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Merge pull request #1357 from effigies/docs/derivatives_rc
DOC: Update outputs.rst to match Derivatives RC1 changes
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‎docs/links.rst‎

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.. _Nipype: http://nipype.readthedocs.io/en/latest/
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.. _BIDS: http://bids.neuroimaging.io
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.. _`BIDS Derivatives`: https://docs.google.com/document/d/1Wwc4A6Mow4ZPPszDIWfCUCRNstn7d_zzaWPcfcHmgI4/edit
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.. _`BIDS Derivatives`: https://docs.google.com/document/d/17ebopupQxuRwp7U7TFvS6BH03ALJOgGHufxK8ToAvyI
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.. _`BIDS Derivatives RC1`: https://docs.google.com/document/d/17ebopupQxuRwp7U7TFvS6BH03ALJOgGHufxK8ToAvyI
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.. _Usage: usage.html
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.. _Installation: installation.html
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.. _workflows: workflows.html

‎docs/outputs.rst‎

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.. include:: links.rst
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.. _outputs:
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-------------------
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Outputs of FMRIPREP
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Outputs of fMRIPrep
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-------------------
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FMRIPREP generates three broad classes of outcomes:
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FMRIPrep generates three broad classes of outcomes:
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1. **Visual QA (quality assessment) reports**:
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one :abbr:`HTML (hypertext markup language)` per subject,
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between different spaces or the estimated confounds.
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In general, FMRIPREP follows the current working draft of the
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:abbr:`BIDS (brain imaging data structure)`-derivatives extension.
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fMRIPrep outputs conform to the :abbr:`BIDS (brain imaging data structure)`
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Derivatives specification (see `BIDS Derivatives RC1`_).
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Visual Reports
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--------------
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FMRIPREP outputs summary reports, written to ``<output dir>/fmriprep/sub-<subject_label>.html``.
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FMRIPrep outputs summary reports, written to ``<output dir>/fmriprep/sub-<subject_label>.html``.
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These reports provide a quick way to make visual inspection of the results easy.
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Each report is self contained and thus can be easily shared with collaborators (for example via email).
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`View a sample report. <_static/sample_report.html>`_
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Preprocessed data (fMRIPrep *derivatives*)
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------------------------------------------
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There are additional files, called "Derivatives", written to
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``<output dir>/fmriprep/sub-<subject_label>/``. See the
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`BIDS Derivatives <https://docs.google.com/document/d/1Wwc4A6Mow4ZPPszDIWfCUCRNstn7d_zzaWPcfcHmgI4/edit?usp=sharing>`_
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spec for more information.
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Derivatives related to T1w files are in the ``anat`` subfolder:
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- ``*T1w_brainmask.nii.gz`` Brain mask derived using ANTs' ``antsBrainExtraction.sh``.
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- ``*T1w_class-CSF_probtissue.nii.gz``
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- ``*T1w_class-GM_probtissue.nii.gz``
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- ``*T1w_class-WM_probtissue.nii.gz`` tissue-probability maps.
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- ``*T1w_dtissue.nii.gz`` Tissue class map derived using FAST.
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- ``*T1w_preproc.nii.gz`` Bias field corrected T1w file, using ANTS' N4BiasFieldCorrection
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- ``*T1w_space-MNI152NLin2009cAsym_brainmask.nii.gz`` Same as ``_brainmask`` above, but in MNI space.
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- ``*T1w_space-MNI152NLin2009cAsym_class-CSF_probtissue.nii.gz``
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- ``*T1w_space-MNI152NLin2009cAsym_class-GM_probtissue.nii.gz``
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- ``*T1w_space-MNI152NLin2009cAsym_class-WM_probtissue.nii.gz`` Probability tissue maps, transformed into MNI space
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- ``*T1w_space-MNI152NLin2009cAsym_dtissue.nii.gz`` Same as ``_dtissue`` above, but in MNI space
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- ``*T1w_space-MNI152NLin2009cAsym_preproc.nii.gz`` Same as ``_preproc`` above, but in MNI space
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- ``*T1w_space-MNI152NLin2009cAsym_target-T1w_warp.h5`` Composite (warp and affine) transform to map from MNI to T1 space
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- ``*T1w_target-MNI152NLin2009cAsym_warp.h5`` Composite (warp and affine) transform to transform T1w into MNI space
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- (optional) ``*T1w_target-fsnative_affine.txt`` Affine transform to transform T1w into ``fsnative`` space
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- (optional) ``*T1w_smoothwm.[LR].surf.gii`` Smoothed GrayWhite surfaces
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- (optional) ``*T1w_pial.[LR].surf.gii`` Pial surfaces
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- (optional) ``*T1w_midthickness.[LR].surf.gii`` MidThickness surfaces
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- (optional) ``*T1w_inflated.[LR].surf.gii`` FreeSurfer inflated surfaces for visualization
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Derivatives related to EPI files are in the ``func`` subfolder.
