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help > RE: CONN compatibility with BIDS and fmriprep output
Feb 14, 2019 09:02 PM | Karolina Finc
RE: CONN compatibility with BIDS and fmriprep output
Dear Alfonso,
Thank you very much for the detailed answer. I'm very excited to hear about new BIDS-compatible functionalities in CONN!
In case of fmriprep, it is possible to load fmriprep output into CONN (after small modifications). One of the fmriprep output is confounds.tsv table including 6 motion parameters, values extracted from 5 aCompCor components, Framewise Displacement, DVARS, and many others.
The way how to load fmriprep output data into CONN depends if someone wants to obtain some confounds via CONN, or only use the confounds file from fmriprep. So far I did it in a way, that I've selected 6 motion parameters from confounds.tsv file, saved them as .txt file and load them in using CONN batch together with anatomical and functional data. I've also taken DVARS and Framewise Displacement variables to calculate outlier scans outside CONN (in the same way it's done with ART outlier detection). In case of aCompCor, it should also work (but I didn't try this myself yet) to load aCompCor values from fmriprep and skip loading WM and CSF masks, which are later used by CONN for calculation of aCompCor components. Am I right?
I think that for future releases of CONN it would be great to load whole confounds.tsv with the option to select only confounds we want to include in the denoising step. Column names of the selected variables from .tsv output would be automatically extracted as names of confounds in CONN. I think this could be a very useful functionality.
Hope this help in future releases! I'm also happy to provide some further advice if that may be useful. I'm also sure that Oscar Esteban (oesteban@stanford.edu) and other fmriprep developers will be open to cooperate on making fmriprep available for a broader audience of researchers.
Best,
Karolina
Thank you very much for the detailed answer. I'm very excited to hear about new BIDS-compatible functionalities in CONN!
In case of fmriprep, it is possible to load fmriprep output into CONN (after small modifications). One of the fmriprep output is confounds.tsv table including 6 motion parameters, values extracted from 5 aCompCor components, Framewise Displacement, DVARS, and many others.
The way how to load fmriprep output data into CONN depends if someone wants to obtain some confounds via CONN, or only use the confounds file from fmriprep. So far I did it in a way, that I've selected 6 motion parameters from confounds.tsv file, saved them as .txt file and load them in using CONN batch together with anatomical and functional data. I've also taken DVARS and Framewise Displacement variables to calculate outlier scans outside CONN (in the same way it's done with ART outlier detection). In case of aCompCor, it should also work (but I didn't try this myself yet) to load aCompCor values from fmriprep and skip loading WM and CSF masks, which are later used by CONN for calculation of aCompCor components. Am I right?
I think that for future releases of CONN it would be great to load whole confounds.tsv with the option to select only confounds we want to include in the denoising step. Column names of the selected variables from .tsv output would be automatically extracted as names of confounds in CONN. I think this could be a very useful functionality.
Hope this help in future releases! I'm also happy to provide some further advice if that may be useful. I'm also sure that Oscar Esteban (oesteban@stanford.edu) and other fmriprep developers will be open to cooperate on making fmriprep available for a broader audience of researchers.
Best,
Karolina
Threaded View
Title | Author | Date |
---|---|---|
Karolina Finc | Feb 9, 2019 | |
Alfonso Nieto-Castanon | Feb 14, 2019 | |
Karolina Finc | Feb 14, 2019 | |
padma | Jul 12, 2021 | |
omaomae | Jul 12, 2021 | |
padma | Jul 13, 2021 | |
omaomae | Jul 14, 2021 | |
padma | Jul 9, 2021 | |
Harrison Fisher | Mar 13, 2019 | |
Karolina Finc | Mar 19, 2019 | |
David Pagliaccio | Mar 18, 2021 | |
Kylie Isenburg | Jun 11, 2021 | |