nipreps · effigies · Apr 10, 2023 · Mar 12, 2023
diff --git a/.circleci/config.yml b/.circleci/config.yml
@@ -551,7 +551,6 @@ jobs:
             mkdir -p /tmp/${DATASET}/derivatives_partial
             sudo cp -a /tmp/${DATASET}/work /tmp/${DATASET}/work_partial
             sudo cp -a /tmp/${DATASET}/work /tmp/${DATASET}/work_bids
-            sudo rm -rf /tmp/${DATASET}/work_partial/fmriprep_*_wf/single_subject_01_wf/func_preproc_task_mixedgamblestask_run_02_wf/ica_aroma_wf
             # Nipype sometimes fails to pick up when the base directory changes
             # This is a cheap workflow, so let's not fuss
             sudo rm -rf /tmp/${DATASET}/work /tmp/${DATASET}/work_bids/fmriprep_*_wf/single_subject_01_wf/anat_preproc_wf/surface_recon_wf/gifti_surface_wf || true
@@ -608,7 +607,6 @@ jobs:
                 --output-layout legacy \
                 --sloppy --write-graph --use-syn-sdc --mem-mb 14336 \
                 --output-spaces MNI152NLin2009cAsym fsaverage5 fsnative MNI152NLin6Asym anat \
-                --aroma-melodic-dimensionality 2 --use-aroma \
                 --nthreads 4 --cifti-output --project-goodvoxels -vv
       - store_artifacts:
           path: /tmp/ds005/derivatives_partial

diff --git a/.circleci/ds005_legacy_partial_fasttrack_outputs.txt b/.circleci/ds005_legacy_partial_fasttrack_outputs.txt
@@ -17,11 +17,9 @@ fmriprep/sub-01/fmap/sub-01_run-02_fmapid-auto00000_desc-magnitude_fieldmap.nii.
 fmriprep/sub-01/fmap/sub-01_run-02_fmapid-auto00000_desc-preproc_fieldmap.json
 fmriprep/sub-01/fmap/sub-01_run-02_fmapid-auto00000_desc-preproc_fieldmap.nii.gz
 fmriprep/sub-01/func
-fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_AROMAnoiseICs.csv
 fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_boldref.nii.gz
 fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_desc-confounds_timeseries.json
 fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_desc-confounds_timeseries.tsv
-fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_desc-MELODIC_mixing.tsv
 fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_from-scanner_to-boldref_mode-image_xfm.txt
 fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_from-scanner_to-T1w_mode-image_xfm.txt
 fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_from-T1w_to-scanner_mode-image_xfm.txt
@@ -49,8 +47,6 @@ fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_space-MNI152NLin6Asym_d
 fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_space-MNI152NLin6Asym_desc-brain_mask.nii.gz
 fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_space-MNI152NLin6Asym_desc-preproc_bold.json
 fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz
-fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_space-MNI152NLin6Asym_desc-smoothAROMAnonaggr_bold.json
-fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_space-MNI152NLin6Asym_desc-smoothAROMAnonaggr_bold.nii.gz
 fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_space-T1w_boldref.nii.gz
 fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_space-T1w_desc-aparcaseg_dseg.nii.gz
 fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_space-T1w_desc-aseg_dseg.nii.gz

