Are the datasets in nilearn post fmriprep?

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Hi,
Are the data when fetching existing datasets normally after or before fmriprep?

For example, in this encoding model - https://nilearn.github.io/auto_examples/02_decoding/plot_miyawaki_encoding.html#sphx-glr-auto-examples-02-decoding-plot-miyawaki-encoding-py

Are the functional files in dataset.func[12:] before or after fmriprep?

I am asking since I want to build something similar to my data, and I want to know if I should take raw data or fmriprep-ed

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Hi @orko,

The nilearn datasets should have more information on their processing in their docstrings, though this could certainly be expanded !

The majority have undergone some level of preprocessing, though relatively few have been run through fMRIPrep specifically (the main exception I can think of is the fetch_development_fmri dataset).

For the fetch_miyawaki2008 dataset in particular, it’s had some level of processing (see: it’s already masked), and if you’re planning to run a similar analysis as the example you linked, I would definitely recommend preprocessing first !

HTH,

Elizabeth

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@emdupre Can I know what the dataset background is?
It is '/root/nilearn_data/miyawaki2008/bg.nii.gz' and it produces a whole-brain image (See in https://nilearn.github.io/auto_examples/02_decoding/plot_miyawaki_encoding.html#mapping-the-encoding-scores-on-the-brain)
But is there anyway to know how it was created? I didn’t see any such output from fmriprep or in BIDS. Is there a conventional way to fetch it, or maybe a common source? or is it dataset-specific?

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Hi @orko !

This dataset background is specific to this dataset; in general, you’d likely want to put the anatomical template used for normalization as a background. For example, Nilearn ships the MNI152 template, which is commonly used for anatomical normalization. Indeed, many functions such as plot_stat_map automatically put the MNI152 template as a background because of how commonly it’s used within the community !

If you’re preprocessing with fMRIPrep, though, you may notice that there are in fact multiple MNI152 templates that you can normalize to. You can grab the specific one that your data has been aligned to from TemplateFlow.

HTH !

Elizabeth