From 23bc03b9454296538b55e54ea5cc4bae71150da5 Mon Sep 17 00:00:00 2001
From: "birajstha:construction_worker::penguin" <birajstha@gmail.com>
Date: Fri, 22 Aug 2025 16:07:36 -0400
Subject: [PATCH 01/17] changing ref from brain to whole head

---
 CPAC/func_preproc/func_preproc.py | 37 ++++++--------
 CPAC/pipeline/cpac_pipeline.py    | 16 +++---
 CPAC/registration/registration.py | 82 +++++++------------------------
 3 files changed, 44 insertions(+), 91 deletions(-)

diff --git a/CPAC/func_preproc/func_preproc.py b/CPAC/func_preproc/func_preproc.py
index d098b6186..c787b06f3 100644
--- a/CPAC/func_preproc/func_preproc.py
+++ b/CPAC/func_preproc/func_preproc.py
@@ -1559,12 +1559,12 @@ def anat_brain_to_bold_res(wf_name, cfg, pipe_num):
 
     inputNode = pe.Node(
         util.IdentityInterface(
-            fields=["T1w-template-funcreg", "space-template_desc-preproc_T1w"]
+            fields=["T1w-template-funcreg", "space-template_desc-head_T1w"]
         ),
         name="inputspec",
     )
     outputNode = pe.Node(
-        util.IdentityInterface(fields=["space-template_res-bold_desc-brain_T1w"]),
+        util.IdentityInterface(fields=["space-template_res-bold_desc-head_T1w"]),
         name="outputspec",
     )
 
@@ -1579,7 +1579,7 @@ def anat_brain_to_bold_res(wf_name, cfg, pipe_num):
     ]["registration"]["FSL-FNIRT"]["identity_matrix"]
 
     wf.connect(
-        inputNode, "space-template_desc-preproc_T1w", anat_brain_to_func_res, "in_file"
+        inputNode, "space-template_desc-head_T1w", anat_brain_to_func_res, "in_file"
     )
     wf.connect(inputNode, "T1w-template-funcreg", anat_brain_to_func_res, "ref_file")
 
@@ -1587,7 +1587,7 @@ def anat_brain_to_bold_res(wf_name, cfg, pipe_num):
         anat_brain_to_func_res,
         "out_file",
         outputNode,
-        "space-template_res-bold_desc-brain_T1w",
+        "space-template_res-bold_desc-head_T1w",
     )
     return wf
 
@@ -1598,7 +1598,7 @@ def anat_brain_mask_to_bold_res(wf_name, cfg, pipe_num):
     wf = pe.Workflow(name=f"{wf_name}_{pipe_num}")
     inputNode = pe.Node(
         util.IdentityInterface(
-            fields=["space-template_desc-brain_mask", "space-template_desc-preproc_T1w"]
+            fields=["space-template_desc-brain_mask", "space-template_desc-head_T1w"]
         ),
         name="inputspec",
     )
@@ -1625,7 +1625,7 @@ def anat_brain_mask_to_bold_res(wf_name, cfg, pipe_num):
     )
     wf.connect(
         inputNode,
-        "space-template_desc-preproc_T1w",
+        "space-template_desc-head_T1w",
         anat_brain_mask_to_func_res,
         "ref_file",
     )
@@ -1649,11 +1649,11 @@ def anat_brain_mask_to_bold_res(wf_name, cfg, pipe_num):
     option_val="Anatomical_Resampled",
     inputs=[
         "T1w-template-funcreg",
-        "space-template_desc-preproc_T1w",
+        "space-template_desc-head_T1w",
         "space-template_desc-brain_mask",
     ],
     outputs=[
-        "space-template_res-bold_desc-brain_T1w",
+        "space-template_res-bold_desc-head_T1w",
         "space-template_desc-bold_mask",
     ],
 )
@@ -1666,9 +1666,9 @@ def bold_mask_anatomical_resampled(wf, cfg, strat_pool, pipe_num, opt=None):
         wf_name="anat_brain_to_bold_res", cfg=cfg, pipe_num=pipe_num
     )
 
-    node, out = strat_pool.get_data("space-template_desc-preproc_T1w")
+    node, out = strat_pool.get_data("space-template_desc-head_T1w")
     wf.connect(
-        node, out, anat_brain_to_func_res, "inputspec.space-template_desc-preproc_T1w"
+        node, out, anat_brain_to_func_res, "inputspec.space-template_desc-head_T1w"
     )
 
     node, out = strat_pool.get_data("T1w-template-funcreg")
@@ -1690,15 +1690,15 @@ def bold_mask_anatomical_resampled(wf, cfg, strat_pool, pipe_num, opt=None):
 
     wf.connect(
         anat_brain_to_func_res,
-        "outputspec.space-template_res-bold_desc-brain_T1w",
+        "outputspec.space-template_res-bold_desc-head_T1w",
         anat_brain_mask_to_func_res,
-        "inputspec.space-template_desc-preproc_T1w",
+        "inputspec.space-template_desc-head_T1w",
     )
 
     outputs = {
-        "space-template_res-bold_desc-brain_T1w": (
+        "space-template_res-bold_desc-head_T1w": (
             anat_brain_to_func_res,
-            "outputspec.space-template_res-bold_desc-brain_T1w",
+            "outputspec.space-template_res-bold_desc-head_T1w",
         ),
         "space-template_desc-bold_mask": (
             anat_brain_mask_to_func_res,
@@ -1897,7 +1897,7 @@ def bold_masking(wf, cfg, strat_pool, pipe_num, opt=None):
         ["functional_preproc", "template_space_func_masking", "run"],
     ],
     inputs=[
-        ("space-template_desc-preproc_bold", "space-template_desc-bold_mask"),
+        ("space-template_desc-head_bold", "space-template_desc-bold_mask"),
     ],
     outputs={
         "space-template_desc-preproc_bold": {
@@ -1908,10 +1908,6 @@ def bold_masking(wf, cfg, strat_pool, pipe_num, opt=None):
             "Description": "The skull-stripped BOLD time-series.",
             "SkullStripped": True,
         },
-        "space-template_desc-head_bold": {
-            "Description": "The non skull-stripped BOLD time-series.",
-            "SkullStripped": False,
-        },
     },
 )
 def template_space_bold_masking(
@@ -1931,7 +1927,7 @@ def template_space_bold_masking(
     func_apply_mask.inputs.outputtype = "NIFTI_GZ"
 
     node_head_bold, out_head_bold = strat_pool.get_data(
-        "space-template_desc-preproc_bold"
+        "space-template_desc-head_bold"
     )
     wf.connect(node_head_bold, out_head_bold, func_apply_mask, "in_file_a")
 
@@ -1941,7 +1937,6 @@ def template_space_bold_masking(
     outputs: POOL_RESOURCE_DICT = {
         "space-template_desc-preproc_bold": (func_apply_mask, "out_file"),
         "space-template_desc-brain_bold": (func_apply_mask, "out_file"),
-        "space-template_desc-head_bold": (node_head_bold, out_head_bold),
     }
 
     return wf, outputs
diff --git a/CPAC/pipeline/cpac_pipeline.py b/CPAC/pipeline/cpac_pipeline.py
index c2ffa9640..6546a1324 100644
--- a/CPAC/pipeline/cpac_pipeline.py
+++ b/CPAC/pipeline/cpac_pipeline.py
@@ -1291,6 +1291,13 @@ def build_workflow(subject_id, sub_dict, cfg, pipeline_name=None):
             mask_sbref,
         ]
 
+    # Template space functional mask
+    if cfg.functional_preproc["template_space_func_masking"]["run"]:
+        if not rpool.check_rpool("space-template_desc-bold_mask"):
+            pipeline_blocks += [
+                bold_mask_anatomical_resampled,
+            ]
+
         # Distortion/Susceptibility Correction
         distcor_blocks = []
         if "fmap" in sub_dict:
@@ -1472,17 +1479,12 @@ def build_workflow(subject_id, sub_dict, cfg, pipeline_name=None):
             warp_deriv_mask_to_EPItemplate,
         ]
 
-    # Template space functional masking
+    # Apply mask in template space
     if cfg.functional_preproc["template_space_func_masking"]["run"]:
-        if not rpool.check_rpool("space-template_desc-bold_mask"):
-            pipeline_blocks += [
-                bold_mask_anatomical_resampled,
-            ]
-
         pipeline_blocks += [
             template_space_bold_masking,
         ]
-
+        
     # Template-space nuisance regression
     nuisance_template = (
         cfg["nuisance_corrections", "2-nuisance_regression", "space"] == "template"
diff --git a/CPAC/registration/registration.py b/CPAC/registration/registration.py
index efb8645df..9bdda851b 100644
--- a/CPAC/registration/registration.py
+++ b/CPAC/registration/registration.py
@@ -2901,6 +2901,7 @@ def register_ANTs_EPI_to_template(wf, cfg, strat_pool, pipe_num, opt=None):
     inputs=[
         (
             "desc-restore-brain_T1w",
+            "desc-head_T1w",
             ["desc-preproc_T1w", "space-longitudinal_desc-brain_T1w"],
             ["desc-restore_T1w", "desc-preproc_T1w", "desc-reorient_T1w", "T1w"],
             ["desc-preproc_T1w", "desc-reorient_T1w", "T1w"],
@@ -3081,7 +3082,7 @@ def overwrite_transform_anat_to_template(wf, cfg, strat_pool, pipe_num, opt=None
         wf.connect(node, out, match_fovs_T1w, "reference")
         wf.connect(node, out, fsl_apply_warp_t1_to_template, "ref_file")
 
-        node, out = strat_pool.get_data(["desc-restore_T1w", "desc-preproc_T1w"])
+        node, out = strat_pool.get_data(["desc-restore_T1w", "desc-head_T1w"])
         wf.connect(node, out, match_fovs_T1w, "in_file")
         wf.connect(match_fovs_T1w, "out_file", fsl_apply_warp_t1_to_template, "in_file")
 
@@ -4169,7 +4170,8 @@ def warp_timeseries_to_T1template_deriv(wf, cfg, strat_pool, pipe_num, opt=None)
         "from-bold_to-template_mode-image_xfm",
         "fsl-blip-warp",
         "desc-preproc_T1w",
-        "space-template_res-bold_desc-brain_T1w",
+        "desc-head_T1w",
+        "space-template_res-bold_desc-head_T1w",
         "space-template_desc-bold_mask",
         "T1w-brain-template-funcreg",
         "T1w-template-funcreg",
@@ -4199,7 +4201,7 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
     convert_func_to_anat_linear_warp.inputs.out_relwarp = True
     convert_func_to_anat_linear_warp.inputs.relwarp = True
 
-    node, out = strat_pool.get_data("desc-preproc_T1w")
+    node, out = strat_pool.get_data("desc-head_T1w")
     wf.connect(node, out, convert_func_to_anat_linear_warp, "reference")
 
     if strat_pool.check_rpool("fsl-blip-warp"):
@@ -4231,24 +4233,9 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
     node, out = strat_pool.get_data("from-T1w_to-template_mode-image_xfm")
     wf.connect(node, out, convert_func_to_standard_warp, "warp2")
 
-    from CPAC.func_preproc.func_preproc import (
-        anat_brain_mask_to_bold_res,
-        anat_brain_to_bold_res,
-    )
-
-    anat_brain_to_func_res = anat_brain_to_bold_res(wf, cfg, pipe_num)
-
-    node, out = strat_pool.get_data("space-template_desc-preproc_T1w")
-    wf.connect(
-        node, out, anat_brain_to_func_res, "inputspec.space-template_desc-preproc_T1w"
-    )
-
-    node, out = strat_pool.get_data("T1w-template-funcreg")
-    wf.connect(node, out, anat_brain_to_func_res, "inputspec.T1w-template-funcreg")
-
+    node, out = strat_pool.get_data("space-template_res-bold_desc-head_T1w")
     wf.connect(
-        anat_brain_to_func_res,
-        "outputspec.space-template_res-bold_desc-brain_T1w",
+        node, out,
         convert_func_to_standard_warp,
         "reference",
     )
@@ -4314,11 +4301,9 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
     convert_registration_warp.inputs.out_relwarp = True
     convert_registration_warp.inputs.relwarp = True
 
+    node, out = strat_pool.get_data("space-template_res-bold_desc-head_T1w")
     wf.connect(
-        anat_brain_to_func_res,
-        "outputspec.space-template_res-bold_desc-brain_T1w",
-        convert_registration_warp,
-        "reference",
+        node, out, convert_registration_warp, "reference",
     )
 
     wf.connect(
@@ -4356,11 +4341,9 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
         convert_registration_warp, "out_file", applywarp_func_to_standard, "field_file"
     )
 
+    node, out = strat_pool.get_data("space-template_res-bold_desc-head_T1w")
     wf.connect(
-        anat_brain_to_func_res,
-        "outputspec.space-template_res-bold_desc-brain_T1w",
-        applywarp_func_to_standard,
-        "ref_file",
+        node, out, applywarp_func_to_standard, "ref_file",
     )
 