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- ``*bold_confounds.tsv`` A tab-separated value file with one column per calculated confound and one row per timepoint/volume
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- (optional) ``*bold_AROMAnoiseICs.csv`` A comma-separated value file listing each MELODIC component classified as noise
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- (optional) ``*bold_MELODICmix.tsv`` A tab-separated value file with one column per MELODIC component
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Preprocessed, or derivative, data are written to
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``<output dir>/fmriprep/sub-<subject_label>/``.
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The `BIDS Derivatives RC1`_ specification describes the naming and metadata conventions we follow.
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Anatomical derivatives are placed in each subject's ``anat`` subfolder:
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- ``anat/sub-<subject_label>_[space-<space_label>_]desc-preproc_T1w.nii.gz``
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- ``anat/sub-<subject_label>_[space-<space_label>_]desc-brain_mask.nii.gz``
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- ``anat/sub-<subject_label>_[space-<space_label>_]dseg.nii.gz``
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- ``anat/sub-<subject_label>_[space-<space_label>_]label-CSF_probseg.nii.gz``
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- ``anat/sub-<subject_label>_[space-<space_label>_]label-GM_probseg.nii.gz``
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- ``anat/sub-<subject_label>_[space-<space_label>_]label-WM_probseg.nii.gz``
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Template-normalized derivatives use the space label ``MNI152NLin2009cAsym``, while derivatives in
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the original ``T1w`` space omit the ``space-`` keyword.
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Additionally, the following transforms are saved:
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- ``anat/sub-<subject_label>_from-MNI152NLin2009cAsym_to-T1w_mode-image_xfm.h5``
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- ``anat/sub-<subject_label>_from-T1w_to-MNI152NLin2009cAsym_mode-image_xfm.h5``
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If FreeSurfer reconstructions are used, the following surface files are generated:
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- ``anat/sub-<subject_label>_hemi-[LR]_smoothwm.surf.gii``
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- ``anat/sub-<subject_label>_hemi-[LR]_pial.surf.gii``
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- ``anat/sub-<subject_label>_hemi-[LR]_midthickness.surf.gii``
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- ``anat/sub-<subject_label>_hemi-[LR]_inflated.surf.gii``
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And the affine translation between ``T1w`` space and FreeSurfer's reconstruction (``fsnative``) is
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stored in:
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- ``anat/sub-<subject_label>_from-T1w_to-fsnative_mode-image_xfm.txt``
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Functional derivatives are stored in the ``func`` subfolder.
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All derivatives contain ``task-<task_label>`` (mandatory) and ``run-<run_index>`` (optional), and
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these will be indicated with ``[specifiers]``.
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- ``func/sub-<subject_label>_[specifiers]_space-<space_label>_boldref.nii.gz``
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- ``func/sub-<subject_label>_[specifiers]_space-<space_label>_desc-brain_mask.nii.gz``
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- ``func/sub-<subject_label>_[specifiers]_space-<space_label>_desc-preproc_bold.nii.gz``
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Volumetric output spaces include ``T1w`` and ``MNI152NLin2009cAsym`` (default).
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- ``*bold_space-<space>_brainmask.nii.gz`` Brain mask for EPI files, calculated by nilearn on the average EPI volume, post-motion correction
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- ``*bold_space-<space>_preproc.nii.gz`` Motion-corrected (using MCFLIRT for estimation and ANTs for interpolation) EPI file
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- (optional) ``*bold_space-<space>_variant-smoothAROMAnonaggr_preproc.nii.gz`` Motion-corrected (using MCFLIRT for estimation and ANTs for interpolation),
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smoothed (6mm), and non-aggressively denoised (using AROMA) EPI file - currently produced only for the ``MNI152NLin2009cAsym`` space
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Confounds are saved as a :abbr:`TSV (tab-separated value)` file:
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- ``func/sub-<subject_label>_[specifiers]_desc-confounds_regressors.nii.gz``
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If FreeSurfer reconstructions are used, the ``(aparc+)aseg`` segmentations are aligned to the
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subject's T1w space and resampled to the BOLD grid, and the BOLD series are resampled to the
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midthickness surface mesh:
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- ``func/sub-<subject_label>_[specifiers]_space-T1w_desc-aparcaseg_dseg.nii.gz``
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- ``func/sub-<subject_label>_[specifiers]_space-T1w_desc-aseg_dseg.nii.gz``
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- ``func/sub-<subject_label>_[specifiers]_space-<space_label>_hemi-[LR].func.gii``
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Surface output spaces include ``fsnative`` (full density subject-specific mesh),
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``fsaverage`` and the down-sampled meshes ``fsaverage6`` (41k vertices) and
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``fsaverage5`` (10k vertices, default).
