Fix longitudinal functional template

src/rbc/bids/longitudinal/anatomical.py

@@ -43,7 +43,7 @@ def resolve_longitudinal_anat(
         Dict with keys matching ``longitudinal_process`` parameters.
     """
     return {
-        "template": tpl_q.expect(tpl_df, suffix=Suffix.T1W),
+        "template": tpl_q.expect(tpl_df, suffix=Suffix.T1W, without=["res"]),
         "subj_to_template_xfm": tpl_q.expect(
             tpl_df,
             suffix="xfm",

src/rbc/bids/longitudinal/functional.py

@@ -51,7 +51,7 @@ def resolve_longitudinal_func(
         )
 
     return {
-        "template": tpl_q.expect(tpl_df, suffix="T1w"),
+        "template": tpl_q.expect(tpl_df, res="bold", suffix="T1w"),
         "anat_to_template_xfm": tpl_q.expect(
             tpl_df,
             suffix="xfm",

src/rbc/bids/longitudinal/template.py

@@ -21,11 +21,13 @@ class TemplateInputs(NamedTuple):
         sub: Subject label.
         sessions: Per-input session labels (parallel to ``files``).
         files: Per-session preprocessed T1w brain volumes.
+        bold_ref: First BOLD volume for grid reference
     """
 
     sub: str
     sessions: list[str]
     files: list[Path]
+    bold_ref: Path | None
 
 
 def discover_template_inputs(
@@ -56,6 +58,17 @@ def discover_template_inputs(
         # the mri_robust_template invocation.
         pl.col("space").is_null(),
     )
+    bold_ref_rows = df.filter(
+        pl.col("ses") != "longitudinal",
+        pl.col("datatype") == "func",
+        pl.col("suffix") == "bold",
+        pl.col("space").is_null(),
+    )
+    bold_ref = (
+        None
+        if bold_ref_rows.is_empty()
+        else Path(bold_ref_rows["root"][0]) / bold_ref_rows["path"][0]
+    )
 
     inputs: list[TemplateInputs] = []
     skipped: list[str] = []
@@ -68,7 +81,9 @@ def discover_template_inputs(
         files = [
             Path(row["root"]) / row["path"] for row in sub_group.iter_rows(named=True)
         ]
-        inputs.append(TemplateInputs(sub=sub, sessions=sessions, files=files))
+        inputs.append(
+            TemplateInputs(sub=sub, sessions=sessions, files=files, bold_ref=bold_ref)
+        )
     return inputs, skipped
 
 
@@ -81,6 +96,8 @@ def export_template(tpl: Bids, outputs: LongitudinalTemplateOutputs) -> None:
         outputs: Results from the longitudinal template workflow.
     """
     tpl.save(outputs.template, suffix=Suffix.T1W)
+    if outputs.bold_template is not None:
+        tpl.save(outputs.bold_template, res="bold", suffix=Suffix.T1W)
     for ses, xfm in zip(outputs.sessions, outputs.transforms, strict=True):
         ses_label = bids_safe_label(ses)
         tpl.save(

src/rbc/core/longitudinal/resampling.py

@@ -0,0 +1,45 @@
+"""Resampling utilities for longitudinal templates."""
+
+from __future__ import annotations
+
+from typing import TYPE_CHECKING
+
+import nibabel as nib
+from nibabel.processing import resample_from_to
+
+if TYPE_CHECKING:
+    from pathlib import Path
+
+from rbc.core.niwrap import generate_exec_folder
+
+
+def resample_img_to_bold_grid(bold_ref: Path, img: Path) -> Path:
+    """Resample template to BOLD grid if shapes differ.
+
+    Args:
+        bold_ref: BOLD reference volume (used for ITK conversion).
+        img: 3D image in target space to resample.
+
+    Returns:
+        Resampled 3D image with BOLD grid
+
+    Raises:
+        FileNotFoundError: No motion .mat files found in the directory.
+        ValueError: Number of motion matrices does not match STC volumes.
+    """
+    bold_ref_img = nib.nifti1.load(bold_ref)
+    img_obj = nib.nifti1.load(img)
+
+    # If 4D, extract first volume
+    if len(bold_ref_img.shape) > 3:
+        bold_ref_img = nib.four_to_three(bold_ref_img)[0]
+    # If same shape, no need to resample
+    if bold_ref_img.shape == img_obj.shape:
+        return img
+
+    img_resampled = resample_from_to(img_obj, bold_ref_img)
+    img_resampled_path = (
+        generate_exec_folder("img_resample_to_bold_grid") / "resampled.nii.gz"
+    )
+    nib.save(img_resampled, img_resampled_path)
+    return img_resampled_path