     # applywarp --rel --interp=nn --in=${WD}/prevols/vol${vnum}_mask.nii.gz --warp=${MotionMatrixFolder}/${MotionMatrixPrefix}${vnum}_all_warp.nii.gz --ref=${WD}/${T1wImageFile}.${FinalfMRIResolution} --out=${WD}/postvols/vol${vnum}_mask.nii.gz
@@ -4384,11 +4367,9 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
         "field_file",
     )
 
+    node, out = strat_pool.get_data("space-template_res-bold_desc-head_T1w")
     wf.connect(
-        anat_brain_to_func_res,
-        "outputspec.space-template_res-bold_desc-brain_T1w",
-        applywarp_func_mask_to_standard,
-        "ref_file",
+        node, out, applywarp_func_mask_to_standard, "ref_file",
     )
 
     ### Loop ends! ###
@@ -4436,11 +4417,9 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
     convert_dc_warp.inputs.out_relwarp = True
     convert_dc_warp.inputs.relwarp = True
 
+    node, out = strat_pool.get_data("space-template_res-bold_desc-head_T1w")
     wf.connect(
-        anat_brain_to_func_res,
-        "outputspec.space-template_res-bold_desc-brain_T1w",
-        convert_dc_warp,
-        "reference",
+        node, out, convert_dc_warp, "reference",
     )
 
     wf.connect(multiply_func_roi_by_zero, "out_file", convert_dc_warp, "warp1")
@@ -4458,11 +4437,9 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
     node, out = strat_pool.get_data("motion-basefile")
     wf.connect(node, out, applywarp_scout, "in_file")
 
+    node, out = strat_pool.get_data("space-template_res-bold_desc-head_T1w")
     wf.connect(
-        anat_brain_to_func_res,
-        "outputspec.space-template_res-bold_desc-brain_T1w",
-        applywarp_scout,
-        "ref_file",
+        node, out, applywarp_scout, "ref_file",
     )
 
     wf.connect(convert_dc_warp, "out_file", applywarp_scout, "field_file")
@@ -4471,30 +4448,9 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
     # fslmaths ${InputfMRI} -mas ${BrainMask} -mas ${InputfMRI}_mask -thr 0 -ing 10000 ${OutputfMRI} -odt float
     merge_func_mask = pe.Node(util.Merge(2), name=f"merge_func_mask_{pipe_num}")
 
-    anat_brain_mask_to_func_res = anat_brain_mask_to_bold_res(
-        wf_name="anat_brain_mask_to_bold_res", cfg=cfg, pipe_num=pipe_num
-    )
-
-    node, out = strat_pool.get_data("space-template_desc-brain_mask")
+    node, out = strat_pool.get_data("space-template_desc-bold_mask")
     wf.connect(
-        node,
-        out,
-        anat_brain_mask_to_func_res,
-        "inputspec.space-template_desc-brain_mask",
-    )
-
-    wf.connect(
-        anat_brain_to_func_res,
-        "outputspec.space-template_res-bold_desc-brain_T1w",
-        anat_brain_mask_to_func_res,
-        "inputspec.space-template_desc-preproc_T1w",
-    )
-
-    wf.connect(
-        anat_brain_mask_to_func_res,
-        "outputspec.space-template_desc-bold_mask",
-        merge_func_mask,
-        "in1",
+        node, out, merge_func_mask, "in1",
     )
 
     wf.connect(find_min_mask, "out_file", merge_func_mask, "in2")

From 9d89c6f93b202574781419a91449d94b71fe8477 Mon Sep 17 00:00:00 2001
From: "birajstha:construction_worker::penguin" <birajstha@gmail.com>
Date: Tue, 26 Aug 2025 12:13:52 -0400
Subject: [PATCH 02/17] removing unnecessary nodes

---
 CPAC/registration/registration.py | 132 ++++++++++++++++++------------
 1 file changed, 81 insertions(+), 51 deletions(-)

diff --git a/CPAC/registration/registration.py b/CPAC/registration/registration.py
index 9bdda851b..c2bdb6d60 100644
--- a/CPAC/registration/registration.py
+++ b/CPAC/registration/registration.py
@@ -22,6 +22,7 @@
 from voluptuous import RequiredFieldInvalid
 from nipype.interfaces import afni, ants, c3, fsl, utility as util
 from nipype.interfaces.afni import utils as afni_utils
+from pathlib import Path 
 
 from CPAC.anat_preproc.lesion_preproc import create_lesion_preproc
 from CPAC.func_preproc.func_preproc import fsl_afni_subworkflow
@@ -4194,6 +4195,21 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
     https://github.com/DCAN-Labs/DCAN-HCP/blob/a8d495a/fMRIVolume/scripts/DistortionCorrectionAndEPIToT1wReg_FLIRTBBRAndFreeSurferBBRbased.sh#L548
     convertwarp --relout --rel -m ${WD}/fMRI2str.mat --ref=${T1wImage} --out=${WD}/fMRI2str.nii.gz
     """
+    # Identity matrix node needed for matching FOV
+    identity_node = pe.Node(
+        Function(
+            imports=["from pathlib import Path", "import numpy as np"],
+            input_names=["workdir"],
+            output_names=["identity_file"],
+            function=lambda workdir: (
+                np.savetxt(Path(workdir) / "identity.mat", np.eye(4), fmt="%.6f") or
+                str(Path(workdir) / "identity.mat")
+            )
+        ),
+        name=f"create_identity_matrix_{pipe_num}"
+    )
+    identity_node.inputs.workdir = str(Path.cwd())
+        
     convert_func_to_anat_linear_warp = pe.Node(
         interface=fsl.ConvertWarp(), name=f"convert_func_to_anat_linear_warp_{pipe_num}"
     )
@@ -4204,15 +4220,12 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
     node, out = strat_pool.get_data("desc-head_T1w")
     wf.connect(node, out, convert_func_to_anat_linear_warp, "reference")
 
-    if strat_pool.check_rpool("fsl-blip-warp"):
-        node, out = strat_pool.get_data("from-bold_to-T1w_mode-image_desc-linear_xfm")
-        wf.connect(node, out, convert_func_to_anat_linear_warp, "postmat")
+    node, out = strat_pool.get_data("from-bold_to-T1w_mode-image_desc-linear_xfm")
+    wf.connect(node, out, convert_func_to_anat_linear_warp, "premat")
 
+    if strat_pool.check_rpool("fsl-blip-warp"):
         node, out = strat_pool.get_data("fsl-blip-warp")
         wf.connect(node, out, convert_func_to_anat_linear_warp, "warp1")
-    else:
-        node, out = strat_pool.get_data("from-bold_to-T1w_mode-image_desc-linear_xfm")
-        wf.connect(node, out, convert_func_to_anat_linear_warp, "premat")
 
     # https://github.com/DCAN-Labs/DCAN-HCP/blob/1d90814/fMRIVolume/scripts/OneStepResampling.sh#L140
     # convertwarp --relout --rel --warp1=${fMRIToStructuralInput} --warp2=${StructuralToStandard} --ref=${WD}/${T1wImageFile}.${FinalfMRIResolution} --out=${OutputTransform}
@@ -4253,15 +4266,6 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
     node, out = strat_pool.get_data("desc-reorient_bold")
     wf.connect(node, out, extract_func_roi, "in_file")
 
-    # fslmaths "$fMRIFolder"/"$NameOffMRI"_gdc_warp -mul 0 "$fMRIFolder"/"$NameOffMRI"_gdc_warp
-    multiply_func_roi_by_zero = pe.Node(
-        interface=fsl.maths.MathsCommand(), name=f"multiply_func_roi_by_zero_{pipe_num}"
-    )
-
-    multiply_func_roi_by_zero.inputs.args = "-mul 0"
-
-    wf.connect(extract_func_roi, "roi_file", multiply_func_roi_by_zero, "in_file")
-
     # https://github.com/DCAN-Labs/DCAN-HCP/blob/1d90814/fMRIVolume/scripts/OneStepResampling.sh#L168-L193
     # fslsplit ${InputfMRI} ${WD}/prevols/vol -t
     split_func = pe.Node(interface=fsl.Split(), name=f"split_func_{pipe_num}")
@@ -4272,6 +4276,16 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
     wf.connect(node, out, split_func, "in_file")
 
     ### Loop starts! ###
+    # Match FOV func_to_standard
+    match_fov_func = pe.MapNode(
+        interface=fsl.FLIRT(apply_xfm=True, interp="spline"), name=f"match_fov_func_{pipe_num}", iterfield=["in_file"]
+    )
+    wf.connect(identity_node, "identity_file", match_fov_func, "in_matrix_file")
+    wf.connect(split_func, "out_files", match_fov_func, "in_file")
+
+    node, out = strat_pool.get_data("space-template_res-bold_desc-head_T1w")
+    wf.connect(node, out, match_fov_func, "reference")
+
     # convertwarp --relout --rel --ref=${WD}/prevols/vol${vnum}.nii.gz --warp1=${GradientDistortionField} --postmat=${MotionMatrixFolder}/${MotionMatrixPrefix}${vnum} --out=${MotionMatrixFolder}/${MotionMatrixPrefix}${vnum}_gdc_warp.nii.gz
     convert_motion_distortion_warp = pe.MapNode(
         interface=fsl.ConvertWarp(),
@@ -4282,15 +4296,15 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
     convert_motion_distortion_warp.inputs.out_relwarp = True
     convert_motion_distortion_warp.inputs.relwarp = True
 
-    wf.connect(
-        multiply_func_roi_by_zero, "out_file", convert_motion_distortion_warp, "warp1"
-    )
-
-    wf.connect(split_func, "out_files", convert_motion_distortion_warp, "reference")
+    wf.connect(match_fov_func, "out_file", convert_motion_distortion_warp, "reference")
 
     node, out = strat_pool.get_data("coordinate-transformation")
     wf.connect(node, out, convert_motion_distortion_warp, "postmat")
 
+    if strat_pool.check_rpool("gradient-distortion-field"):
+        node, out = strat_pool.get_data("gradient-distortion-field")
+        wf.connect(node, out, convert_motion_distortion_warp, "warp1")
+
     # convertwarp --relout --rel --ref=${WD}/${T1wImageFile}.${FinalfMRIResolution} --warp1=${MotionMatrixFolder}/${MotionMatrixPrefix}${vnum}_gdc_warp.nii.gz --warp2=${OutputTransform} --out=${MotionMatrixFolder}/${MotionMatrixPrefix}${vnum}_all_warp.nii.gz
     convert_registration_warp = pe.MapNode(
         interface=fsl.ConvertWarp(),
@@ -4314,17 +4328,6 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
         convert_func_to_standard_warp, "out_file", convert_registration_warp, "warp2"
     )
 
-    # fslmaths ${WD}/prevols/vol${vnum}.nii.gz -mul 0 -add 1 ${WD}/prevols/vol${vnum}_mask.nii.gz
-    generate_vol_mask = pe.MapNode(
-        interface=fsl.maths.MathsCommand(),
-        name=f"generate_mask_{pipe_num}",
-        iterfield=["in_file"],
-    )
-
-    generate_vol_mask.inputs.args = "-mul 0 -add 1"
-
-    wf.connect(split_func, "out_files", generate_vol_mask, "in_file")
-
     # applywarp --rel --interp=spline --in=${WD}/prevols/vol${vnum}.nii.gz --warp=${MotionMatrixFolder}/${MotionMatrixPrefix}${vnum}_all_warp.nii.gz --ref=${WD}/${T1wImageFile}.${FinalfMRIResolution} --out=${WD}/postvols/vol${vnum}.nii.gz
     applywarp_func_to_standard = pe.MapNode(
         interface=fsl.ApplyWarp(),
@@ -4332,10 +4335,9 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
         iterfield=["in_file", "field_file"],
     )
 
-    applywarp_func_to_standard.inputs.relwarp = True
     applywarp_func_to_standard.inputs.interp = "spline"
 
-    wf.connect(split_func, "out_files", applywarp_func_to_standard, "in_file")
+    wf.connect(match_fov_func, "out_file", applywarp_func_to_standard, "in_file")
 
     wf.connect(
         convert_registration_warp, "out_file", applywarp_func_to_standard, "field_file"
@@ -4353,11 +4355,11 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
         iterfield=["in_file", "field_file"],
     )
 
-    applywarp_func_mask_to_standard.inputs.relwarp = True
     applywarp_func_mask_to_standard.inputs.interp = "nn"
 
+    node, out = strat_pool.get_data("space-template_desc-bold_mask")
     wf.connect(
-        generate_vol_mask, "out_file", applywarp_func_mask_to_standard, "in_file"
+        node, out, applywarp_func_mask_to_standard, "in_file"
     )
 
     wf.connect(
@@ -4408,41 +4410,35 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
 
     wf.connect(merge_func_mask_to_standard, "merged_file", find_min_mask, "in_file")
 