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- (optional) ``*bold_space-<space>.[LR].func.gii`` Motion-corrected EPI file sampled to surface ``<space>``
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If CIFTI outputs are requested, the BOLD series is also saved as ``dtseries.nii`` CIFTI2 files:
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- ``func/sub-<subject_label>_[specifiers]_bold.dtseries.nii``
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Sub-cortical time series are volumetric (supported spaces: ``MNI152NLin2009cAsym``), while cortical
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time series are sampled to surface (supported spaces: ``fsaverage5``, ``fsaverage6``)
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EPIs can be saved as a CIFTI dtseries file.
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Finally, if ICA-AROMA is used, the MELODIC mixing matrix and the components classified as noise
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are saved:
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- (optional) ``*bold_space-cifti_variant-<variant>_preproc.dtseries.nii`` Motion-corrected EPI converted to CIFTI filetype. Sub-cortical representations
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are volumetric (supported spaces: ``MNI152NLin2009cAsym``), while cortical representations are sampled to surface (supported spaces: ``fsaverage5``, ``fsaverage6``)
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- ``func/sub-<subject_label>_[specifiers]_AROMAnoiseICs.csv``
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- ``func/sub-<subject_label>_[specifiers]_desc-MELODIC_mixing.tsv``
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.. _fsderivs:
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See implementation on :mod:`~fmriprep.workflows.bold.confounds.init_bold_confs_wf`.
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For each :abbr:`BOLD (blood-oxygen level dependent)` run processed with FMRIPREP, a
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``<output_folder>/fmriprep/sub-<sub_id>/func/sub-<sub_id>_task-<task_id>_run-<run_id>_confounds.tsv``
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For each :abbr:`BOLD (blood-oxygen level dependent)` run processed with fMRIPrep, a
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``<output_folder>/fmriprep/sub-<sub_id>/func/sub-<sub_id>_task-<task_id>_run-<run_id>_desc-confounds_regressors.tsv``
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file will be generated.
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These are :abbr:`TSV (tab-separated values)` tables, which look like the example below: ::
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WhiteMatter GlobalSignal stdDVARS non-stdDVARS vx-wisestdDVARS FramewiseDisplacement tCompCor00 tCompCor01 tCompCor02 tCompCor03 tCompCor04 tCompCor05 aCompCor00 aCompCor01 aCompCor02 aCompCor03 aCompCor04 aCompCor05 NonSteadyStateOutlier00 X Y Z RotX RotY RotZ AROMAAggrComp01 AROMAAggrComp03 AROMAAggrComp04 AROMAAggrComp05
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0.63 2.72 n/a n/a n/a n/a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.00 0.00 0.00 0.00 0.00 0.00 0.00 2.62 -1.12 -0.03 3.12
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3.14 0.51 1.18 16.05 1.21 0.07 -0.21 -0.36 -0.23 0.29 -0.37 0.04 -0.33 -0.54 -0.36 0.22 -0.07 0.16 0.00 0.00 0.02 0.05 0.00 0.00 0.00 1.66 -1.74 -0.38 -0.99
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-1.23 -0.85 1.09 14.86 1.11 0.03 0.02 0.04 -0.22 -0.08 -0.18 0.66 0.11 -0.45 -0.16 -0.28 -0.05 0.26 0.00 0.00 0.00 0.05 0.00 0.00 0.00 0.35 -1.22 0.10 -0.23
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-1.61 -1.53 1.01 13.83 1.05 0.03 0.27 0.21 -0.07 0.21 0.30 -0.02 0.24 -0.15 0.24 0.17 0.51 -0.02 0.00 0.01 -0.01 0.04 0.00 0.00 0.00 -0.42 -0.55 0.49 -0.38
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-3.43 -1.48 0.98 13.32 1.02 0.03 0.06 0.49 0.24 -0.18 0.06 0.12 0.25 0.11 0.09 -0.10 0.08 0.47 0.00 0.02 -0.01 0.03 0.00 0.00 0.00 -1.12 -0.40 0.21 1.23
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0.71 -0.66 0.97 13.26 1.02 0.04 -0.29 0.43 0.14 0.06 -0.20 -0.32 0.40 0.22 -0.07 0.45 -0.02 -0.04 0.00 0.02 -0.02 0.03 0.00 0.00 0.00 -1.00 -0.91 -0.99 0.30