src/rbc/orchestration/longitudinal/qc.py

@@ -21,6 +21,7 @@
     write_longitudinal_qc_tsv,
 )
 from rbc.bids.session import iter_session_files
+from rbc.core.longitudinal.resampling import resample_img_to_bold_grid
 from rbc.core.niwrap import generate_exec_folder
 from rbc.core.qc.registration import registration_qc_metrics
 from rbc.orchestration import Filters, RunnerConfig, init_runner
@@ -67,6 +68,10 @@ def process_qc(
     Returns:
         QC outputs with overlap metrics and pass/fail flag.
     """
+    # Resample longitudinal anatomical mask to bold grid for QC purposes.
+    # Longitudinal processed data are registered to the longitudinal template with
+    # respective modality's native resolution
+    anat_brain_mask = resample_img_to_bold_grid(bold_mask, anat_brain_mask)
     anat_mask_arr = nib.nifti1.load(anat_brain_mask).get_fdata()
     bold_mask_arr = nib.nifti1.load(bold_mask).get_fdata()
     reg_metrics = registration_qc_metrics(anat_mask_arr, bold_mask_arr)

src/rbc/orchestration/longitudinal/template.py

@@ -49,6 +49,7 @@ def process_subject(
         sub=inputs.sub,
         sessions=inputs.sessions,
         in_files=inputs.files,
+        bold_ref=inputs.bold_ref,
     )
     tpl = pipe_ctx.bids(datatype=Datatype.ANAT).derive(ses="longitudinal")
     export_template(tpl, outputs)

src/rbc/workflows/longitudinal/template.py

@@ -14,6 +14,7 @@
     fs_to_itk_xfm,
     generate_robust_template,
 )
+from rbc.core.longitudinal.resampling import resample_img_to_bold_grid
 
 if TYPE_CHECKING:
     from collections.abc import Sequence
@@ -27,11 +28,13 @@ class LongitudinalTemplateOutputs(NamedTuple):
 
     Attributes:
         template: Robust within-subject template volume.
+        bold_template: Within-subject template volume resampled to BOLD resolution.
         sessions: Session labels in the same order as ``transforms``.
         transforms: Per-session ITK-format session-to-template transforms.
     """
 
     template: Path
+    bold_template: Path | None
     sessions: list[str]
     transforms: list[Path]
 
@@ -40,13 +43,15 @@ def generate_subject_template(
     sub: str,
     sessions: Sequence[str],
     in_files: Sequence[Path],
+    bold_ref: Path | None = None,
 ) -> LongitudinalTemplateOutputs:
     """Build a robust template and ITK transforms for one subject.
 
     Args:
         sub: Subject label (without the ``sub-`` prefix).
         sessions: Session labels parallel to ``in_files``.
         in_files: Per-session preprocessed T1w volumes (e.g. brain-extracted).
+        bold_ref: Reference bold volume to resample template for functional data.
 
     Returns:
         :class:`LongitudinalTemplateOutputs` ready for BIDS export.
@@ -65,8 +70,12 @@ def generate_subject_template(
         in_xfms=robust.transforms,
     )
 
+    if bold_ref is not None:
+        bold_ref = resample_img_to_bold_grid(bold_ref, robust.template)
+
     return LongitudinalTemplateOutputs(
         template=robust.template,
+        bold_template=bold_ref,
         sessions=list(sessions),
         transforms=itk_xfms,
     )

tests/unit/bids/test_longitudinal_anatomical.py

@@ -99,6 +99,7 @@ def _anat_row(
         "sub": sub,
         "ses": ses,
         "desc": desc,
+        "res": None,
         "root": "/data",
         "path": path,
         "extra_entities": extra or [],

tests/unit/bids/test_longitudinal_functional.py

@@ -59,6 +59,7 @@ def _anat_row(
     sub: str,
     ses: str,
     suffix: str,
+    res: str | None = None,
     desc: str | None = None,
     ext: str = ".nii.gz",
     extra: list[dict[str, str]] | None = None,
@@ -73,6 +74,7 @@ def _anat_row(
         "sub": sub,
         "ses": ses,
         "space": None,
+        "res": res,
         "desc": desc,
         "root": "/data",
         "path": path,
@@ -143,7 +145,7 @@ def test_resolves_single_regressor(self, tmp_path: Path) -> None:
             ),
         )
         tpl_df = _df(
-            _anat_row(sub="01", ses="longitudinal", suffix="T1w"),
+            _anat_row(sub="01", ses="longitudinal", res="bold", suffix="T1w"),
             _anat_row(
                 sub="01",
                 ses="longitudinal",
@@ -218,7 +220,7 @@ def test_resolves_multiple_regressors(self, tmp_path: Path) -> None:
             ),
         )
         tpl_df = _df(
-            _anat_row(sub="01", ses="longitudinal", suffix="T1w"),
+            _anat_row(sub="01", ses="longitudinal", res="bold", suffix="T1w"),
             _anat_row(
                 sub="01",
                 ses="longitudinal",
@@ -275,7 +277,7 @@ def test_missing_regressor_raises(self, tmp_path: Path) -> None:
             ),
         )
         tpl_df = _df(
-            _anat_row(sub="01", ses="longitudinal", suffix="T1w"),
+            _anat_row(sub="01", ses="longitudinal", res="bold", suffix="T1w"),
             _anat_row(
                 sub="01",
                 ses="longitudinal",
@@ -328,7 +330,7 @@ def test_bold_mask_mandatory(self, tmp_path: Path) -> None:
             ),
         )
         tpl_df = _df(
-            _anat_row(sub="01", ses="longitudinal", suffix="T1w"),
+            _anat_row(sub="01", ses="longitudinal", res="bold", suffix="T1w"),
             _anat_row(
                 sub="01",
                 ses="longitudinal",

tests/unit/bids/test_longitudinal_template.py

@@ -35,7 +35,7 @@ def _df(*rows: tuple) -> pl.DataFrame:
     return pl.DataFrame(dict(zip(_SCHEMA, zip(*rows, strict=True), strict=True)))
 