-    # Combine transformations: gradient non-linearity distortion + fMRI_dc to standard
-    # convertwarp --relout --rel --ref=${WD}/${T1wImageFile}.${FinalfMRIResolution} --warp1=${GradientDistortionField} --warp2=${OutputTransform} --out=${WD}/Scout_gdc_MNI_warp.nii.gz
-    convert_dc_warp = pe.Node(
-        interface=fsl.ConvertWarp(), name=f"convert_dc_warp_{pipe_num}"
+    # Match FOV scout_to_standard
+    match_fov_scout_to_standard = pe.MapNode(
+        interface=fsl.FLIRT(apply_xfm=True, interp="spline"), name=f"match_fov_scout_to_standard_{pipe_num}", iterfield=["in_file"]
     )
-
-    convert_dc_warp.inputs.out_relwarp = True
-    convert_dc_warp.inputs.relwarp = True
+    wf.connect(identity_node, "identity_file", match_fov_scout_to_standard, "in_matrix_file")
+    node, out = strat_pool.get_data("motion-basefile")
+    wf.connect(node, out, match_fov_scout_to_standard, "in_file")
 
     node, out = strat_pool.get_data("space-template_res-bold_desc-head_T1w")
     wf.connect(
-        node, out, convert_dc_warp, "reference",
+        node, out, match_fov_scout_to_standard, "reference"
     )
 
-    wf.connect(multiply_func_roi_by_zero, "out_file", convert_dc_warp, "warp1")
-
-    wf.connect(convert_func_to_standard_warp, "out_file", convert_dc_warp, "warp2")
-
     # applywarp --rel --interp=spline --in=${ScoutInput} -w ${WD}/Scout_gdc_MNI_warp.nii.gz -r ${WD}/${T1wImageFile}.${FinalfMRIResolution} -o ${ScoutOutput}
     applywarp_scout = pe.Node(
         interface=fsl.ApplyWarp(), name=f"applywarp_scout_input_{pipe_num}"
     )
 
-    applywarp_scout.inputs.relwarp = True
     applywarp_scout.inputs.interp = "spline"
 
-    node, out = strat_pool.get_data("motion-basefile")
-    wf.connect(node, out, applywarp_scout, "in_file")
+    wf.connect(match_fov_scout_to_standard, "out_file", applywarp_scout, "in_file")
 
     node, out = strat_pool.get_data("space-template_res-bold_desc-head_T1w")
     wf.connect(
         node, out, applywarp_scout, "ref_file",
     )
 
-    wf.connect(convert_dc_warp, "out_file", applywarp_scout, "field_file")
+    # warp field is just fMRI->standard (skip GDC)
+    wf.connect(convert_func_to_standard_warp, "out_file", applywarp_scout, "field_file")
 
     # https://github.com/DCAN-Labs/DCAN-HCP/blob/1214767/fMRIVolume/scripts/IntensityNormalization.sh#L124-L127
     # fslmaths ${InputfMRI} -mas ${BrainMask} -mas ${InputfMRI}_mask -thr 0 -ing 10000 ${OutputfMRI} -odt float
@@ -5597,3 +5593,37 @@ def _warp_return(
     if apply_xfm is None:
         return wf, {}
     return wf, outputs
+
+
+def create_identity_matrix(workdir):
+    """Create an identity matrix for FLIRT."""
+    identity_file = Path(workdir) / "identity.mat"
+    np.savetxt(identity_file, np.eye(4), fmt="%.6f")
+    return str(identity_file)
+
+def build_match_fov_wf(name, workdir, pipe_num):
+    """
+    Workflow to match Field-of-View for T1w or functional images
+    using an identity matrix.
+    """
+    wf = Workflow(name=name)
+    
+    identity_node = Node(
+        Function(
+            input_names=["workdir"],
+            output_names=["identity_file"],
+            function=create_identity_matrix
+        ),
+        name=f"create_identity_matrix_{pipe_num}"
+    )
+    identity_node.inputs.workdir = workdir
+
+    match_fov_node = MapNode(
+        interface=fsl.FLIRT(apply_xfm=True, interp="spline"),
+        name=f"match_fov_{pipe_num}",
+        iterfield=["in_file"]
+    )
+    
+    wf.connect(identity_node, "identity_file", match_fov_node, "in_matrix_file")
+
+    return wf, match_fov_node
\ No newline at end of file

From 262c2fc528b07cb8e70426de8fee0790cc80b150 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Tue, 26 Aug 2025 16:14:21 +0000
Subject: [PATCH 03/17] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 CPAC/func_preproc/func_preproc.py |  4 +-
 CPAC/pipeline/cpac_pipeline.py    |  2 +-
 CPAC/registration/registration.py | 73 +++++++++++++++++++------------
 3 files changed, 48 insertions(+), 31 deletions(-)

diff --git a/CPAC/func_preproc/func_preproc.py b/CPAC/func_preproc/func_preproc.py
index c787b06f3..43658bbec 100644
--- a/CPAC/func_preproc/func_preproc.py
+++ b/CPAC/func_preproc/func_preproc.py
@@ -1926,9 +1926,7 @@ def template_space_bold_masking(
     func_apply_mask.inputs.expr = "a*b"
     func_apply_mask.inputs.outputtype = "NIFTI_GZ"
 
-    node_head_bold, out_head_bold = strat_pool.get_data(
-        "space-template_desc-head_bold"
-    )
+    node_head_bold, out_head_bold = strat_pool.get_data("space-template_desc-head_bold")
     wf.connect(node_head_bold, out_head_bold, func_apply_mask, "in_file_a")
 
     node, out = strat_pool.get_data("space-template_desc-bold_mask")
diff --git a/CPAC/pipeline/cpac_pipeline.py b/CPAC/pipeline/cpac_pipeline.py
index 6546a1324..b9e686593 100644
--- a/CPAC/pipeline/cpac_pipeline.py
+++ b/CPAC/pipeline/cpac_pipeline.py
@@ -1484,7 +1484,7 @@ def build_workflow(subject_id, sub_dict, cfg, pipeline_name=None):
         pipeline_blocks += [
             template_space_bold_masking,
         ]
-        
+
     # Template-space nuisance regression
     nuisance_template = (
         cfg["nuisance_corrections", "2-nuisance_regression", "space"] == "template"
diff --git a/CPAC/registration/registration.py b/CPAC/registration/registration.py
index c2bdb6d60..d42f66095 100644
--- a/CPAC/registration/registration.py
+++ b/CPAC/registration/registration.py
@@ -22,7 +22,7 @@
 from voluptuous import RequiredFieldInvalid
 from nipype.interfaces import afni, ants, c3, fsl, utility as util
 from nipype.interfaces.afni import utils as afni_utils
-from pathlib import Path 
+from pathlib import Path
 
 from CPAC.anat_preproc.lesion_preproc import create_lesion_preproc
 from CPAC.func_preproc.func_preproc import fsl_afni_subworkflow
@@ -4202,14 +4202,14 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
             input_names=["workdir"],
             output_names=["identity_file"],
             function=lambda workdir: (
-                np.savetxt(Path(workdir) / "identity.mat", np.eye(4), fmt="%.6f") or
-                str(Path(workdir) / "identity.mat")
-            )
+                np.savetxt(Path(workdir) / "identity.mat", np.eye(4), fmt="%.6f")
+                or str(Path(workdir) / "identity.mat")
+            ),
         ),
-        name=f"create_identity_matrix_{pipe_num}"
+        name=f"create_identity_matrix_{pipe_num}",
     )
     identity_node.inputs.workdir = str(Path.cwd())
-        
+
     convert_func_to_anat_linear_warp = pe.Node(
         interface=fsl.ConvertWarp(), name=f"convert_func_to_anat_linear_warp_{pipe_num}"
     )
@@ -4248,7 +4248,8 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
 
     node, out = strat_pool.get_data("space-template_res-bold_desc-head_T1w")
     wf.connect(
-        node, out,
+        node,
+        out,
         convert_func_to_standard_warp,
         "reference",
     )
@@ -4278,7 +4279,9 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
     ### Loop starts! ###
     # Match FOV func_to_standard
     match_fov_func = pe.MapNode(
-        interface=fsl.FLIRT(apply_xfm=True, interp="spline"), name=f"match_fov_func_{pipe_num}", iterfield=["in_file"]
+        interface=fsl.FLIRT(apply_xfm=True, interp="spline"),
+        name=f"match_fov_func_{pipe_num}",
+        iterfield=["in_file"],
     )
     wf.connect(identity_node, "identity_file", match_fov_func, "in_matrix_file")
     wf.connect(split_func, "out_files", match_fov_func, "in_file")
@@ -4317,7 +4320,10 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
 
     node, out = strat_pool.get_data("space-template_res-bold_desc-head_T1w")
     wf.connect(
-        node, out, convert_registration_warp, "reference",
+        node,
+        out,
+        convert_registration_warp,
+        "reference",
     )
 
     wf.connect(
@@ -4345,7 +4351,10 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
 
     node, out = strat_pool.get_data("space-template_res-bold_desc-head_T1w")
     wf.connect(
-        node, out, applywarp_func_to_standard, "ref_file",
+        node,
+        out,
+        applywarp_func_to_standard,
+        "ref_file",
     )
 
     # applywarp --rel --interp=nn --in=${WD}/prevols/vol${vnum}_mask.nii.gz --warp=${MotionMatrixFolder}/${MotionMatrixPrefix}${vnum}_all_warp.nii.gz --ref=${WD}/${T1wImageFile}.${FinalfMRIResolution} --out=${WD}/postvols/vol${vnum}_mask.nii.gz
@@ -4358,9 +4367,7 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
     applywarp_func_mask_to_standard.inputs.interp = "nn"
 
     node, out = strat_pool.get_data("space-template_desc-bold_mask")
-    wf.connect(
-        node, out, applywarp_func_mask_to_standard, "in_file"
-    )
+    wf.connect(node, out, applywarp_func_mask_to_standard, "in_file")
 
     wf.connect(
         convert_registration_warp,
@@ -4371,7 +4378,10 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
 
     node, out = strat_pool.get_data("space-template_res-bold_desc-head_T1w")
     wf.connect(
-        node, out, applywarp_func_mask_to_standard, "ref_file",
+        node,
+        out,
+        applywarp_func_mask_to_standard,
+        "ref_file",
     )
 
     ### Loop ends! ###
@@ -4412,16 +4422,18 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
 
     # Match FOV scout_to_standard
     match_fov_scout_to_standard = pe.MapNode(
-        interface=fsl.FLIRT(apply_xfm=True, interp="spline"), name=f"match_fov_scout_to_standard_{pipe_num}", iterfield=["in_file"]
+        interface=fsl.FLIRT(apply_xfm=True, interp="spline"),
+        name=f"match_fov_scout_to_standard_{pipe_num}",
+        iterfield=["in_file"],
+    )
+    wf.connect(
+        identity_node, "identity_file", match_fov_scout_to_standard, "in_matrix_file"
     )
-    wf.connect(identity_node, "identity_file", match_fov_scout_to_standard, "in_matrix_file")
     node, out = strat_pool.get_data("motion-basefile")
     wf.connect(node, out, match_fov_scout_to_standard, "in_file")
 
     node, out = strat_pool.get_data("space-template_res-bold_desc-head_T1w")
-    wf.connect(
-        node, out, match_fov_scout_to_standard, "reference"
-    )
+    wf.connect(node, out, match_fov_scout_to_standard, "reference")
 
     # applywarp --rel --interp=spline --in=${ScoutInput} -w ${WD}/Scout_gdc_MNI_warp.nii.gz -r ${WD}/${T1wImageFile}.${FinalfMRIResolution} -o ${ScoutOutput}
     applywarp_scout = pe.Node(
@@ -4434,7 +4446,10 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
 
     node, out = strat_pool.get_data("space-template_res-bold_desc-head_T1w")
     wf.connect(
-        node, out, applywarp_scout, "ref_file",
+        node,
+        out,
+        applywarp_scout,
+        "ref_file",
     )
 
     # warp field is just fMRI->standard (skip GDC)
@@ -4446,7 +4461,10 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
 
     node, out = strat_pool.get_data("space-template_desc-bold_mask")
     wf.connect(
-        node, out, merge_func_mask, "in1",
+        node,
+        out,
+        merge_func_mask,
+        "in1",
     )
 
     wf.connect(find_min_mask, "out_file", merge_func_mask, "in2")
@@ -5601,29 +5619,30 @@ def create_identity_matrix(workdir):
     np.savetxt(identity_file, np.eye(4), fmt="%.6f")
     return str(identity_file)
 