diff --git a/.circleci/ds005_legacy_partial_outputs.txt b/.circleci/ds005_legacy_partial_outputs.txt
@@ -71,11 +71,9 @@ fmriprep/sub-01/fmap/sub-01_run-02_fmapid-auto00000_desc-magnitude_fieldmap.nii.
 fmriprep/sub-01/fmap/sub-01_run-02_fmapid-auto00000_desc-preproc_fieldmap.json
 fmriprep/sub-01/fmap/sub-01_run-02_fmapid-auto00000_desc-preproc_fieldmap.nii.gz
 fmriprep/sub-01/func
-fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_AROMAnoiseICs.csv
 fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_boldref.nii.gz
 fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_desc-confounds_timeseries.json
 fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_desc-confounds_timeseries.tsv
-fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_desc-MELODIC_mixing.tsv
 fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_from-scanner_to-boldref_mode-image_xfm.txt
 fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_from-scanner_to-T1w_mode-image_xfm.txt
 fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_from-T1w_to-scanner_mode-image_xfm.txt
@@ -103,8 +101,6 @@ fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_space-MNI152NLin6Asym_d
 fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_space-MNI152NLin6Asym_desc-brain_mask.nii.gz
 fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_space-MNI152NLin6Asym_desc-preproc_bold.json
 fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_space-MNI152NLin6Asym_desc-preproc_bold.nii.gz
-fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_space-MNI152NLin6Asym_desc-smoothAROMAnonaggr_bold.json
-fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_space-MNI152NLin6Asym_desc-smoothAROMAnonaggr_bold.nii.gz
 fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_space-T1w_boldref.nii.gz
 fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_space-T1w_desc-aparcaseg_dseg.nii.gz
 fmriprep/sub-01/func/sub-01_task-mixedgamblestask_run-02_space-T1w_desc-aseg_dseg.nii.gz

diff --git a/.vscode/launch.json b/.vscode/launch.json
@@ -34,7 +34,6 @@
                 "/tmp/ds005/derivatives",
                 "participant",
                 "--sloppy", "--write-graph",
-                "--use-aroma",
                 "--skull-strip-template", "OASIS30ANTs:res-1",
                 "--output-space", "T1w", "template", "fsaverage5", "fsnative",
                 "--template-resampling-grid",  "native",
@@ -98,4 +97,4 @@
             "justMyCode": false
         }
     ]
-}
+}
diff --git a/Dockerfile b/Dockerfile
@@ -223,14 +223,6 @@ WORKDIR $ANTSPATH
 RUN curl -sSL "https://dl.dropbox.com/s/gwf51ykkk5bifyj/ants-Linux-centos6_x86_64-v2.3.4.tar.gz" \
     | tar -xzC $ANTSPATH --strip-components 1
 
-# Installing and setting up ICA_AROMA
-WORKDIR /opt/ICA-AROMA
-RUN curl -sSL "https://github.com/oesteban/ICA-AROMA/archive/v0.4.5.tar.gz" \
-  | tar -xzC /opt/ICA-AROMA --strip-components 1 && \
-  chmod +x /opt/ICA-AROMA/ICA_AROMA.py
-ENV PATH="/opt/ICA-AROMA:$PATH" \
-    AROMA_VERSION="0.4.5"
-
 WORKDIR /opt
 RUN curl -sSLO https://www.humanconnectome.org/storage/app/media/workbench/workbench-linux64-v1.5.0.zip && \
     unzip workbench-linux64-v1.5.0.zip && \

diff --git a/REFERENCES.md b/REFERENCES.md
@@ -17,7 +17,6 @@
 | MCFLIRT | https://doi.org/10.1006/nimg.2002.1132 | https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/MCFLIRT |
 | SUSAN | https://doi.org/10.1023/A:1007963824710 | https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/SUSAN |
 | MELODIC | | https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/MELODIC |
-| ICA-AROMA | http://www.sciencedirect.com/science/article/pii/S1053811915001822 | https://github.com/rhr-pruim/ICA-AROMA/ |
 | PRELUDE & FUGUE | https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FUGUE/Guide | https://nipype.readthedocs.io/en/latest/interfaces/generated/workflows.dmri/fsl.utils.html#cleanup-edge-pipeline |
 | **AFNI** | | https://doi.org/10.1006/cbmr.1996.0014; https://doi.org/10.1016/j.neuroimage.2011.08.056
 | 3dvolreg | | https://afni.nimh.nih.gov/pub/dist/doc/program_help/3dvolreg.html |

diff --git a/docs/_static/sbatch.slurm b/docs/_static/sbatch.slurm
@@ -40,7 +40,7 @@ subject=$( sed -n -E "$((${SLURM_ARRAY_TASK_ID} + 1))s/sub-(\S*)\>.*/\1/gp" ${BI
 find ${LOCAL_FREESURFER_DIR}/sub-$subject/ -name "*IsRunning*" -type f -delete
 
