<commit_before>package: niworkflows
sections:
- name: Summary
  reportlets:
  - bids: {datatype: anat, desc: summary, suffix: T1w}
- name: Anatomical
  reportlets:
  - bids:
      datatype: anat
      desc: conform
      extensions: [.html]
      suffix: T1w
  - bids: {datatype: anat, suffix: dseg}
    caption: This panel shows the template T1-weighted image (if several T1w images
      were found), with contours delineating the detected brain mask and brain tissue
      segmentations.
    subtitle: Brain mask and brain tissue segmentation of the T1w
  - bids: {datatype: anat, space: .*, suffix: T1w}
    caption: Spatial normalization of the T1w image to the <code>{space}</code> template.
    description: Results of nonlinear alignment of the T1w reference one or more template
      space(s). Hover on the panels with the mouse pointer to transition between both
      spaces.
    subtitle: Spatial normalization of the anatomical T1w reference
  - bids: {datatype: anat, desc: reconall, suffix: T1w}
    caption: Surfaces (white and pial) reconstructed with FreeSurfer (<code>recon-all</code>)
      overlaid on the participant's T1w template.
    subtitle: Surface reconstruction
- name: Fieldmaps
  ordering: session
  reportlets:
  - bids: {datatype: fmap, desc: brain, suffix: mask}
    caption: Brain extraction of the magnitude image from the fieldmap
    subtitle: Skull stripped magnitude image
- name: Functional
  ordering: session,task,run
  reportlets:
  - bids: {datatype: func, desc: summary, suffix: bold}
  - bids: {datatype: func, desc: validation, suffix: bold}
  - bids: {datatype: func, desc: magnitude, suffix: bold}
    caption: Results of affine coregistration between the magnitude image of the fieldmap
      and the reference EPI image
    subtitle: Fieldmap to EPI registration
  - bids: {datatype: func, desc: fieldmap, suffix: bold}
    caption: Overlaid on the reference EPI image
    subtitle: Fieldmap
  - bids: {datatype: func, desc: sdc, suffix: bold}
    caption: Results of performing susceptibility distortion correction (SDC) on the
      EPI
    subtitle: Susceptibility distortion correction
  - bids: {datatype: func, desc: forcedsyn, suffix: bold}
    caption: The dataset contained some fieldmap information, but the argument <code>--force-syn</code>
      was used. The higher-priority SDC method was used. Here, we show the results
      of performing SyN-based SDC on the EPI for comparison.
    subtitle: Experimental fieldmap-less susceptibility distortion correction
  - bids: {datatype: func, desc: rois, suffix: bold}
    caption: Brain mask calculated on the BOLD signal (red contour), along with the
      masks used for a/tCompCor.<br />The aCompCor mask (magenta contour) is a conservative
      CSF and white-matter mask for extracting physiological and movement confounds.
      <br />The fCompCor mask (blue contour) contains the top 5% most variable voxels
      within a heavily-eroded brain-mask.
    subtitle: ROIs in BOLD space
  - bids:
      datatype: func
      desc: '[at]compcor'
      extensions: [.html]
      suffix: bold
  - bids: {datatype: func, desc: flirtnobbr, suffix: bold}
    caption: FSL <code>flirt</code> was used to generate transformations from EPI
      space to T1 Space - BBR refinement rejected. Note that Nearest Neighbor interpolation
      is used in the reportlets in order to highlight potential spin-history and other
      artifacts, whereas final images are resampled using Lanczos interpolation.
    subtitle: EPI to T1 registration
  - bids: {datatype: func, desc: coreg, suffix: bold}
    caption: <code>mri_coreg</code> (FreeSurfer) was used to generate transformations
      from EPI space to T1 Space - <code>bbregister</code> refinement rejected. Note
      that Nearest Neighbor interpolation is used in the reportlets in order to highlight
      potential spin-history and other artifacts, whereas final images are resampled
      using Lanczos interpolation.
    subtitle: EPI to T1 registration
  - bids: {datatype: func, desc: flirtbbr, suffix: bold}
    caption: FSL <code>flirt</code> was used to generate transformations from EPI-space
      to T1w-space - The white matter mask calculated with FSL <code>fast</code> (brain
      tissue segmentation) was used for BBR. Note that Nearest Neighbor interpolation<commit_msg>fix(reports): Add new confounds model to reports template<commit_after>package: niworkflows
sections:
- name: Summary
  reportlets:
  - bids: {datatype: anat, desc: summary, suffix: T1w}
- name: Anatomical
  reportlets:
  - bids:
      datatype: anat
      desc: conform
      extensions: [.html]
      suffix: T1w
  - bids: {datatype: anat, suffix: dseg}
    caption: This panel shows the template T1-weighted image (if several T1w images
      were found), with contours delineating the detected brain mask and brain tissue
      segmentations.
    subtitle: Brain mask and brain tissue segmentation of the T1w
  - bids: {datatype: anat, space: .*, suffix: T1w}
    caption: Spatial normalization of the T1w image to the <code>{space}</code> template.
    description: Results of nonlinear alignment of the T1w reference one or more template
      space(s). Hover on the panels with the mouse pointer to transition between both
      spaces.
    subtitle: Spatial normalization of the anatomical T1w reference
  - bids: {datatype: anat, desc: reconall, suffix: T1w}
    caption: Surfaces (white and pial) reconstructed with FreeSurfer (<code>recon-all</code>)
      overlaid on the participant's T1w template.
    subtitle: Surface reconstruction
- name: Fieldmaps
  ordering: session
  reportlets:
  - bids: {datatype: fmap, desc: brain, suffix: mask}
    caption: Brain extraction of the magnitude image from the fieldmap
    subtitle: Skull stripped magnitude image
- name: Functional
  ordering: session,task,run
  reportlets:
  - bids: {datatype: func, desc: summary, suffix: bold}
  - bids: {datatype: func, desc: validation, suffix: bold}
  - bids: {datatype: func, desc: magnitude, suffix: bold}
    caption: Results of affine coregistration between the magnitude image of the fieldmap
      and the reference EPI image
    subtitle: Fieldmap to EPI registration
  - bids: {datatype: func, desc: fieldmap, suffix: bold}
    caption: Overlaid on the reference EPI image
    subtitle: Fieldmap
  - bids: {datatype: func, desc: sdc, suffix: bold}
    caption: Results of performing susceptibility distortion correction (SDC) on the
      EPI
    subtitle: Susceptibility distortion correction
  - bids: {datatype: func, desc: forcedsyn, suffix: bold}
    caption: The dataset contained some fieldmap information, but the argument <code>--force-syn</code>
      was used. The higher-priority SDC method was used. Here, we show the results
      of performing SyN-based SDC on the EPI for comparison.
    subtitle: Experimental fieldmap-less susceptibility distortion correction
  - bids: {datatype: func, desc: rois, suffix: bold}
    caption: Brain mask calculated on the BOLD signal (red contour), along with the
      masks used for a/tCompCor.<br />The aCompCor mask (magenta contour) is a conservative
      CSF and white-matter mask for extracting physiological and movement confounds.
      <br />The fCompCor mask (blue contour) contains the top 5% most variable voxels
      within a heavily-eroded brain-mask.
    subtitle: ROIs in BOLD space
  - bids:
      datatype: func
      desc: '[at]compcor'
      extensions: [.html]
      suffix: bold
  - bids: {datatype: func, desc: '[at]compcorvar', suffix: bold}
    caption: The cumulative variance explained by the first k components of the
      <em>t/aCompCor</em> decomposition, plotted for all values of <em>k</em>.
      The number of components that must be included in the model in order to
      explain some fraction of variance in the decomposition mask can be used
      as a feature selection criterion for confound regression.
  - bids: {datatype: func, desc: 'confoundcorr', suffix: bold}
    caption: |
      Left: Heatmap summarizing the correlation structure among confound variables.
      (Cosine bases and PCA-derived CompCor components are inherently orthogonal.)
      Right: magnitude of the correlation between each confound time series and the
      mean global signal. Strong correlations might be indicative of partial volume
      effects and can inform decisions about feature orthogonalization prior to 
      confound regression.
    subtitle: Correlations among nuisance regressors
  - bids: {datatype: func, desc: flirtnobbr, suffix: bold}
    caption: FSL <code>flirt</code> was used to generate transformations from EPI
      space to T1 Space - BBR refinement rejected. Note that Nearest Neighbor interpolation
      is used in the reportlets in order to highlight potential spin-history and other
      artifacts, whereas final images are resampled using Lanczos interpolation.
    subtitle: EPI to T1 registration
  - bids: {datatype: func, desc: coreg, suffix: bold}
    caption: <code>mri_coreg</code> (FreeSurfer) was used to generate transformations
      from EPI space to T1 Space - <code>bbregister</code> refinement rejected. Note
      that Nearest Neighbor interpolation is used in the reportlets in order to highlight
      potential spin-history and other artifacts, whereas final images are resampled
      using Lanczos interpolation.
    subtitle: EPI to T1 registration
  - bids: {datatype: func, desc: flirtbbr, suffix: bold}
    caption: FSL <code>flirt</code> was used to generate transformations from EPI-space
      to T1w-space - The white matter mask calculated with FSL <code>fast</code> (brain
      tissue segmentation) was used for BBR. Note that Nearest Neighbor interpolation
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