+
 def build_match_fov_wf(name, workdir, pipe_num):
     """
     Workflow to match Field-of-View for T1w or functional images
     using an identity matrix.
     """
     wf = Workflow(name=name)
-    
+
     identity_node = Node(
         Function(
             input_names=["workdir"],
             output_names=["identity_file"],
-            function=create_identity_matrix
+            function=create_identity_matrix,
         ),
-        name=f"create_identity_matrix_{pipe_num}"
+        name=f"create_identity_matrix_{pipe_num}",
     )
     identity_node.inputs.workdir = workdir
 
     match_fov_node = MapNode(
         interface=fsl.FLIRT(apply_xfm=True, interp="spline"),
         name=f"match_fov_{pipe_num}",
-        iterfield=["in_file"]
+        iterfield=["in_file"],
     )
-    
+
     wf.connect(identity_node, "identity_file", match_fov_node, "in_matrix_file")
 
-    return wf, match_fov_node
\ No newline at end of file
+    return wf, match_fov_node

From 713f451b597daba3e39f4ae290a41811dccf599d Mon Sep 17 00:00:00 2001
From: "birajstha:construction_worker::penguin" <birajstha@gmail.com>
Date: Wed, 27 Aug 2025 15:08:46 -0400
Subject: [PATCH 04/17] moving the reference flag from inside of bbreg to
 coregistration

---
 CPAC/pipeline/schema.py                       |   2 +-
 CPAC/registration/registration.py             | 138 ++++++------------
 .../configs/pipeline_config_abcd-options.yml  |   5 +-
 .../configs/pipeline_config_blank.yml         |  10 +-
 .../configs/pipeline_config_default.yml       |  10 +-
 .../pipeline_config_fmriprep-options.yml      |   7 +-
 6 files changed, 59 insertions(+), 113 deletions(-)

diff --git a/CPAC/pipeline/schema.py b/CPAC/pipeline/schema.py
index 2785f6d8a..abfb7a3c4 100644
--- a/CPAC/pipeline/schema.py
+++ b/CPAC/pipeline/schema.py
@@ -843,12 +843,12 @@ def sanitize(filename):
                         },
                         "mask_sbref": bool1_1,
                     },
+                    "reference": In({"whole-head", "brain"}),
                     "boundary_based_registration": {
                         "run": forkable,
                         "bbr_schedule": str,
                         "bbr_wm_map": In({"probability_map", "partial_volume_map"}),
                         "bbr_wm_mask_args": str,
-                        "reference": In({"whole-head", "brain"}),
                     },
                 },
                 "EPI_registration": {
diff --git a/CPAC/registration/registration.py b/CPAC/registration/registration.py
index d42f66095..a8da814e9 100644
--- a/CPAC/registration/registration.py
+++ b/CPAC/registration/registration.py
@@ -22,7 +22,6 @@
 from voluptuous import RequiredFieldInvalid
 from nipype.interfaces import afni, ants, c3, fsl, utility as util
 from nipype.interfaces.afni import utils as afni_utils
-from pathlib import Path
 
 from CPAC.anat_preproc.lesion_preproc import create_lesion_preproc
 from CPAC.func_preproc.func_preproc import fsl_afni_subworkflow
@@ -3068,7 +3067,9 @@ def overwrite_transform_anat_to_template(wf, cfg, strat_pool, pipe_num, opt=None
         wf.connect(merge_inv_xfms_to_list, "out", merge_inv_xfms, "in_files")
 
         # Match FOVs using flirt -in infile -ref MNI152_T1_1mm_resample.nii.gz -out my_T1w_resampled.nii.gz -applyxfm -usesqform
-        match_fovs_T1w = pe.Node(interface=fsl.FLIRT(), name=f"match_fovs_T1w_{pipe_num}")
+        match_fovs_T1w = pe.Node(
+            interface=fsl.FLIRT(), name=f"match_fovs_T1w_{pipe_num}"
+        )
         match_fovs_T1w.inputs.apply_xfm = True
         match_fovs_T1w.inputs.uses_qform = True
 
@@ -3091,7 +3092,9 @@ def overwrite_transform_anat_to_template(wf, cfg, strat_pool, pipe_num, opt=None
             merge_xfms, "merged_file", fsl_apply_warp_t1_to_template, "field_file"
         )
 
-        match_fovs_T1w_brain = pe.Node(interface=fsl.FLIRT(), name=f"match_fovs_T1w_brain_{pipe_num}")
+        match_fovs_T1w_brain = pe.Node(
+            interface=fsl.FLIRT(), name=f"match_fovs_T1w_brain_{pipe_num}"
+        )
         match_fovs_T1w_brain.inputs.apply_xfm = True
         match_fovs_T1w_brain.inputs.uses_qform = True
 
@@ -3105,7 +3108,12 @@ def overwrite_transform_anat_to_template(wf, cfg, strat_pool, pipe_num, opt=None
         # TODO connect T1wRestoreBrain, check T1wRestoreBrain quality
         node, out = strat_pool.get_data(["desc-restore-brain_T1w", "desc-preproc_T1w"])
         wf.connect(node, out, match_fovs_T1w_brain, "in_file")
-        wf.connect(match_fovs_T1w_brain, "out_file", fsl_apply_warp_t1_brain_to_template, "in_file")
+        wf.connect(
+            match_fovs_T1w_brain,
+            "out_file",
+            fsl_apply_warp_t1_brain_to_template,
+            "in_file",
+        )
 
         node, out = strat_pool.get_data("T1w-brain-template")
         wf.connect(node, out, match_fovs_T1w_brain, "reference")
@@ -3115,7 +3123,9 @@ def overwrite_transform_anat_to_template(wf, cfg, strat_pool, pipe_num, opt=None
             merge_xfms, "merged_file", fsl_apply_warp_t1_brain_to_template, "field_file"
         )
 
-        match_fovs_T1w_brain_mask = pe.Node(interface=fsl.FLIRT(), name=f"match_fovs_T1w_brain_mask_{pipe_num}")
+        match_fovs_T1w_brain_mask = pe.Node(
+            interface=fsl.FLIRT(), name=f"match_fovs_T1w_brain_mask_{pipe_num}"
+        )
         match_fovs_T1w_brain_mask.inputs.apply_xfm = True
         match_fovs_T1w_brain_mask.inputs.uses_qform = True
 
@@ -3128,7 +3138,12 @@ def overwrite_transform_anat_to_template(wf, cfg, strat_pool, pipe_num, opt=None
 
         node, out = strat_pool.get_data("space-T1w_desc-brain_mask")
         wf.connect(node, out, match_fovs_T1w_brain_mask, "in_file")
-        wf.connect(match_fovs_T1w_brain_mask, "out_file", fsl_apply_warp_t1_brain_mask_to_template, "in_file")
+        wf.connect(
+            match_fovs_T1w_brain_mask,
+            "out_file",
+            fsl_apply_warp_t1_brain_mask_to_template,
+            "in_file",
+        )
 
         node, out = strat_pool.get_data("T1w-brain-template-mask")
         wf.connect(node, out, match_fovs_T1w_brain_mask, "reference")
@@ -3335,6 +3350,7 @@ def coregistration_prep_fmriprep(wf, cfg, strat_pool, pipe_num, opt=None):
         (
             "desc-preproc_T1w",
             ["desc-restore-brain_T1w", "desc-preproc_T1w"],
+            ["desc-restore_T1w", "desc-head_T1w"],
             "desc-preproc_T2w",
             "desc-preproc_T2w",
             "T2w",
@@ -3405,7 +3421,18 @@ def coregistration(wf, cfg, strat_pool, pipe_num, opt=None):
         node, out = strat_pool.get_data("sbref")
         wf.connect(node, out, func_to_anat, "inputspec.func")
 
-        node, out = strat_pool.get_data(["desc-restore-brain_T1w", "desc-preproc_T1w"])
+        if (
+            cfg.registration_workflows["functional_registration"]["coregistration"][
+                "reference"
+            ]
+            == "whole-head"
+        ):
+            node, out = strat_pool.get_data(["desc-restore_T1w", "desc-head_T1w"])
+        else:
+            node, out = strat_pool.get_data(
+                ["desc-restore-brain_T1w", "desc-preproc_T1w"]
+            )
+
         wf.connect(node, out, func_to_anat, "inputspec.anat")
 
     if diff_complete:
@@ -3466,8 +3493,8 @@ def coregistration(wf, cfg, strat_pool, pipe_num, opt=None):
 
         if (
             cfg.registration_workflows["functional_registration"]["coregistration"][
-                "boundary_based_registration"
-            ]["reference"]
+                "reference"
+            ]
             == "whole-head"
         ):
             node, out = strat_pool.get_data("desc-head_T1w")
@@ -3475,8 +3502,8 @@ def coregistration(wf, cfg, strat_pool, pipe_num, opt=None):
 
         elif (
             cfg.registration_workflows["functional_registration"]["coregistration"][
-                "boundary_based_registration"
-            ]["reference"]
+                "reference"
+            ]
             == "brain"
         ):
             node, out = strat_pool.get_data("desc-preproc_T1w")
@@ -4195,21 +4222,6 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
     https://github.com/DCAN-Labs/DCAN-HCP/blob/a8d495a/fMRIVolume/scripts/DistortionCorrectionAndEPIToT1wReg_FLIRTBBRAndFreeSurferBBRbased.sh#L548
     convertwarp --relout --rel -m ${WD}/fMRI2str.mat --ref=${T1wImage} --out=${WD}/fMRI2str.nii.gz
     """
-    # Identity matrix node needed for matching FOV
-    identity_node = pe.Node(
-        Function(
-            imports=["from pathlib import Path", "import numpy as np"],
-            input_names=["workdir"],
-            output_names=["identity_file"],
-            function=lambda workdir: (
-                np.savetxt(Path(workdir) / "identity.mat", np.eye(4), fmt="%.6f")
-                or str(Path(workdir) / "identity.mat")
-            ),
-        ),
-        name=f"create_identity_matrix_{pipe_num}",
-    )
-    identity_node.inputs.workdir = str(Path.cwd())
-
     convert_func_to_anat_linear_warp = pe.Node(
         interface=fsl.ConvertWarp(), name=f"convert_func_to_anat_linear_warp_{pipe_num}"
     )
@@ -4277,18 +4289,6 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
     wf.connect(node, out, split_func, "in_file")
 
     ### Loop starts! ###
-    # Match FOV func_to_standard
-    match_fov_func = pe.MapNode(
-        interface=fsl.FLIRT(apply_xfm=True, interp="spline"),
-        name=f"match_fov_func_{pipe_num}",
-        iterfield=["in_file"],
-    )
-    wf.connect(identity_node, "identity_file", match_fov_func, "in_matrix_file")
-    wf.connect(split_func, "out_files", match_fov_func, "in_file")
-
-    node, out = strat_pool.get_data("space-template_res-bold_desc-head_T1w")
-    wf.connect(node, out, match_fov_func, "reference")
-
     # convertwarp --relout --rel --ref=${WD}/prevols/vol${vnum}.nii.gz --warp1=${GradientDistortionField} --postmat=${MotionMatrixFolder}/${MotionMatrixPrefix}${vnum} --out=${MotionMatrixFolder}/${MotionMatrixPrefix}${vnum}_gdc_warp.nii.gz
     convert_motion_distortion_warp = pe.MapNode(
         interface=fsl.ConvertWarp(),
@@ -4299,7 +4299,7 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
     convert_motion_distortion_warp.inputs.out_relwarp = True
     convert_motion_distortion_warp.inputs.relwarp = True
 
-    wf.connect(match_fov_func, "out_file", convert_motion_distortion_warp, "reference")
+    wf.connect(split_func, "out_files", convert_motion_distortion_warp, "reference")
 
     node, out = strat_pool.get_data("coordinate-transformation")
     wf.connect(node, out, convert_motion_distortion_warp, "postmat")
@@ -4341,9 +4341,10 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
         iterfield=["in_file", "field_file"],
     )
 
+    applywarp_func_to_standard.inputs.relwarp = True
     applywarp_func_to_standard.inputs.interp = "spline"
 
-    wf.connect(match_fov_func, "out_file", applywarp_func_to_standard, "in_file")
+    wf.connect(split_func, "out_files", applywarp_func_to_standard, "in_file")
 
     wf.connect(
         convert_registration_warp, "out_file", applywarp_func_to_standard, "field_file"
@@ -4364,9 +4365,10 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
         iterfield=["in_file", "field_file"],
     )
 
+    applywarp_func_mask_to_standard.inputs.relwarp = True
     applywarp_func_mask_to_standard.inputs.interp = "nn"
 
-    node, out = strat_pool.get_data("space-template_desc-bold_mask")
+    node, out = strat_pool.get_data("space-template_desc-brain_mask")
     wf.connect(node, out, applywarp_func_mask_to_standard, "in_file")
 
     wf.connect(
@@ -4420,29 +4422,16 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
 
     wf.connect(merge_func_mask_to_standard, "merged_file", find_min_mask, "in_file")
 