 # Compose the command line
-cmd="${SINGULARITY_CMD} /data /data/${DERIVS_DIR} participant --participant-label $subject -w /work/ -vv --omp-nthreads 8 --nthreads 12 --mem_mb 30000 --output-spaces MNI152NLin2009cAsym:res-2 anat fsnative fsaverage5 --use-aroma --fs-subjects-dir /fsdir"
+cmd="${SINGULARITY_CMD} /data /data/${DERIVS_DIR} participant --participant-label $subject -w /work/ -vv --omp-nthreads 8 --nthreads 12 --mem_mb 30000 --output-spaces MNI152NLin2009cAsym:res-2 anat fsnative fsaverage5 --fs-subjects-dir /fsdir"
 
 # Setup done, run the command
 echo Running task ${SLURM_ARRAY_TASK_ID}

diff --git a/docs/faq.rst b/docs/faq.rst
@@ -202,7 +202,7 @@ In addition to the ``--output-spaces`` that you specify, *fMRIPrep* will
 internally require the ``MNI152NLin2009cAsym`` template.
 If the ``--skull-strip-template`` option is not set, then ``OASIS30ANTs``
 will be used.
-Finally, both the ``--cifti-output`` and ``--use-aroma`` arguments require ``MNI152NLin6Asym``.
+Finally, the ``--cifti-output`` argument requires ``MNI152NLin6Asym``.
 To do so, follow the next steps.
 
 1. By default, a mirror of *TemplateFlow* to store the resources will be

diff --git a/docs/installation.rst b/docs/installation.rst
@@ -80,7 +80,6 @@ the ``fmriprep`` package:
 - AFNI_ (version 22.3.06)
 - `C3D <https://sourceforge.net/projects/c3d/>`_ (version 1.3.0)
 - FreeSurfer_ (version 7.3.2)
-- `ICA-AROMA <https://github.com/maartenmennes/ICA-AROMA/archive/v0.4.5.tar.gz>`_ (version 0.4.5)
 - `bids-validator <https://github.com/bids-standard/bids-validator>`_ (version 1.8.0)
 - `connectome-workbench <https://www.humanconnectome.org/software/connectome-workbench>`_ (version 1.5.0)
 

diff --git a/docs/outputs.rst b/docs/outputs.rst
@@ -30,10 +30,9 @@ upcoming `BEP 011`_ and `BEP 012`_).
    .. important::
        In order to remain agnostic to any possible subsequent analysis,
        *fMRIPrep* does not perform any denoising (e.g., spatial smoothing) itself.
-       There are two exceptions to this principle (described in their corresponding
-       sections below):
+       There are exceptions to this principle (described in its corresponding
+       section below):
 
-       - ICA-AROMA's *non-aggressive* denoised outputs, and
        - CompCor regressors, which are calculated after temporal high-pass filtering.
 
 Layout
@@ -228,19 +227,11 @@ These :abbr:`TSV (tab-separated values)` tables look like the example below,
 where each row of the file corresponds to one time point found in the
 corresponding :abbr:`BOLD (blood-oxygen level dependent)` time series::
 
-  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
-  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
-  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
-  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
-  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
-
-Finally, if ICA-AROMA is used, the MELODIC mixing matrix and the components classified as noise
-are saved::
-
-  sub-<subject_label>/
-    func/
-      sub-<subject_label>_[specifiers]_AROMAnoiseICs.csv
-      sub-<subject_label>_[specifiers]_desc-MELODIC_mixing.tsv
+  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
+  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
+  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
+  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
+  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
 
 **Multi-echo derivatives**.
 For multi-echo datasets, the output ``_bold`` series are "optimally combined" by
@@ -529,31 +520,6 @@ the brain's outer edge (*crown*) mask.
 The procedure essentially follows the initial proposal of the approach by Patriat et al.
 [Patriat2017]_ and is described in our ISMRM abstract [Provins2022]_.
 
