto-Castanon:
Hi
Jeremy,
Yes, preprocessing takes the functional data indicated in the 'primary dataset', preprocesses it, and points again the 'primary dataset' to the fully preprocessed data.
If you want to redo preprocessing from scratch you should first move the data listed in the 'original data' dataset to the 'primary dataset' (you can do that selecting the 'move' option in the datasets dropdown menu), and then preprocess all subjects again
If, on the other hand, you simply want to preprocess only newly-added subjects (after you have already preprocessed some other subjects' data) you can then run preprocessing normally but remember to uncheck in the preprocessing GUI the 'all subjects' field and select only the new subjects there (so that preprocessing is only run on the new subjects data, and the previous subjects data is left unchanged)
Hope this helps
Alfonso
Originally posted by Jeremy Smith:
Yes, preprocessing takes the functional data indicated in the 'primary dataset', preprocesses it, and points again the 'primary dataset' to the fully preprocessed data.
If you want to redo preprocessing from scratch you should first move the data listed in the 'original data' dataset to the 'primary dataset' (you can do that selecting the 'move' option in the datasets dropdown menu), and then preprocess all subjects again
If, on the other hand, you simply want to preprocess only newly-added subjects (after you have already preprocessed some other subjects' data) you can then run preprocessing normally but remember to uncheck in the preprocessing GUI the 'all subjects' field and select only the new subjects there (so that preprocessing is only run on the new subjects data, and the previous subjects data is left unchanged)
Hope this helps
Alfonso
Originally posted by Jeremy Smith:
In the GUI, when I run Preprocessing on a set of
subjects, it looks like the previously-processed data gets labeled
as the "original data." This is particularly a concern when I add
more subjects to the pipeline and re-run Preprocessing. For
example, I'm concerned that if I apply a particular smoothing
kernel and Preprocess one batch of subjects, then add more subjects
and re-run Preprocessing, that the smoothing kernel is applied
twice to the first batch of subjects. (If I keep the same
kernel, this shouldn't be a problem, but what if I want to re-run
with a 4mm or 5mm kernel?)
Can someone confirm that the original data (say, subject01_rsfmri.nii) is replaced by the processed data (say, suwususus_subject01_rsfmri.nii) after one Preprocessing run? Is there a way to avoid this?
Can someone confirm that the original data (say, subject01_rsfmri.nii) is replaced by the processed data (say, suwususus_subject01_rsfmri.nii) after one Preprocessing run? Is there a way to avoid this?
Threaded View
Title | Author | Date |
---|---|---|
Jeremy Smith | Oct 6, 2021 | |
Alfonso Nieto-Castanon | Oct 6, 2021 | |
Anna Kwiatkowski | May 23, 2024 | |
Jeremy Smith | Mar 10, 2023 | |
Alfonso Nieto-Castanon | Mar 10, 2023 | |
Jeremy Smith | Oct 7, 2021 | |