-    # Match FOV scout_to_standard
-    match_fov_scout_to_standard = pe.MapNode(
-        interface=fsl.FLIRT(apply_xfm=True, interp="spline"),
-        name=f"match_fov_scout_to_standard_{pipe_num}",
-        iterfield=["in_file"],
-    )
-    wf.connect(
-        identity_node, "identity_file", match_fov_scout_to_standard, "in_matrix_file"
-    )
-    node, out = strat_pool.get_data("motion-basefile")
-    wf.connect(node, out, match_fov_scout_to_standard, "in_file")
-
-    node, out = strat_pool.get_data("space-template_res-bold_desc-head_T1w")
-    wf.connect(node, out, match_fov_scout_to_standard, "reference")
-
     # applywarp --rel --interp=spline --in=${ScoutInput} -w ${WD}/Scout_gdc_MNI_warp.nii.gz -r ${WD}/${T1wImageFile}.${FinalfMRIResolution} -o ${ScoutOutput}
     applywarp_scout = pe.Node(
         interface=fsl.ApplyWarp(), name=f"applywarp_scout_input_{pipe_num}"
     )
 
+    applywarp_scout.inputs.relwarp = True
     applywarp_scout.inputs.interp = "spline"
 
-    wf.connect(match_fov_scout_to_standard, "out_file", applywarp_scout, "in_file")
+    node, out = strat_pool.get_data("motion-basefile")
+    wf.connect(node, out, applywarp_scout, "in_file")
 
     node, out = strat_pool.get_data("space-template_res-bold_desc-head_T1w")
     wf.connect(
@@ -5611,38 +5600,3 @@ def _warp_return(
     if apply_xfm is None:
         return wf, {}
     return wf, outputs
-
-
-def create_identity_matrix(workdir):
-    """Create an identity matrix for FLIRT."""
-    identity_file = Path(workdir) / "identity.mat"
-    np.savetxt(identity_file, np.eye(4), fmt="%.6f")
-    return str(identity_file)
-
-
-def build_match_fov_wf(name, workdir, pipe_num):
-    """
-    Workflow to match Field-of-View for T1w or functional images
-    using an identity matrix.
-    """
-    wf = Workflow(name=name)
-
-    identity_node = Node(
-        Function(
-            input_names=["workdir"],
-            output_names=["identity_file"],
-            function=create_identity_matrix,
-        ),
-        name=f"create_identity_matrix_{pipe_num}",
-    )
-    identity_node.inputs.workdir = workdir
-
-    match_fov_node = MapNode(
-        interface=fsl.FLIRT(apply_xfm=True, interp="spline"),
-        name=f"match_fov_{pipe_num}",
-        iterfield=["in_file"],
-    )
-
-    wf.connect(identity_node, "identity_file", match_fov_node, "in_matrix_file")
-
-    return wf, match_fov_node
diff --git a/CPAC/resources/configs/pipeline_config_abcd-options.yml b/CPAC/resources/configs/pipeline_config_abcd-options.yml
index 844def45a..ee961a7ff 100644
--- a/CPAC/resources/configs/pipeline_config_abcd-options.yml
+++ b/CPAC/resources/configs/pipeline_config_abcd-options.yml
@@ -217,14 +217,15 @@ registration_workflows:
         # Mask the sbref created by coregistration input prep nodeblocks above before registration
         mask_sbref: Off
 
+      # options: 'whole-head' or 'brain'
+      reference: whole-head
+
       # Choose coregistration interpolation
       interpolation: spline
 
       # Choose coregistration degree of freedom
       dof: 12
 
-
-
     func_registration_to_template:
 
       # these options modify the application (to the functional data), not the calculation, of the
diff --git a/CPAC/resources/configs/pipeline_config_blank.yml b/CPAC/resources/configs/pipeline_config_blank.yml
index fd1686a21..008090280 100644
--- a/CPAC/resources/configs/pipeline_config_blank.yml
+++ b/CPAC/resources/configs/pipeline_config_blank.yml
@@ -738,16 +738,15 @@ registration_workflows:
         # Mask the sbref created by coregistration input prep nodeblocks above before registration
         mask_sbref: On
 
+      # options: 'whole-head' or 'brain'
+      reference: whole-head
+
       boundary_based_registration:
 
         # this is a fork point
         #   run: [On, Off] - this will run both and fork the pipeline
         run: [Off]
 
-        # reference for boundary based registration
-        # options: 'whole-head' or 'brain'
-        reference: whole-head
-
         # choose which FAST map to generate BBR WM mask
         # options: 'probability_map', 'partial_volume_map'
         bbr_wm_map: probability_map
@@ -759,9 +758,6 @@ registration_workflows:
         # It is not necessary to change this path unless you intend to use non-standard MNI registration.
         bbr_schedule: $FSLDIR/etc/flirtsch/bbr.sch
 
-      # Choose FSL or ABCD as coregistration method
-      using: FSL
-
       # Choose coregistration interpolation
       interpolation: trilinear
 
diff --git a/CPAC/resources/configs/pipeline_config_default.yml b/CPAC/resources/configs/pipeline_config_default.yml
index cba22d6a0..c69cc8d4b 100644
--- a/CPAC/resources/configs/pipeline_config_default.yml
+++ b/CPAC/resources/configs/pipeline_config_default.yml
@@ -775,9 +775,6 @@ registration_workflows:
 
       run: On
 
-      # Choose FSL or ABCD as coregistration method
-      using: FSL
-
       # Choose coregistration interpolation
       interpolation: trilinear
 
@@ -811,6 +808,9 @@ registration_workflows:
         # Mask the sbref created by coregistration input prep nodeblocks above before registration
         mask_sbref: On
 
+      # options: 'whole-head' or 'brain'
+      reference: whole-head
+
       boundary_based_registration:
         # this is a fork point
         #   run: [On, Off] - this will run both and fork the pipeline
@@ -820,10 +820,6 @@ registration_workflows:
         # It is not necessary to change this path unless you intend to use non-standard MNI registration.
         bbr_schedule: $FSLDIR/etc/flirtsch/bbr.sch
 
-        # reference for boundary based registration
-        # options: 'whole-head' or 'brain'
-        reference: whole-head
-
         # choose which FAST map to generate BBR WM mask
         # options: 'probability_map', 'partial_volume_map'
         bbr_wm_map: 'probability_map'
diff --git a/CPAC/resources/configs/pipeline_config_fmriprep-options.yml b/CPAC/resources/configs/pipeline_config_fmriprep-options.yml
index 5453144af..2b268930a 100644
--- a/CPAC/resources/configs/pipeline_config_fmriprep-options.yml
+++ b/CPAC/resources/configs/pipeline_config_fmriprep-options.yml
@@ -251,16 +251,15 @@ registration_workflows:
         # input: ['Mean_Functional', 'Selected_Functional_Volume', 'fmriprep_reference']
         input: [fmriprep_reference]
 
+      # options: 'whole-head' or 'brain'
+      reference: brain
+
       boundary_based_registration:
 
         # this is a fork point
         #   run: [On, Off] - this will run both and fork the pipeline
         run: [On]
 
-        # reference for boundary based registration
-        # options: 'whole-head' or 'brain'
-        reference: brain
-
         # choose which FAST map to generate BBR WM mask
         # options: 'probability_map', 'partial_volume_map'
         bbr_wm_map: partial_volume_map

From e9ba975098b09382ed976f2964caca4dab7245f2 Mon Sep 17 00:00:00 2001
From: "birajstha:construction_worker::penguin" <birajstha@gmail.com>
Date: Wed, 27 Aug 2025 16:25:52 -0400
Subject: [PATCH 05/17] adding ref_weight in FLIRT whole head registration

---
 CPAC/registration/registration.py | 33 ++++++++++++++++++++++++++++---
 1 file changed, 30 insertions(+), 3 deletions(-)

diff --git a/CPAC/registration/registration.py b/CPAC/registration/registration.py
index a8da814e9..c3d63f43c 100644
--- a/CPAC/registration/registration.py
+++ b/CPAC/registration/registration.py
@@ -711,6 +711,12 @@ def create_register_func_to_anat(
         inputspec.interp : string
             Type of interpolation to use
             ('trilinear' or 'nearestneighbour' or 'sinc')
+        inputspec.ref_weight : string (nifti file)
+            Reference weight image for registration
+        inputspec.fieldmap : string (nifti file)
+            Field map image for registration
+        inputspec.fieldmapmask : string (nifti file)
+            Field map mask image for registration
 
     Workflow Outputs::
 
@@ -723,7 +729,15 @@ def create_register_func_to_anat(
 
     inputspec = pe.Node(
         util.IdentityInterface(
-            fields=["func", "anat", "dof", "interp", "fieldmap", "fieldmapmask"]
+            fields=[
+                "func",
+                "anat",
+                "dof",
+                "interp",
+                "fieldmap",
+                "fieldmapmask",
+                "ref_weight",
+            ]
         ),
         name="inputspec",
     )
@@ -754,6 +768,15 @@ def create_register_func_to_anat(
     linear_reg.inputs.dof = config.registration_workflows["functional_registration"][
         "coregistration"
     ]["dof"]
+
+    if (
+        config.registration_workflows["functional_registration"]["coregistration"][
+            "reference"
+        ]
+        == "whole_head"
+    ):
+        register_func_to_anat.connect(inputspec, "ref_weight", linear_reg, "ref_weight")
+
     if (
         config.registration_workflows["functional_registration"]["coregistration"][
             "arguments"
@@ -3349,6 +3372,7 @@ def coregistration_prep_fmriprep(wf, cfg, strat_pool, pipe_num, opt=None):
         ),
         (
             "desc-preproc_T1w",
+            "space-T1w_desc-brain_mask",
             ["desc-restore-brain_T1w", "desc-preproc_T1w"],
             ["desc-restore_T1w", "desc-head_T1w"],
             "desc-preproc_T2w",
@@ -3428,12 +3452,15 @@ def coregistration(wf, cfg, strat_pool, pipe_num, opt=None):
             == "whole-head"
         ):
             node, out = strat_pool.get_data(["desc-restore_T1w", "desc-head_T1w"])
+            wf.connect(node, out, func_to_anat, "inputspec.anat")
+
+            node, out = strat_pool.get_data("space-T1w_desc-brain_mask")
+            wf.connect(node, out, func_to_anat, "inputspec.ref_weight")
         else:
             node, out = strat_pool.get_data(
                 ["desc-restore-brain_T1w", "desc-preproc_T1w"]
             )
-
-        wf.connect(node, out, func_to_anat, "inputspec.anat")
+            wf.connect(node, out, func_to_anat, "inputspec.anat")
 
     if diff_complete:
         node, out = strat_pool.get_data("effectiveEchoSpacing")

From 4e47f2dbb588b487a2bf5116aca6df0f68eda0ac Mon Sep 17 00:00:00 2001
From: "birajstha:construction_worker::penguin" <birajstha@gmail.com>
Date: Thu, 28 Aug 2025 13:14:33 -0400
Subject: [PATCH 06/17] adding reference whole head

---
 CPAC/registration/registration.py                     |  2 +-
 .../configs/pipeline_config_abcd-options.yml          | 11 +++++++++++
 2 files changed, 12 insertions(+), 1 deletion(-)

diff --git a/CPAC/registration/registration.py b/CPAC/registration/registration.py
index c3d63f43c..65a6f00a8 100644
--- a/CPAC/registration/registration.py
+++ b/CPAC/registration/registration.py
@@ -773,7 +773,7 @@ def create_register_func_to_anat(
         config.registration_workflows["functional_registration"]["coregistration"][
             "reference"
         ]
-        == "whole_head"
+        == "whole-head"
     ):
         register_func_to_anat.connect(inputspec, "ref_weight", linear_reg, "ref_weight")
 
diff --git a/CPAC/resources/configs/pipeline_config_abcd-options.yml b/CPAC/resources/configs/pipeline_config_abcd-options.yml
index ee961a7ff..de7d04a47 100644
--- a/CPAC/resources/configs/pipeline_config_abcd-options.yml
+++ b/CPAC/resources/configs/pipeline_config_abcd-options.yml
@@ -225,6 +225,11 @@ registration_workflows:
 
       # Choose coregistration degree of freedom
       dof: 12
+      boundary_based_registration:
+
+        # this is a fork point
+        #   run: [On, Off] - this will run both and fork the pipeline
+        run: [On]
 
     func_registration_to_template:
 
@@ -263,7 +268,13 @@ registration_workflows:
         # Interpolation method for writing out transformed functional images.
         # Possible values: Linear, BSpline, LanczosWindowedSinc
         interpolation: Linear
+    EPI_registration:
 
+      # directly register the mean functional to an EPI template
+      #   instead of applying the anatomical T1-to-template transform to the functional data that has been
+      #   coregistered to anatomical/T1 space
+      run: on
+      
 functional_preproc:
   run: On
   motion_estimates_and_correction:

From 25453fcf656fa14696002da1c3adaf494d3388e1 Mon Sep 17 00:00:00 2001
From: "birajstha:construction_worker::penguin" <birajstha@gmail.com>
Date: Fri, 29 Aug 2025 18:56:51 -0400
Subject: [PATCH 07/17] concating match_fov to the xfm

---
 CPAC/registration/registration.py | 145 ++++++------------------------
 1 file changed, 28 insertions(+), 117 deletions(-)

diff --git a/CPAC/registration/registration.py b/CPAC/registration/registration.py
index 65a6f00a8..a39d4b3a3 100644
--- a/CPAC/registration/registration.py
+++ b/CPAC/registration/registration.py
@@ -3095,6 +3095,7 @@ def overwrite_transform_anat_to_template(wf, cfg, strat_pool, pipe_num, opt=None
         )
         match_fovs_T1w.inputs.apply_xfm = True
         match_fovs_T1w.inputs.uses_qform = True
+        match_fovs_T1w.inputs.out_matrix_file = "match_fov.mat"
 
         # applywarp --rel --interp=spline -i ${T1wRestore} -r ${Reference} -w ${OutputTransform} -o ${OutputT1wImageRestore}
         fsl_apply_warp_t1_to_template = pe.Node(
@@ -3115,11 +3116,25 @@ def overwrite_transform_anat_to_template(wf, cfg, strat_pool, pipe_num, opt=None
             merge_xfms, "merged_file", fsl_apply_warp_t1_to_template, "field_file"
         )
 
-        match_fovs_T1w_brain = pe.Node(
-            interface=fsl.FLIRT(), name=f"match_fovs_T1w_brain_{pipe_num}"
+        concat_match_fov = pe.Node(interface=fsl.ConvertWarp(), name=f"concat_match_fov_{pipe_num}")
+        concat_match_fov.inputs.relwarp = True
+
+        wf.connect(match_fovs_T1w, "out_matrix_file", concat_match_fov, "premat")
+        wf.connect(merge_xfms, "merged_file", concat_match_fov, "warp1")
+        node, out = strat_pool.get_data("T1w-template")
+        wf.connect(node, out, concat_match_fov, "reference")
+
+        # Node to concatenate the inverse warp with the FOV matrix
+        concat_match_fov_inv = pe.Node(
+            interface=fsl.ConvertWarp(),
+            name=f"concat_match_fov_inv_{pipe_num}"
         )
-        match_fovs_T1w_brain.inputs.apply_xfm = True
-        match_fovs_T1w_brain.inputs.uses_qform = True
+        concat_match_fov_inv.inputs.relwarp = True
+
+        wf.connect(merge_inv_xfms, "merged_file", concat_match_fov_inv, "warp1")
+        wf.connect(match_fovs_T1w, "out_matrix_file", concat_match_fov_inv, "premat")
+        node, out = strat_pool.get_data(["desc-restore_T1w", "desc-head_T1w"])
+        wf.connect(node, out, concat_match_fov_inv, "reference")
 
         # applywarp --rel --interp=nn -i ${T1wRestoreBrain} -r ${Reference} -w ${OutputTransform} -o ${OutputT1wImageRestoreBrain}
         fsl_apply_warp_t1_brain_to_template = pe.Node(
@@ -3130,28 +3145,17 @@ def overwrite_transform_anat_to_template(wf, cfg, strat_pool, pipe_num, opt=None
 
         # TODO connect T1wRestoreBrain, check T1wRestoreBrain quality
         node, out = strat_pool.get_data(["desc-restore-brain_T1w", "desc-preproc_T1w"])
-        wf.connect(node, out, match_fovs_T1w_brain, "in_file")
         wf.connect(
-            match_fovs_T1w_brain,
-            "out_file",
-            fsl_apply_warp_t1_brain_to_template,
-            "in_file",
+            node, out, fsl_apply_warp_t1_brain_to_template, "in_file"
         )
 
         node, out = strat_pool.get_data("T1w-brain-template")
-        wf.connect(node, out, match_fovs_T1w_brain, "reference")
         wf.connect(node, out, fsl_apply_warp_t1_brain_to_template, "ref_file")
 
         wf.connect(
-            merge_xfms, "merged_file", fsl_apply_warp_t1_brain_to_template, "field_file"
+            concat_match_fov, "out_file", fsl_apply_warp_t1_brain_to_template, "field_file"
         )
 
-        match_fovs_T1w_brain_mask = pe.Node(
-            interface=fsl.FLIRT(), name=f"match_fovs_T1w_brain_mask_{pipe_num}"
-        )
-        match_fovs_T1w_brain_mask.inputs.apply_xfm = True
-        match_fovs_T1w_brain_mask.inputs.uses_qform = True
-
         fsl_apply_warp_t1_brain_mask_to_template = pe.Node(
             interface=fsl.ApplyWarp(),
             name=f"FSL-ABCD_T1_brain_mask_to_template_{pipe_num}",
@@ -3160,21 +3164,16 @@ def overwrite_transform_anat_to_template(wf, cfg, strat_pool, pipe_num, opt=None
         fsl_apply_warp_t1_brain_mask_to_template.inputs.interp = "nn"
 
         node, out = strat_pool.get_data("space-T1w_desc-brain_mask")
-        wf.connect(node, out, match_fovs_T1w_brain_mask, "in_file")
         wf.connect(
-            match_fovs_T1w_brain_mask,
-            "out_file",
-            fsl_apply_warp_t1_brain_mask_to_template,
-            "in_file",
+            node, out, fsl_apply_warp_t1_brain_mask_to_template, "in_file"
         )
 
         node, out = strat_pool.get_data("T1w-brain-template-mask")
-        wf.connect(node, out, match_fovs_T1w_brain_mask, "reference")
         wf.connect(node, out, fsl_apply_warp_t1_brain_mask_to_template, "ref_file")
 
         wf.connect(
-            merge_xfms,
-            "merged_file",
+            concat_match_fov,
+            "out_file",
             fsl_apply_warp_t1_brain_mask_to_template,
             "field_file",
         )
@@ -3193,8 +3192,8 @@ def overwrite_transform_anat_to_template(wf, cfg, strat_pool, pipe_num, opt=None
         outputs = {
             "space-template_desc-preproc_T1w": (apply_mask, "out_file"),
             "space-template_desc-head_T1w": (fsl_apply_warp_t1_to_template, "out_file"),
-            "from-T1w_to-template_mode-image_xfm": (merge_xfms, "merged_file"),
-            "from-template_to-T1w_mode-image_xfm": (merge_inv_xfms, "merged_file"),
+            "from-T1w_to-template_mode-image_xfm": (concat_match_fov, "out_file"),
+            "from-template_to-T1w_mode-image_xfm": (concat_match_fov_inv, "out_file"),
         }
 
     else:
@@ -4385,34 +4384,6 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
         "ref_file",
     )
 
-    # applywarp --rel --interp=nn --in=${WD}/prevols/vol${vnum}_mask.nii.gz --warp=${MotionMatrixFolder}/${MotionMatrixPrefix}${vnum}_all_warp.nii.gz --ref=${WD}/${T1wImageFile}.${FinalfMRIResolution} --out=${WD}/postvols/vol${vnum}_mask.nii.gz
-    applywarp_func_mask_to_standard = pe.MapNode(
-        interface=fsl.ApplyWarp(),
-        name=f"applywarp_func_mask_to_standard_{pipe_num}",
-        iterfield=["in_file", "field_file"],
-    )
-
-    applywarp_func_mask_to_standard.inputs.relwarp = True
-    applywarp_func_mask_to_standard.inputs.interp = "nn"
-
-    node, out = strat_pool.get_data("space-template_desc-brain_mask")
-    wf.connect(node, out, applywarp_func_mask_to_standard, "in_file")
-
-    wf.connect(
-        convert_registration_warp,
-        "out_file",
-        applywarp_func_mask_to_standard,
-        "field_file",
-    )
-
-    node, out = strat_pool.get_data("space-template_res-bold_desc-head_T1w")
-    wf.connect(
-        node,
-        out,
-        applywarp_func_mask_to_standard,
-        "ref_file",
-    )
-
     ### Loop ends! ###
 
     # fslmerge -tr ${OutputfMRI} $FrameMergeSTRING $TR_vol
@@ -4426,29 +4397,6 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
         applywarp_func_to_standard, "out_file", merge_func_to_standard, "in_files"
     )
 
-    # fslmerge -tr ${OutputfMRI}_mask $FrameMergeSTRINGII $TR_vol
-    merge_func_mask_to_standard = pe.Node(
-        interface=fslMerge(), name=f"merge_func_mask_to_standard_{pipe_num}"
-    )
-
-    merge_func_mask_to_standard.inputs.dimension = "t"
-
-    wf.connect(
-        applywarp_func_mask_to_standard,
-        "out_file",
-        merge_func_mask_to_standard,
-        "in_files",
-    )
-
-    # fslmaths ${OutputfMRI}_mask -Tmin ${OutputfMRI}_mask
-    find_min_mask = pe.Node(
-        interface=fsl.maths.MathsCommand(), name=f"find_min_mask_{pipe_num}"
-    )
-
-    find_min_mask.inputs.args = "-Tmin"
-
-    wf.connect(merge_func_mask_to_standard, "merged_file", find_min_mask, "in_file")
-
     # applywarp --rel --interp=spline --in=${ScoutInput} -w ${WD}/Scout_gdc_MNI_warp.nii.gz -r ${WD}/${T1wImageFile}.${FinalfMRIResolution} -o ${ScoutOutput}
     applywarp_scout = pe.Node(
         interface=fsl.ApplyWarp(), name=f"applywarp_scout_input_{pipe_num}"
@@ -4471,46 +4419,9 @@ def warp_timeseries_to_T1template_abcd(wf, cfg, strat_pool, pipe_num, opt=None):
     # warp field is just fMRI->standard (skip GDC)
     wf.connect(convert_func_to_standard_warp, "out_file", applywarp_scout, "field_file")
 
-    # https://github.com/DCAN-Labs/DCAN-HCP/blob/1214767/fMRIVolume/scripts/IntensityNormalization.sh#L124-L127
-    # fslmaths ${InputfMRI} -mas ${BrainMask} -mas ${InputfMRI}_mask -thr 0 -ing 10000 ${OutputfMRI} -odt float
-    merge_func_mask = pe.Node(util.Merge(2), name=f"merge_func_mask_{pipe_num}")
-
-    node, out = strat_pool.get_data("space-template_desc-bold_mask")
-    wf.connect(
-        node,
-        out,
-        merge_func_mask,
-        "in1",
-    )
-
-    wf.connect(find_min_mask, "out_file", merge_func_mask, "in2")
-
-    extract_func_brain = pe.Node(
-        interface=fsl.MultiImageMaths(), name=f"extract_func_brain_{pipe_num}"
-    )
-
-    extract_func_brain.inputs.op_string = "-mas %s -mas %s -thr 0 -ing 10000"
-    extract_func_brain.inputs.output_datatype = "float"
-
-    wf.connect(merge_func_to_standard, "merged_file", extract_func_brain, "in_file")
-
-    wf.connect(merge_func_mask, "out", extract_func_brain, "operand_files")
-
-    # fslmaths ${ScoutInput} -mas ${BrainMask} -mas ${InputfMRI}_mask -thr 0 -ing 10000 ${ScoutOutput} -odt float
-    extract_scout_brain = pe.Node(
-        interface=fsl.MultiImageMaths(), name=f"extract_scout_brain_{pipe_num}"
-    )
-
-    extract_scout_brain.inputs.op_string = "-mas %s -mas %s -thr 0 -ing 10000"
-    extract_scout_brain.inputs.output_datatype = "float"
-
-    wf.connect(applywarp_scout, "out_file", extract_scout_brain, "in_file")
-
-    wf.connect(merge_func_mask, "out", extract_scout_brain, "operand_files")
-
     outputs = {
-        "space-template_desc-preproc_bold": (extract_func_brain, "out_file"),
-        "space-template_desc-scout_bold": (extract_scout_brain, "out_file"),
+        "space-template_desc-preproc_bold": (merge_func_to_standard, "merged_file"),
+        "space-template_desc-scout_bold": (applywarp_scout, "out_file"),
         "space-template_desc-head_bold": (merge_func_to_standard, "merged_file"),
     }
 

From 47cdb13942f0c8efb6bc8ad6ed413461b809e272 Mon Sep 17 00:00:00 2001
From: "birajstha:construction_worker::penguin" <birajstha@gmail.com>
Date: Tue, 2 Sep 2025 13:12:09 -0400
Subject: [PATCH 08/17] Turning EPI off for abcd-options config

---
 CHANGELOG.md                                            | 1 +
 CPAC/resources/configs/pipeline_config_abcd-options.yml | 4 ++--
 2 files changed, 3 insertions(+), 2 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index cac9fc998..ceb319991 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -57,6 +57,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   - Removed broken support for native-space masking.
   - Introduced a new `template_space_func_masking` section in the pipeline config for template-space-only methods.
   - Moved `Anatomical_Resampled` masking method from `func_masking` to the `template_space_func_masking`.
+- Moved `reference` in the bbreg config out to the whole co-registration block in all configs.
 
 ### Upgraded
 
diff --git a/CPAC/resources/configs/pipeline_config_abcd-options.yml b/CPAC/resources/configs/pipeline_config_abcd-options.yml
index de7d04a47..733941323 100644
--- a/CPAC/resources/configs/pipeline_config_abcd-options.yml
+++ b/CPAC/resources/configs/pipeline_config_abcd-options.yml
@@ -273,8 +273,8 @@ registration_workflows:
       # directly register the mean functional to an EPI template
       #   instead of applying the anatomical T1-to-template transform to the functional data that has been
       #   coregistered to anatomical/T1 space
-      run: on
-      
+      run: off
+
 functional_preproc:
   run: On
   motion_estimates_and_correction:

From 66d40dc7cfecca282fa72a70af07a654ba7cff28 Mon Sep 17 00:00:00 2001
From: "birajstha:construction_worker::penguin" <birajstha@gmail.com>
Date: Tue, 2 Sep 2025 13:30:23 -0400
Subject: [PATCH 09/17] adding to changelog

---
 CHANGELOG.md | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index ceb319991..7a97e6345 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -58,6 +58,9 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   - Introduced a new `template_space_func_masking` section in the pipeline config for template-space-only methods.
   - Moved `Anatomical_Resampled` masking method from `func_masking` to the `template_space_func_masking`.
 - Moved `reference` in the bbreg config out to the whole co-registration block in all configs.
+- Turned `On` boundary_based_registration for abcd-options preconfig.
+- Refactored `transform_timeseries_to_T1template_abcd` nodeblock removing unnecessary nodes, changing `desc-preproc_T1w` inputs as reference to `desc-head_T1w`.
+- Appended `T1w to Template` FOV match transform to the XFM.
 
 ### Upgraded
 

From f2a75786d9c047c20e0f60bfb47849e8ea833b88 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Tue, 2 Sep 2025 18:25:49 +0000
Subject: [PATCH 10/17] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 CPAC/registration/registration.py | 20 ++++++++++----------
 1 file changed, 10 insertions(+), 10 deletions(-)

diff --git a/CPAC/registration/registration.py b/CPAC/registration/registration.py
index b4e4e85ab..1a2385b64 100644
--- a/CPAC/registration/registration.py
+++ b/CPAC/registration/registration.py
@@ -3116,7 +3116,9 @@ def overwrite_transform_anat_to_template(wf, cfg, strat_pool, pipe_num, opt=None
             merge_xfms, "merged_file", fsl_apply_warp_t1_to_template, "field_file"
         )
 
-        concat_match_fov = pe.Node(interface=fsl.ConvertWarp(), name=f"concat_match_fov_{pipe_num}")
+        concat_match_fov = pe.Node(
+            interface=fsl.ConvertWarp(), name=f"concat_match_fov_{pipe_num}"
+        )
         concat_match_fov.inputs.relwarp = True
 
         wf.connect(match_fovs_T1w, "out_matrix_file", concat_match_fov, "premat")
@@ -3126,8 +3128,7 @@ def overwrite_transform_anat_to_template(wf, cfg, strat_pool, pipe_num, opt=None
 
         # Node to concatenate the inverse warp with the FOV matrix
         concat_match_fov_inv = pe.Node(
-            interface=fsl.ConvertWarp(),
-            name=f"concat_match_fov_inv_{pipe_num}"
+            interface=fsl.ConvertWarp(), name=f"concat_match_fov_inv_{pipe_num}"
         )
         concat_match_fov_inv.inputs.relwarp = True
 
@@ -3146,15 +3147,16 @@ def overwrite_transform_anat_to_template(wf, cfg, strat_pool, pipe_num, opt=None
         # TODO connect T1wRestoreBrain, check T1wRestoreBrain quality
         node, out = strat_pool.get_data(["desc-restore-brain_T1w", "desc-preproc_T1w"])
 
-        wf.connect(
-            node, out, fsl_apply_warp_t1_brain_to_template, "in_file"
-        )
+        wf.connect(node, out, fsl_apply_warp_t1_brain_to_template, "in_file")
 
         node, out = strat_pool.get_data("T1w-brain-template")
         wf.connect(node, out, fsl_apply_warp_t1_brain_to_template, "ref_file")
 
         wf.connect(
-            concat_match_fov, "out_file", fsl_apply_warp_t1_brain_to_template, "field_file"
+            concat_match_fov,
+            "out_file",
+            fsl_apply_warp_t1_brain_to_template,
+            "field_file",
         )
 
         fsl_apply_warp_t1_brain_mask_to_template = pe.Node(
@@ -3166,9 +3168,7 @@ def overwrite_transform_anat_to_template(wf, cfg, strat_pool, pipe_num, opt=None
 
         node, out = strat_pool.get_data("space-T1w_desc-brain_mask")
 
-        wf.connect(
-            node, out, fsl_apply_warp_t1_brain_mask_to_template, "in_file"
-        )
+        wf.connect(node, out, fsl_apply_warp_t1_brain_mask_to_template, "in_file")
 
         node, out = strat_pool.get_data("T1w-brain-template-mask")
         wf.connect(node, out, fsl_apply_warp_t1_brain_mask_to_template, "ref_file")

From e9925b7d51d4c2f967b8c8f4272f3d5b10f8a5b1 Mon Sep 17 00:00:00 2001
From: "birajstha:construction_worker::penguin" <birajstha@gmail.com>
Date: Wed, 3 Sep 2025 16:58:32 -0400
Subject: [PATCH 11/17] changing func_input from Selected_Functional_Volume to
 Mean_Functional in abcd-options preconfig

---
 CPAC/registration/registration.py                       | 6 +++++-
 CPAC/resources/configs/pipeline_config_abcd-options.yml | 2 +-
 2 files changed, 6 insertions(+), 2 deletions(-)

diff --git a/CPAC/registration/registration.py b/CPAC/registration/registration.py
index 1a2385b64..696f9ad83 100644
--- a/CPAC/registration/registration.py
+++ b/CPAC/registration/registration.py
@@ -4039,7 +4039,11 @@ def warp_wholeheadT1_to_template(wf, cfg, strat_pool, pipe_num, opt=None):
 )
 def warp_T1mask_to_template(wf, cfg, strat_pool, pipe_num, opt=None):
     """Warp T1 mask to template."""
-    reg_tool = strat_pool.reg_tool("from-T1w_to-template_mode-image_xfm")
+
+    if cfg.registration_workflows["anatomical_registration"]["overwrite_transform"] and cfg.registration_workflows["anatomical_registration"]["overwrite_transform"]["using"] == 'FSL':
+        reg_tool = 'fsl'
+    else:
+        reg_tool = strat_pool.reg_tool("from-T1w_to-template_mode-image_xfm")
 
     num_cpus = cfg.pipeline_setup["system_config"]["max_cores_per_participant"]
 
diff --git a/CPAC/resources/configs/pipeline_config_abcd-options.yml b/CPAC/resources/configs/pipeline_config_abcd-options.yml
index 733941323..111f53232 100644
--- a/CPAC/resources/configs/pipeline_config_abcd-options.yml
+++ b/CPAC/resources/configs/pipeline_config_abcd-options.yml
@@ -212,7 +212,7 @@ registration_workflows:
 
         # Choose whether to use the mean of the functional/EPI as the input to functional-to-anatomical registration or one of the volumes from the functional 4D timeseries that you choose.
         # input: ['Mean_Functional', 'Selected_Functional_Volume', 'fmriprep_reference']
-        input: [Selected_Functional_Volume]
+        input: [Mean_Functional]
 
         # Mask the sbref created by coregistration input prep nodeblocks above before registration
         mask_sbref: Off

From 009ba4a822077800a699162a26706d4aa84b5182 Mon Sep 17 00:00:00 2001
From: "birajstha:construction_worker::penguin" <birajstha@gmail.com>
Date: Wed, 3 Sep 2025 16:58:41 -0400
Subject: [PATCH 12/17] changing func_input from Selected_Functional_Volume to
 Mean_Functional in abcd-options preconfig

---
 CPAC/registration/registration.py | 11 ++++++++---
 1 file changed, 8 insertions(+), 3 deletions(-)

diff --git a/CPAC/registration/registration.py b/CPAC/registration/registration.py
index 696f9ad83..f5af23979 100644
--- a/CPAC/registration/registration.py
+++ b/CPAC/registration/registration.py
@@ -4039,9 +4039,14 @@ def warp_wholeheadT1_to_template(wf, cfg, strat_pool, pipe_num, opt=None):
 )
 def warp_T1mask_to_template(wf, cfg, strat_pool, pipe_num, opt=None):
     """Warp T1 mask to template."""
-
-    if cfg.registration_workflows["anatomical_registration"]["overwrite_transform"] and cfg.registration_workflows["anatomical_registration"]["overwrite_transform"]["using"] == 'FSL':
-        reg_tool = 'fsl'
+    if (
+        cfg.registration_workflows["anatomical_registration"]["overwrite_transform"]
+        and cfg.registration_workflows["anatomical_registration"][
+            "overwrite_transform"
+        ]["using"]
+        == "FSL"
+    ):
+        reg_tool = "fsl"
     else:
         reg_tool = strat_pool.reg_tool("from-T1w_to-template_mode-image_xfm")
 

From 2b13ca56b6fec6f007687482518f1345dcaf61c9 Mon Sep 17 00:00:00 2001
From: "birajstha:construction_worker::penguin" <birajstha@gmail.com>
Date: Wed, 3 Sep 2025 20:58:17 -0400
Subject: [PATCH 13/17] reverting some unnecessary changes

---
 CPAC/pipeline/schema.py                       |  2 +-
 CPAC/registration/registration.py             | 67 ++++++-------------
 .../configs/pipeline_config_abcd-options.yml  |  9 +--
 .../configs/pipeline_config_blank.yml         |  7 +-
 .../configs/pipeline_config_default.yml       |  7 +-
 .../pipeline_config_fmriprep-options.yml      |  7 +-
 6 files changed, 39 insertions(+), 60 deletions(-)

diff --git a/CPAC/pipeline/schema.py b/CPAC/pipeline/schema.py
index abfb7a3c4..81c542e8e 100644
--- a/CPAC/pipeline/schema.py
+++ b/CPAC/pipeline/schema.py
@@ -843,9 +843,9 @@ def sanitize(filename):
                         },
                         "mask_sbref": bool1_1,
                     },
-                    "reference": In({"whole-head", "brain"}),
                     "boundary_based_registration": {
                         "run": forkable,
+                        "reference": In({"whole-head", "brain"}),
                         "bbr_schedule": str,
                         "bbr_wm_map": In({"probability_map", "partial_volume_map"}),
                         "bbr_wm_mask_args": str,
diff --git a/CPAC/registration/registration.py b/CPAC/registration/registration.py
index f5af23979..2865c15b7 100644
--- a/CPAC/registration/registration.py
+++ b/CPAC/registration/registration.py
@@ -769,14 +769,6 @@ def create_register_func_to_anat(
         "coregistration"
     ]["dof"]
 
-    if (
-        config.registration_workflows["functional_registration"]["coregistration"][
-            "reference"
-        ]
-        == "whole-head"
-    ):
-        register_func_to_anat.connect(inputspec, "ref_weight", linear_reg, "ref_weight")
-
     if (
         config.registration_workflows["functional_registration"]["coregistration"][
             "arguments"
@@ -3116,9 +3108,7 @@ def overwrite_transform_anat_to_template(wf, cfg, strat_pool, pipe_num, opt=None
             merge_xfms, "merged_file", fsl_apply_warp_t1_to_template, "field_file"
         )
 
-        concat_match_fov = pe.Node(
-            interface=fsl.ConvertWarp(), name=f"concat_match_fov_{pipe_num}"
-        )
+        concat_match_fov = pe.Node(interface=fsl.ConvertWarp(), name=f"concat_match_fov_{pipe_num}")
         concat_match_fov.inputs.relwarp = True
 
         wf.connect(match_fovs_T1w, "out_matrix_file", concat_match_fov, "premat")
@@ -3128,7 +3118,8 @@ def overwrite_transform_anat_to_template(wf, cfg, strat_pool, pipe_num, opt=None
 
         # Node to concatenate the inverse warp with the FOV matrix
         concat_match_fov_inv = pe.Node(
-            interface=fsl.ConvertWarp(), name=f"concat_match_fov_inv_{pipe_num}"
+            interface=fsl.ConvertWarp(),
+            name=f"concat_match_fov_inv_{pipe_num}"
         )
         concat_match_fov_inv.inputs.relwarp = True
 
@@ -3147,16 +3138,15 @@ def overwrite_transform_anat_to_template(wf, cfg, strat_pool, pipe_num, opt=None
         # TODO connect T1wRestoreBrain, check T1wRestoreBrain quality
         node, out = strat_pool.get_data(["desc-restore-brain_T1w", "desc-preproc_T1w"])
 