-**AROMA confounds**.
-:abbr:`AROMA (Automatic Removal Of Motion Artifacts)` is an :abbr:`ICA (independent components analysis)`
-based procedure to identify confounding time series related to head-motion [Prium2015]_.
-ICA-AROMA can be enabled with the flag ``--use-aroma``.
-
-- ``aroma_motion_XX`` - the motion-related components identified by ICA-AROMA.
-
-.. danger::
-    If you are already using AROMA-cleaned data (``~desc-smoothAROMAnonaggr_bold.nii.gz``),
-    do not include ICA-AROMA confounds during your design specification or denoising procedure.
-
-    Additionally, as per [Hallquist2013]_ and [Lindquist2019]_, when using AROMA-cleaned data
-    most of the confound regressors should be recalculated (this feature is a work-in-progress,
-    follow up on `#1905 <https://github.com/nipreps/fmriprep/issues/1905>`__).
-    Surprisingly, `our simulations
-    <https://github.com/nipreps/fmriprep-notebooks/blob/9933a628dfb759dc73e61701c144d67898b92de0/05%20-%20Discussion%20AROMA%20confounds%20-%20issue-817%20%5BJ.%20Kent%5D.ipynb>`__
-    (with thanks to JD. Kent) suggest that using the confounds as currently calculated by
-    *fMRIPrep* --before denoising-- would be just fine.
-
-.. caution::
-    *Nonsteady-states* (or *dummy scans*) in the beginning of every run
-    are dropped **before** ICA-AROMA is performed.
-    Therefore, any subsequent analysis of ICA-AROMA outputs must drop the same
-    number of *nonsteady-states*.
-
 Confounds and "carpet"-plot on the visual reports
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 The visual reports provide several sections per task and run to aid designing
@@ -698,11 +664,6 @@ the following invocation::
   .. [Power2016] Power JD, A simple but useful way to assess fMRI scan qualities. NeuroImage. 2016.
      doi:`10.1016/j.neuroimage.2016.08.009 <http://doi.org/10.1016/j.neuroimage.2016.08.009>`_
 
-  .. [Prium2015] Pruim RHR, Mennes M, van Rooij D, Llera A, Buitelaar JK, Beckmann CF.
-     ICA-AROMA: A robust ICA-based strategy for removing motion artifacts from fMRI data.
-     Neuroimage. 2015 May 15;112:267–77.
-     doi:`10.1016/j.neuroimage.2015.02.064 <https://doi.org/10.1016/j.neuroimage.2015.02.064>`_.
-
   .. [Provins2022] Provins C et al., Quality control and nuisance regression of fMRI, looking out
      where signal should not be found. Proc. Intl. Soc. Mag. Reson. Med. 31, London (UK). 2022
      doi:`10.31219/osf.io/hz52v <https://doi.org/10.31219/osf.io/hz52v>`_.

diff --git a/docs/spaces.rst b/docs/spaces.rst
@@ -138,11 +138,11 @@ Modifiers are not allowed when providing nonstandard spaces.
 
 Preprocessing blocks depending on standard templates
 """"""""""""""""""""""""""""""""""""""""""""""""""""
-Some modules of the pipeline (e.g., the ICA-AROMA denoising, the generation of
-HCP compatible *grayordinates* files, or the *fieldmap-less* distortion correction)
+Some modules of the pipeline (e.g., the generation of HCP compatible
+*grayordinates* files, or the *fieldmap-less* distortion correction)
 operate in specific template spaces.
 When selecting those modules to be included (using any of the following flags:
-``--use-aroma``, ``--cifti-outputs``, ``--use-syn-sdc``) will modify the list of
+``--cifti-outputs``, ``--use-syn-sdc``) will modify the list of
 *internal* spaces to include the space identifiers they require, should the
 identifier not be found within the ``--output-spaces`` list already.
 In other words, running *fMRIPrep* with ``--output-spaces MNI152NLin6Asym:res-2

diff --git a/docs/usage.rst b/docs/usage.rst
@@ -180,7 +180,7 @@ Because processing this emerging type of datasets (*densely sampled neuroimaging
 