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-2.81 0.61 0.95 12.98 1.01 0.08 -0.48 0.24 -0.11 -0.15 -0.16 -0.22 0.38 0.20 -0.35 0.16 -0.31 -0.01 0.00 0.00 0.00 0.05 0.00 0.00 0.00 -0.66 -0.49 -1.89 0.43
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2.85 0.35 0.95 12.99 1.01 0.04 -0.22 0.00 -0.50 0.05 0.15 0.14 0.30 -0.20 -0.22 -0.22 0.04 -0.34 0.00 0.00 -0.01 0.03 0.00 0.00 0.00 0.01 0.22 -1.76 -0.39
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-2.57 -0.54 1.04 14.22 1.07 0.05 0.45 0.01 -0.43 -0.51 -0.01 -0.20 0.13 -0.02 0.26 -0.62 0.00 -0.30 0.00 0.00 0.00 0.06 0.00 0.00 0.00 0.60 1.59 0.05 -0.46
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3.41 -0.72 1.03 14.04 1.05 0.07 0.37 0.06 0.08 0.55 -0.21 -0.14 -0.10 -0.18 0.51 0.17 -0.24 0.05 0.00 0.00 0.02 0.07 0.00 0.00 0.00 0.52 0.71 1.63 -0.95
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3.75 -0.54 1.01 13.83 1.04 0.06 0.16 -0.16 0.38 -0.19 -0.01 0.16 -0.11 0.18 0.37 0.00 -0.43 0.20 0.00 0.00 0.00 0.06 0.00 0.00 0.00 -0.53 -0.07 1.85 -0.01
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0.41 1.19 1.05 14.28 1.08 0.06 -0.27 -0.38 0.32 -0.11 0.10 0.07 -0.31 0.31 -0.25 -0.24 -0.01 0.27 0.00 0.00 0.01 0.09 0.00 0.00 0.00 -0.75 -0.03 0.14 -0.26
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-4.14 0.72 0.97 13.20 1.01 0.03 -0.13 -0.28 0.03 -0.16 0.48 -0.28 -0.26 0.40 -0.24 -0.10 0.18 -0.20 0.00 0.00 0.00 0.08 0.00 0.00 0.00 -0.44 1.03 -0.50 -0.15
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2.21 -0.02 0.96 13.09 1.00 0.01 0.18 -0.26 -0.04 0.14 -0.05 -0.37 -0.26 -0.10 0.07 0.25 -0.10 -0.54 0.00 0.00 0.00 0.08 0.00 0.00 0.00 0.28 1.54 0.12 -0.77
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0.08 -0.06 0.95 12.89 0.99 0.01 0.15 -0.12 0.31 -0.22 -0.37 0.08 -0.22 0.12 -0.02 0.01 -0.15 -0.10 0.00 0.00 0.00 0.08 0.00 0.00 0.00 -0.46 1.00 0.70 0.08
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-1.41 0.29 0.96 13.06 0.99 0.01 -0.04 0.07 0.10 0.31 0.47 0.27 -0.22 0.09 0.11 0.12 0.56 0.14 0.00 0.00 0.00 0.07 0.00 0.00 0.00 -0.67 0.44 0.25 -0.57
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csf white_matter global_signal std_dvars dvars framewise_displacement t_comp_cor_00 t_comp_cor_01 t_comp_cor_02 t_comp_cor_03 t_comp_cor_04 t_comp_cor_05 a_comp_cor_00 a_comp_cor_01 a_comp_cor_02 a_comp_cor_03 a_comp_cor_04 a_comp_cor_05 non_steady_state_outlier00 trans_x trans_y trans_z rot_x rot_y rot_z aroma_motion_02 aroma_motion_04
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682.75275 0.0 491.64752000000004 n/a n/a n/a 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 -0.00017029 -0.0 0.0 0.0 0.0
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669.14166 0.0 489.4421 1.168398 17.575331 0.07211929999999998 -0.4506846719 0.1191909139 -0.0945884724 0.1542023065 -0.2302324641 0.0838194238 -0.032426848599999995 0.4284323184 -0.5809158299 0.1382414008 -0.1203486637 0.3783661265 0.0 0.0 0.0207752 0.0463124 -0.000270924 -0.0 0.0 -2.402958171 -0.7574011893
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665.3969 0.0 488.03 1.085204 16.323903999999995 0.0348966 0.010819676200000001 0.0651895837 -0.09556632150000001 -0.033148835 -0.4768871111 0.20641088559999998 0.2818768463 0.4303863764 0.41323714850000004 -0.2115232212 -0.0037154909000000004 0.10636180070000001 0.0 0.0 0.0 0.0457372 0.0 -0.0 0.0 -1.341359143 0.1636017242
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662.82715 0.0 487.37302 1.01591 15.281561 0.0333937 0.3328022893 -0.2220965269 -0.0912891436 0.2326688125 0.279138129 -0.111878887 0.16901660629999998 0.0550480212 0.1798747037 -0.25383302620000003 0.1646403629 0.3953613889 0.0 0.010164 -0.0103568 0.0424513 0.0 -0.0 0.00019174 -0.1554834655 0.6451987913
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Each row of the file corresponds to one time point found in the
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corresponding :abbr:`BOLD (blood-oxygen level dependent)` time-series
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(stored in ``<output_folder>/fmriprep/sub-<sub_id>/func/sub-<sub_id>_task-<task_id>_run-<run_id>_bold_preproc.nii.gz``).
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Columns represent the different confounds: ``CSF`` and ``WhiteMatter`` are the average signal inside