 
-def _brain_row(sub: str, ses: str, space: str | None = None) -> tuple:
+def _anat_row(sub: str, ses: str, space: str | None = None) -> tuple:
     space_part = f"_space-{space}" if space else ""
     path = (
         f"sub-{sub}/ses-{ses}/anat/"
@@ -56,16 +56,25 @@ def _brain_row(sub: str, ses: str, space: str | None = None) -> tuple:
     )
 
 
+def _func_row(sub: str, ses: str, task: str = "rest") -> tuple:
+    path = f"sub-{sub}/ses-{ses}/func/sub-{sub}_ses-{ses}_task-{task}_bold.nii.gz"
+    return ("func", "bold", ".nii.gz", sub, ses, None, task, None, None, "/data", path)
+
+
 class TestDiscoverTemplateInputs:
     """Tests for :func:`discover_template_inputs`."""
 
     def test_groups_by_subject(self) -> None:
         """Multi-session subjects yield one TemplateInputs each."""
         df = _df(
-            _brain_row("01", "baseline"),
-            _brain_row("01", "vis2"),
-            _brain_row("02", "baseline"),
-            _brain_row("02", "vis2"),
+            _anat_row("01", "baseline"),
+            _anat_row("01", "vis2"),
+            _anat_row("02", "baseline"),
+            _anat_row("02", "vis2"),
+            _func_row("01", "baseline"),
+            _func_row("01", "vis2"),
+            _func_row("02", "baseline"),
+            _func_row("02", "vis2"),
         )
         inputs, skipped = discover_template_inputs(df)
         assert {ti.sub for ti in inputs} == {"01", "02"}
@@ -77,9 +86,12 @@ def test_groups_by_subject(self) -> None:
     def test_reports_single_session_subject(self) -> None:
         """Single-session subjects are reported separately (bug #19)."""
         df = _df(
-            _brain_row("01", "baseline"),
-            _brain_row("01", "vis2"),
-            _brain_row("02", "baseline"),
+            _anat_row("01", "baseline"),
+            _anat_row("01", "vis2"),
+            _anat_row("02", "baseline"),
+            _func_row("01", "baseline"),
+            _func_row("01", "vis2"),
+            _func_row("02", "baseline"),
         )
         inputs, skipped = discover_template_inputs(df)
         assert [ti.sub for ti in inputs] == ["01"]
@@ -88,9 +100,12 @@ def test_reports_single_session_subject(self) -> None:
     def test_excludes_existing_longitudinal(self) -> None:
         """Pre-existing longitudinal templates are not re-included as inputs."""
         df = _df(
-            _brain_row("01", "baseline"),
-            _brain_row("01", "vis2"),
-            _brain_row("01", "longitudinal"),
+            _anat_row("01", "baseline"),
+            _anat_row("01", "vis2"),
+            _anat_row("01", "longitudinal"),
+            _func_row("01", "baseline"),
+            _func_row("01", "vis2"),
+            _func_row("01", "longitudinal"),
         )
         inputs, skipped = discover_template_inputs(df)
         assert len(inputs) == 1
@@ -111,10 +126,10 @@ def test_excludes_mni_registered_brains(self) -> None:
         duplicate LTA filenames in the mri_robust_template invocation.
         """
         df = _df(
-            _brain_row("01", "test"),
-            _brain_row("01", "test", space="MNI152NLin6Asym"),
-            _brain_row("01", "retest"),
-            _brain_row("01", "retest", space="MNI152NLin6Asym"),
+            _anat_row("01", "test"),
+            _anat_row("01", "test", space="MNI152NLin6Asym"),
+            _anat_row("01", "retest"),
+            _anat_row("01", "retest", space="MNI152NLin6Asym"),
         )
         inputs, skipped = discover_template_inputs(df)
         assert len(inputs) == 1
@@ -131,13 +146,16 @@ def test_writes_template_and_xfms(self, tmp_path: Path) -> None:
         """Template + per-session xfms land at the expected BIDS paths."""
         template_src = tmp_path / "src_template.nii.gz"
         template_src.write_bytes(b"\x00")
+        template_bold_src = tmp_path / "src_bold_template.nii.gz"
+        template_bold_src.write_bytes(b"\x00")
         xfm_baseline = tmp_path / "xfm_baseline.txt"
         xfm_baseline.write_text("baseline")
         xfm_vis2 = tmp_path / "xfm_vis2.txt"
         xfm_vis2.write_text("vis2")
 
         outputs = LongitudinalTemplateOutputs(
             template=template_src,
+            bold_template=template_bold_src,
             sessions=["baseline", "vis2"],
             transforms=[xfm_baseline, xfm_vis2],
         )