 .. attention::
     When the intention is to combine the *anatomical fast-track* with some advanced options that involve
-    standard spaces (e.g., ``--use-aroma`` or ``--cifti-output``), please make sure you include the
+    standard spaces (e.g., ``--cifti-output``), please make sure you include the
     ``MNI152NLin6Asym`` space to the ``--output-spaces`` list in the first invocation of *fMRIPrep*
     (or *sMRIPrep*) from which the results are to be reused.
     Otherwise, a warning message indicating that *fMRIPrep*'s expectations were not met will be issued,

diff --git a/docs/workflows.rst b/docs/workflows.rst
@@ -567,56 +567,8 @@ segmentation, the `discover_wf` sub-workflow calculates potential
 confounds per volume.
 
 Calculated confounds include the mean global signal, mean tissue class signal,
-tCompCor, aCompCor, Frame-wise Displacement, 6 motion parameters, DVARS, spike regressors,
-and, if the ``--use-aroma`` flag is enabled, the noise components identified by ICA-AROMA
-(those to be removed by the "aggressive" denoising strategy).
-Particular details about ICA-AROMA are given below.
-
-ICA-AROMA
-~~~~~~~~~
-:py:func:`~fmriprep.workflows.bold.confounds.init_ica_aroma_wf`
-
-ICA-AROMA denoising is performed in ``MNI152NLin6Asym`` space, which is automatically
-added to the list of ``--output-spaces`` if it was not already requested by the user.
-The number of ICA-AROMA components depends on a dimensionality estimate made by
-FSL MELODIC.
-For datasets with a very short TR and a large number of timepoints, this may result
-in an unusually high number of components.
-By default, dimensionality is limited to a maximum of 200 components.
-To override this upper limit one may specify the number of components to be extracted
-with ``--aroma-melodic-dimensionality``.
-Further details on the implementation are given within the workflow generation
-function (:py:func:`~fmriprep.workflows.bold.confounds.init_ica_aroma_wf`).
-
-*Note*: *non*-aggressive AROMA denoising is a fundamentally different procedure
-from its "aggressive" counterpart and cannot be performed only by using a set of noise
-regressors (a separate GLM with both noise and signal regressors needs to be used).
-Therefore instead of regressors, *fMRIPrep* produces *non*-aggressive denoised 4D NIFTI
-files in the MNI space:
-
-``*space-MNI152NLin6Asym_desc-smoothAROMAnonaggr_bold.nii.gz``
-
-Additionally, the MELODIC mix and noise component indices will
-be generated, so non-aggressive denoising can be manually performed in the T1w space with ``fsl_regfilt``, *e.g.*::
-
-    fsl_regfilt -i sub-<subject_label>_task-<task_id>_space-T1w_desc-preproc_bold.nii.gz \
-        -f $(cat sub-<subject_label>_task-<task_id>_AROMAnoiseICs.csv) \
-        -d sub-<subject_label>_task-<task_id>_desc-MELODIC_mixing.tsv \
-        -o sub-<subject_label>_task-<task_id>_space-T1w_desc-AROMAnonaggr_bold.nii.gz
-
-*Note*: The non-steady state volumes are removed for the determination of components in melodic.
-Therefore ``*MELODIC_mixing.tsv`` may have zero padded rows to account for the volumes not used in
-melodic's estimation of components.
-
-A visualization of the AROMA component classification is also included in the HTML reports.
-
-.. figure:: _static/aroma.svg
-
-    Maps created with maximum intensity projection (glass brain) with a black
-    brain outline.
-    Right hand side of each map: time series (top in seconds),
-    frequency spectrum (bottom in Hertz).
-    Components classified as signal in green; noise in red.
+tCompCor, aCompCor, Frame-wise Displacement, 6 motion parameters, DVARS, and
+spike regressors.
 
 .. _bold_t2s: