package: niworkflows
sections:
- name: Summary
  reportlets:
  - bids: {datatype: figures, desc: summary, suffix: T1w}
- name: Anatomical
  reportlets:
  - bids:
      datatype: figures
      desc: conform
      extension: [.html]
      suffix: T1w
  - bids: {datatype: figures, 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: figures, space: .*, suffix: T1w, regex_search: True}
    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.
    static: false
    subtitle: Spatial normalization of the anatomical T1w reference
  - bids: {datatype: figures, 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: Functional
  ordering: session,task,acquisition,ceagent,reconstruction,direction,run,echo
  reportlets:
  - bids: {datatype: figures, desc: summary, suffix: bold}
  - bids: {datatype: figures, desc: validation, suffix: bold}
  - bids: {datatype: figures, desc: fieldmap, suffix: bold}
    caption: The estimated fieldmap was aligned to the corresponding EPI reference
      with a rigid-registration process of the magintude part of the fieldmap,
      using <code>antsRegistration</code>.
      Overlaid on top of the co-registration results, the displacements along the
      phase-encoding direction are represented in arbitrary units.
      Please note that the color scale is centered around zero (i.e. full transparency),
      but the extremes might be different (i.e., the maximum of red colors could be
      orders of magnitude above or below the minimum of blue colors.)
    static: false
    subtitle: Estimated fieldmap and alignment to the corresponding EPI reference
  - bids: {datatype: figures, desc: sdc, suffix: bold}
    caption: Results of performing susceptibility distortion correction (SDC) on the
      EPI
    static: false
    subtitle: Susceptibility distortion correction
  - bids: {datatype: figures, 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.
    static: false
    subtitle: Experimental fieldmap-less susceptibility distortion correction
  - bids: {datatype: figures, 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.
    static: false
    subtitle: Alignment of functional and anatomical MRI data (volume based)
  - bids: {datatype: figures, 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.
    static: false
    subtitle: Alignment of functional and anatomical MRI data (volume based)
  - bids: {datatype: figures, 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
      is used in the reportlets in order to highlight potential spin-history and other
      artifacts, whereas final images are resampled using Lanczos interpolation.
    static: false
    subtitle: Alignment of functional and anatomical MRI data (surface driven)
  - bids: {datatype: figures, desc: bbregister, suffix: bold}
    caption: <code>bbregister</code> was used to generate transformations from EPI-space
      to T1w-space. 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.
    static: false
    subtitle: Alignment of functional and anatomical MRI data (surface driven)
  - bids: {datatype: figures, 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: Brain mask and (temporal/anatomical) CompCor ROIs
  - bids:
      datatype: figures
      desc: '[at]compcor'
      extension: [.html]
      suffix: bold
  - bids: {datatype: figures, desc: '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.
    subtitle: Variance explained by t/aCompCor components
  - bids: {datatype: figures, desc: carpetplot, suffix: bold}
    caption: Summary statistics are plotted, which may reveal trends or artifacts
      in the BOLD data. Global signals calculated within the whole-brain (GS), within
      the white-matter (WM) and within cerebro-spinal fluid (CSF) show the mean BOLD
      signal in their corresponding masks. DVARS and FD show the standardized DVARS
      and framewise-displacement measures for each time point.<br />A carpet plot
      shows the time series for all voxels within the brain mask, or if ``--cifti-output``
      was enabled, all grayordinates. Voxels are grouped into cortical (dark/light blue),
      and subcortical (orange) gray matter, cerebellum (green) and white matter and CSF
      (red), indicated by the color map on the left-hand side.
    subtitle: BOLD Summary
  - bids: {datatype: figures, 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: figures, desc: aroma, suffix: bold}
    caption: |
      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 are plotted
      in green; noise components in red.
    subtitle: ICA Components classified by AROMA
- name: About
  reportlets:
  - bids: {datatype: figures, desc: about, suffix: T1w}