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the :abbr:`CSF (cerebro-spinal fluid)` and :abbr:`WM (white matter)` mask across time;
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``GlobalSignal`` corresponds to the global-signal within the whole-brain mask; three columns relate to the
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derivative of RMS variance over voxels (or :abbr:`DVARS (D referring to difference, )`) that can be
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standardized (``stdDVARS``), non-standardized (``non-stdDVARS``), and voxel-wise standardized (``vx-wisestdDVARS``);
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the ``FrameDisplacement`` is a quantification of the estimated bulk-head motion; ``X``, ``Y``, ``Z``, ``RotX``,
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``RotY``, ``RotZ`` are the actual 6 rigid-body transform parameters estimated by FMRIPREP;
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the ``NonSteadyStateOutlierXX`` columns indicate non-steady state volumes with a single ``1`` value and ``0`` elsewhere (there
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is one ``NonSteadyStateOutlierXX`` column per outlier/volume); and finally six noise components ``aCompCorXX`` calculated using
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:abbr:`CompCor (Component Based Noise Correction Method)`
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and five noise components ``AROMAaggrCompXX`` if
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:abbr:`ICA (independent components analysis)`-:abbr:`AROMA (Automatic Removal Of Motion Artifacts)` was enabled.
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(stored in ``<output_folder>/fmriprep/sub-<sub_id>/func/sub-<sub_id>_task-<task_id>_run-<run_id>_desc-preproc_bold.nii.gz``).
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Columns represent the different confounds: ``csf`` and ``white_matter`` are the average signal
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inside the anatomically-derived :abbr:`CSF (cerebro-spinal fluid)` and :abbr:`WM (white matter)`
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masks across time;
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``global_signal`` corresponds to the mean time series within the brain mask; two columns relate to
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the derivative of RMS variance over voxels (or :abbr:`DVARS (defined in Power, et al. 2012)`), and
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both the original (``dvars``) and standardized (``std_dvars``) are provided;
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``framewise_displacement`` is a quantification of the estimated bulk-head motion;
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``trans_x``, ``trans_y``, ``trans_z``, ``rot_x``, ``rot_y``, ``rot_z`` are the 6 rigid-body
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motion-correction parameters estimated by fMRIPrep;
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if present, ``non_steady_state_outlier_XX`` columns indicate non-steady state volumes with a single
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``1`` value and ``0`` elsewhere (*i.e.*, there is one ``non_steady_state_outlier_XX`` column per
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outlier/volume);
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six noise components are calculated using :abbr:`CompCor (Component Based Noise Correction)`,
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according to both the anatomical (``a_comp_cor_XX``) and temporal (``t_comp_cor_XX``) variants;
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and the motion-related components identified by
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:abbr:`ICA (independent components analysis)`-:abbr:`AROMA (Automatic Removal Of Motion Artifacts)`
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(if enabled) are indicated with ``aroma_motioon_XX``.
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All these confounds can be used to perform *scrubbing* and *censoring* of outliers,
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in the subsequent first-level analysis when building the design matrix,

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