Clarify that warped surfaces can be overlaid on the MNI152NLin6Asym t…

…emplate (#1349)

docs/outputs.rst

@@ -128,6 +128,9 @@ The resulting mesh files will reflect the subject's morphology with the same geo
 as fsLR-32k surfaces, which may be useful for visualizing fsLR-space derivatives on a subject's
 brain.
 
+The mesh files are also warped so that they can be overlaid on top of the MNI152NLin6Asym template,
+as in XCP-D's brainsprite.
+
 .. code-block::
 
    xcp_d/

xcp_d/cli/parser.py

@@ -738,8 +738,9 @@ def _build_parser():
         help="""\
 If used, a workflow will be run to warp native-space (``fsnative``) reconstructed cortical
 surfaces (``surf.gii`` files) produced by Freesurfer into standard (``fsLR``) space.
+Additionally, the fsLR-space surfaces will be warped such that they can be overlaid on the
+MNI152NLin6Asym template.
 These surface files are primarily used for visual quality assessment.
-By default, this workflow is disabled.
 
 **IMPORTANT**: This parameter can only be run if the --file-format flag is set to cifti.
 """,

xcp_d/workflows/anatomical/surface.py

@@ -52,6 +52,8 @@ def init_postprocess_surfaces_wf(
     they will be copied to the output directory.
     These fsLR-space mesh files retain the subject's morphology,
     and are thus useful for visualizing fsLR-space statistical derivatives on the subject's brain.
+    The workflow will also rigidly align the meshes to the MNI152NLin6Asym template,
+    so that they can be overlaid on top of the template for visualization.
 
     As long as process-surfaces is enabled and mesh files (in either space) are available,
     HCP-style midthickness, inflated, and very-inflated surfaces will be generated from them.
@@ -298,6 +300,9 @@ def init_warp_surfaces_to_template_wf(
 ):
     """Transform surfaces from native to standard fsLR-32k space.
 
+    The workflow will also rigidly align the meshes to the MNI152NLin6Asym template,
+    so that they can be overlaid on top of the template for visualization.
+
     Workflow Graph
         .. workflow::
             :graph2use: orig
@@ -926,7 +931,7 @@ def init_warp_one_hemisphere_wf(
     6. Apply the anatomical-to-template warpfield to the 32k surfaces.
        This and the previous step make it so you can overlay the pial and white matter surfaces
        on the associated volumetric template (e.g., for XCP-D's brainsprite).
-        - This important thing is that the volumetric template must match the template space
+        - The important thing is that the volumetric template must match the template space
           used here.
     """
     workflow = Workflow(name=name)
@@ -988,7 +993,8 @@ def init_warp_one_hemisphere_wf(
     ])  # fmt:skip
 
     # Apply FLIRT-format anatomical-to-template affine transform to 32k surfs
-    # NOTE: What does this step do? Aren't the data in fsLR/dhcpAsym-32k from resample_to_fsLR32k?
+    # I think this makes it so you can overlay the pial and white matter surfaces on the
+    # associated volumetric template (e.g., for XCP-D's brainsprite).
     apply_affine_to_fsLR32k = pe.MapNode(
         ApplyAffine(num_threads=omp_nthreads),
         name='apply_affine_to_fsLR32k',
@@ -1002,7 +1008,8 @@ def init_warp_one_hemisphere_wf(
     ])  # fmt:skip
 
     # Apply FNIRT-format (forward) anatomical-to-template warpfield
-    # NOTE: What does this step do?
+    # I think this makes it so you can overlay the pial and white matter surfaces on the
+    # associated volumetric template (e.g., for XCP-D's brainsprite).
     apply_warpfield_to_fsLR32k = pe.MapNode(
         ApplyWarpfield(num_threads=omp_nthreads),
         name='apply_warpfield_to_fsLR32k',