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@@ -380,9 +380,8 @@ More information on DataLad and how to use it can be found in the DataLad Handbo
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datalad run -m "plot size of ROIs per subject" \
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./code/plot_voxel-counts.py
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-
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<!---
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-### non-finalyzed scripts
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+### non-used scripts
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### plot_srm.py
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# manually add script that ...
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@@ -391,19 +390,4 @@ More information on DataLad and how to use it can be found in the DataLad Handbo
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### plot_bland-altman.py
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# manually add script that ...
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datalad save -m 'add script that plots Bland-Altman-Plots'
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-
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-# From PPA study; do similarly according to current dataset
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-
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-### comment: some cleaning that we did
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-
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-In order to limit the dataset to an appropriate size, we dropped some files that were generated by FEAT during an intermediate stage of the first level analyses. More specifically, we dropped *filtered_func_data.nii.gz* (4D fMRI data after all filtering) and *res4d.nii.gz* (residual noise images) for every subject and run using the following commands
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-
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- git annex unused
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- git annex dropunused all --force
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- datalad drop --nocheck sub*/*.feat/filtered_func_data.nii.gz
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- datalad drop --nocheck sub*/*.feat/stats/res4d.nii.gz
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- git rm sub-*/run-*.feat/filtered_func_data.nii.gz
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- git rm sub-*/run-*.feat/stats/res4d.nii.gz
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-
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-If necessary, the files can be obtained by rerunning the corresponding first level analysis.
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-->
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