Track proximal sources of functional GIFTIs (#3263)

Related to #3261.

## Changes proposed in this pull request

- Add an outputnode to `init_ds_volumes_wf` with the saved `bold` path.
- Add `sources` field to `init_bold_surf_wf`'s inputnode.
- Infer Sources for functional GIFTI outputs.
- If the user has requested T1w-space outputs, then this should be
`bold` from the associated `ds_volumes_wf` and `fsnative2t1w_xfm`
- If the user didn't want T1w-space volumetric outputs, then this should
be the raw BOLD file, `motion_xfm`, `boldref2anat_xfm`,
`fsnative2t1w_xfm`.

Author: tsalo

fmriprep/workflows/bold/base.py

@@ -514,6 +514,25 @@ def init_bold_wf(
             (bold_anat_wf, bold_surf_wf, [('outputnode.bold_file', 'inputnode.bold_t1w')]),
         ])  # fmt:skip
 
+        # sources are bold_file, motion_xfm, boldref2anat_xfm, fsnative2t1w_xfm
+        merge_surface_sources = pe.Node(
+            niu.Merge(4),
+            name='merge_surface_sources',
+            run_without_submitting=True,
+        )
+        merge_surface_sources.inputs.in1 = bold_file
+        workflow.connect([
+            (bold_fit_wf, merge_surface_sources, [
+                ('outputnode.motion_xfm', 'in2'),
+                ('outputnode.boldref2anat_xfm', 'in3'),
+            ]),
+            (inputnode, merge_surface_sources, [
+                ('fsnative2t1w_xfm', 'in4'),
+            ]),
+        ])  # fmt:skip
+
+        workflow.connect([(merge_surface_sources, bold_surf_wf, [('out', 'inputnode.sources')])])
+
     if config.workflow.cifti_output:
         from .resampling import (
             init_bold_fsLR_resampling_wf,

fmriprep/workflows/bold/resampling.py

@@ -43,7 +43,9 @@
 from niworkflows.interfaces.fixes import FixHeaderApplyTransforms as ApplyTransforms
 from niworkflows.interfaces.freesurfer import MedialNaNs
 
+from ... import config
 from ...config import DEFAULT_MEMORY_MIN_GB
+from ...interfaces.bids import BIDSURI
 from ...interfaces.workbench import MetricDilate, MetricMask, MetricResample
 from ...utils.bids import dismiss_echo
 from .outputs import prepare_timing_parameters
@@ -93,6 +95,8 @@ def init_bold_surf_wf(
     ------
     source_file
         Original BOLD series
+    sources
+        List of files used to create the output files.
     bold_t1w
         Motion-corrected BOLD series in T1 space
     subjects_dir
@@ -128,6 +132,7 @@ def init_bold_surf_wf(
         niu.IdentityInterface(
             fields=[
                 'source_file',
+                'sources',
                 'bold_t1w',
                 'subject_id',
                 'subjects_dir',
@@ -139,6 +144,15 @@ def init_bold_surf_wf(
     itersource = pe.Node(niu.IdentityInterface(fields=['target']), name='itersource')
     itersource.iterables = [('target', surface_spaces)]
 
+    surfs_sources = pe.Node(
+        BIDSURI(
+            numinputs=1,
+            dataset_links=config.execution.dataset_links,
+            out_dir=str(config.execution.fmriprep_dir.absolute()),
+        ),
+        name='surfs_sources',
+    )
+
     get_fsnative = pe.Node(FreeSurferSource(), name='get_fsnative', run_without_submitting=True)
 
     def select_target(subject_id, space):
@@ -212,6 +226,8 @@ def select_target(subject_id, space):
         (itk2lta, sampler, [('out_inv', 'reg_file')]),
         (targets, sampler, [('out', 'target_subject')]),
         (inputnode, ds_bold_surfs, [('source_file', 'source_file')]),
+        (inputnode, surfs_sources, [('sources', 'in1')]),
+        (surfs_sources, ds_bold_surfs, [('out', 'Sources')]),
         (itersource, ds_bold_surfs, [('target', 'space')]),
         (update_metadata, ds_bold_surfs, [('out_file', 'in_file')]),
     ])  # fmt:skip
@@ -488,14 +504,12 @@ def _calc_lower_thr(in_stats):
     )
 
     # apply goodvoxels ribbon mask to bold
-    workflow.connect(
-        [
-            (goodvoxels_mask, goodvoxels_ribbon_mask, [('out_file', 'in_file')]),
-            (ribbon_boldsrc_xfm, goodvoxels_ribbon_mask, [('output_image', 'mask_file')]),
-            (goodvoxels_mask, outputnode, [('out_file', 'goodvoxels_mask')]),
-            (goodvoxels_ribbon_mask, outputnode, [('out_file', 'goodvoxels_ribbon')]),
-        ]
-    )
+    workflow.connect([
+        (goodvoxels_mask, goodvoxels_ribbon_mask, [('out_file', 'in_file')]),
+        (ribbon_boldsrc_xfm, goodvoxels_ribbon_mask, [('output_image', 'mask_file')]),
+        (goodvoxels_mask, outputnode, [('out_file', 'goodvoxels_mask')]),
+        (goodvoxels_ribbon_mask, outputnode, [('out_file', 'goodvoxels_ribbon')]),
+    ])  # fmt:skip
 
     return workflow