-        wf.connect(node, out, fsl_apply_warp_t1_brain_to_template, "in_file")
+        wf.connect(
+            node, out, fsl_apply_warp_t1_brain_to_template, "in_file"
+        )
 
         node, out = strat_pool.get_data("T1w-brain-template")
         wf.connect(node, out, fsl_apply_warp_t1_brain_to_template, "ref_file")
 
         wf.connect(
-            concat_match_fov,
-            "out_file",
-            fsl_apply_warp_t1_brain_to_template,
-            "field_file",
+            concat_match_fov, "out_file", fsl_apply_warp_t1_brain_to_template, "field_file"
         )
 
         fsl_apply_warp_t1_brain_mask_to_template = pe.Node(
@@ -3168,7 +3158,9 @@ def overwrite_transform_anat_to_template(wf, cfg, strat_pool, pipe_num, opt=None
 
         node, out = strat_pool.get_data("space-T1w_desc-brain_mask")
 
-        wf.connect(node, out, fsl_apply_warp_t1_brain_mask_to_template, "in_file")
+        wf.connect(
+            node, out, fsl_apply_warp_t1_brain_mask_to_template, "in_file"
+        )
 
         node, out = strat_pool.get_data("T1w-brain-template-mask")
         wf.connect(node, out, fsl_apply_warp_t1_brain_mask_to_template, "ref_file")
@@ -3446,22 +3438,10 @@ def coregistration(wf, cfg, strat_pool, pipe_num, opt=None):
         node, out = strat_pool.get_data("sbref")
         wf.connect(node, out, func_to_anat, "inputspec.func")
 
-        if (
-            cfg.registration_workflows["functional_registration"]["coregistration"][
-                "reference"
-            ]
-            == "whole-head"
-        ):
-            node, out = strat_pool.get_data(["desc-restore_T1w", "desc-head_T1w"])
-            wf.connect(node, out, func_to_anat, "inputspec.anat")
-
-            node, out = strat_pool.get_data("space-T1w_desc-brain_mask")
-            wf.connect(node, out, func_to_anat, "inputspec.ref_weight")
-        else:
-            node, out = strat_pool.get_data(
-                ["desc-restore-brain_T1w", "desc-preproc_T1w"]
-            )
-            wf.connect(node, out, func_to_anat, "inputspec.anat")
+        node, out = strat_pool.get_data(
+            ["desc-restore-brain_T1w", "desc-preproc_T1w"]
+        )
+        wf.connect(node, out, func_to_anat, "inputspec.anat")
 
     if diff_complete:
         node, out = strat_pool.get_data("effectiveEchoSpacing")
@@ -3521,8 +3501,8 @@ def coregistration(wf, cfg, strat_pool, pipe_num, opt=None):
 
         if (
             cfg.registration_workflows["functional_registration"]["coregistration"][
-                "reference"
-            ]
+                "boundary_based_registration"
+            ]["reference"]
             == "whole-head"
         ):
             node, out = strat_pool.get_data("desc-head_T1w")
@@ -3530,8 +3510,8 @@ def coregistration(wf, cfg, strat_pool, pipe_num, opt=None):
 
         elif (
             cfg.registration_workflows["functional_registration"]["coregistration"][
-                "reference"
-            ]
+                "boundary_based_registration"
+            ]["reference"]
             == "brain"
         ):
             node, out = strat_pool.get_data("desc-preproc_T1w")
@@ -4039,14 +4019,9 @@ def warp_wholeheadT1_to_template(wf, cfg, strat_pool, pipe_num, opt=None):
 )
 def warp_T1mask_to_template(wf, cfg, strat_pool, pipe_num, opt=None):
     """Warp T1 mask to template."""
-    if (
-        cfg.registration_workflows["anatomical_registration"]["overwrite_transform"]
-        and cfg.registration_workflows["anatomical_registration"][
-            "overwrite_transform"
-        ]["using"]
-        == "FSL"
-    ):
-        reg_tool = "fsl"
+
+    if cfg.registration_workflows["anatomical_registration"]["overwrite_transform"] and cfg.registration_workflows["anatomical_registration"]["overwrite_transform"]["using"] == 'FSL':
+        reg_tool = 'fsl'
     else:
         reg_tool = strat_pool.reg_tool("from-T1w_to-template_mode-image_xfm")
 
diff --git a/CPAC/resources/configs/pipeline_config_abcd-options.yml b/CPAC/resources/configs/pipeline_config_abcd-options.yml
index 111f53232..fa682d8c7 100644
--- a/CPAC/resources/configs/pipeline_config_abcd-options.yml
+++ b/CPAC/resources/configs/pipeline_config_abcd-options.yml
@@ -212,14 +212,11 @@ registration_workflows:
 
         # Choose whether to use the mean of the functional/EPI as the input to functional-to-anatomical registration or one of the volumes from the functional 4D timeseries that you choose.
         # input: ['Mean_Functional', 'Selected_Functional_Volume', 'fmriprep_reference']
-        input: [Mean_Functional]
+        input: [Selected_Functional_Volume]
 
         # Mask the sbref created by coregistration input prep nodeblocks above before registration
         mask_sbref: Off
 
-      # options: 'whole-head' or 'brain'
-      reference: whole-head
-
       # Choose coregistration interpolation
       interpolation: spline
 
@@ -231,6 +228,10 @@ registration_workflows:
         #   run: [On, Off] - this will run both and fork the pipeline
         run: [On]
 
+        # reference for boundary based registration
+        # options: 'whole-head' or 'brain'
+        reference: whole-head
+
     func_registration_to_template:
 
       # these options modify the application (to the functional data), not the calculation, of the
diff --git a/CPAC/resources/configs/pipeline_config_blank.yml b/CPAC/resources/configs/pipeline_config_blank.yml
index 008090280..11e480946 100644
--- a/CPAC/resources/configs/pipeline_config_blank.yml
+++ b/CPAC/resources/configs/pipeline_config_blank.yml
@@ -738,15 +738,16 @@ registration_workflows:
         # Mask the sbref created by coregistration input prep nodeblocks above before registration
         mask_sbref: On
 
-      # options: 'whole-head' or 'brain'
-      reference: whole-head
-
       boundary_based_registration:
 
         # this is a fork point
         #   run: [On, Off] - this will run both and fork the pipeline
         run: [Off]
 
+        # reference for boundary based registration
+        # options: 'whole-head' or 'brain'
+        reference: whole-head
+
         # choose which FAST map to generate BBR WM mask
         # options: 'probability_map', 'partial_volume_map'
         bbr_wm_map: probability_map
diff --git a/CPAC/resources/configs/pipeline_config_default.yml b/CPAC/resources/configs/pipeline_config_default.yml
index c69cc8d4b..7bdbf527c 100644
--- a/CPAC/resources/configs/pipeline_config_default.yml
+++ b/CPAC/resources/configs/pipeline_config_default.yml
@@ -808,14 +808,15 @@ registration_workflows:
         # Mask the sbref created by coregistration input prep nodeblocks above before registration
         mask_sbref: On
 
-      # options: 'whole-head' or 'brain'
-      reference: whole-head
-
       boundary_based_registration:
         # this is a fork point
         #   run: [On, Off] - this will run both and fork the pipeline
         run: [On]
 
+        # reference for boundary based registration
+        # options: 'whole-head' or 'brain'
+        reference: whole-head
+
         # Standard FSL 5.0 Scheduler used for Boundary Based Registration.
         # It is not necessary to change this path unless you intend to use non-standard MNI registration.
         bbr_schedule: $FSLDIR/etc/flirtsch/bbr.sch
diff --git a/CPAC/resources/configs/pipeline_config_fmriprep-options.yml b/CPAC/resources/configs/pipeline_config_fmriprep-options.yml
index 2b268930a..5453144af 100644
--- a/CPAC/resources/configs/pipeline_config_fmriprep-options.yml
+++ b/CPAC/resources/configs/pipeline_config_fmriprep-options.yml
@@ -251,15 +251,16 @@ registration_workflows:
         # input: ['Mean_Functional', 'Selected_Functional_Volume', 'fmriprep_reference']
         input: [fmriprep_reference]
 
-      # options: 'whole-head' or 'brain'
-      reference: brain
-
       boundary_based_registration:
 
         # this is a fork point
         #   run: [On, Off] - this will run both and fork the pipeline
         run: [On]
 
+        # reference for boundary based registration
+        # options: 'whole-head' or 'brain'
+        reference: brain
+
         # choose which FAST map to generate BBR WM mask
         # options: 'probability_map', 'partial_volume_map'
         bbr_wm_map: partial_volume_map

From c3957a969d82fc3baddd6aff17fb1a431b3cfabb Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Thu, 4 Sep 2025 00:58:57 +0000
Subject: [PATCH 14/17] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 CPAC/registration/registration.py | 34 +++++++++++++++++--------------
 1 file changed, 19 insertions(+), 15 deletions(-)

diff --git a/CPAC/registration/registration.py b/CPAC/registration/registration.py
index 2865c15b7..6bf649b44 100644
--- a/CPAC/registration/registration.py
+++ b/CPAC/registration/registration.py
@@ -3108,7 +3108,9 @@ def overwrite_transform_anat_to_template(wf, cfg, strat_pool, pipe_num, opt=None
             merge_xfms, "merged_file", fsl_apply_warp_t1_to_template, "field_file"
         )
 
-        concat_match_fov = pe.Node(interface=fsl.ConvertWarp(), name=f"concat_match_fov_{pipe_num}")
+        concat_match_fov = pe.Node(
+            interface=fsl.ConvertWarp(), name=f"concat_match_fov_{pipe_num}"
+        )
         concat_match_fov.inputs.relwarp = True
 
         wf.connect(match_fovs_T1w, "out_matrix_file", concat_match_fov, "premat")
@@ -3118,8 +3120,7 @@ def overwrite_transform_anat_to_template(wf, cfg, strat_pool, pipe_num, opt=None
 
         # Node to concatenate the inverse warp with the FOV matrix
         concat_match_fov_inv = pe.Node(
-            interface=fsl.ConvertWarp(),
-            name=f"concat_match_fov_inv_{pipe_num}"
+            interface=fsl.ConvertWarp(), name=f"concat_match_fov_inv_{pipe_num}"
         )
         concat_match_fov_inv.inputs.relwarp = True
 
@@ -3138,15 +3139,16 @@ def overwrite_transform_anat_to_template(wf, cfg, strat_pool, pipe_num, opt=None
         # TODO connect T1wRestoreBrain, check T1wRestoreBrain quality
         node, out = strat_pool.get_data(["desc-restore-brain_T1w", "desc-preproc_T1w"])
 
-        wf.connect(
-            node, out, fsl_apply_warp_t1_brain_to_template, "in_file"
-        )
+        wf.connect(node, out, fsl_apply_warp_t1_brain_to_template, "in_file")
 
         node, out = strat_pool.get_data("T1w-brain-template")
         wf.connect(node, out, fsl_apply_warp_t1_brain_to_template, "ref_file")
 
         wf.connect(
-            concat_match_fov, "out_file", fsl_apply_warp_t1_brain_to_template, "field_file"
+            concat_match_fov,
+            "out_file",
+            fsl_apply_warp_t1_brain_to_template,
+            "field_file",
         )
 
         fsl_apply_warp_t1_brain_mask_to_template = pe.Node(
@@ -3158,9 +3160,7 @@ def overwrite_transform_anat_to_template(wf, cfg, strat_pool, pipe_num, opt=None
 
         node, out = strat_pool.get_data("space-T1w_desc-brain_mask")
 
-        wf.connect(
-            node, out, fsl_apply_warp_t1_brain_mask_to_template, "in_file"
-        )
+        wf.connect(node, out, fsl_apply_warp_t1_brain_mask_to_template, "in_file")
 
         node, out = strat_pool.get_data("T1w-brain-template-mask")
         wf.connect(node, out, fsl_apply_warp_t1_brain_mask_to_template, "ref_file")
@@ -3438,9 +3438,7 @@ def coregistration(wf, cfg, strat_pool, pipe_num, opt=None):
         node, out = strat_pool.get_data("sbref")
         wf.connect(node, out, func_to_anat, "inputspec.func")
 
-        node, out = strat_pool.get_data(
-            ["desc-restore-brain_T1w", "desc-preproc_T1w"]
-        )
+        node, out = strat_pool.get_data(["desc-restore-brain_T1w", "desc-preproc_T1w"])
         wf.connect(node, out, func_to_anat, "inputspec.anat")
 
     if diff_complete:
@@ -4020,8 +4018,14 @@ def warp_wholeheadT1_to_template(wf, cfg, strat_pool, pipe_num, opt=None):
 def warp_T1mask_to_template(wf, cfg, strat_pool, pipe_num, opt=None):
     """Warp T1 mask to template."""
 
-    if cfg.registration_workflows["anatomical_registration"]["overwrite_transform"] and cfg.registration_workflows["anatomical_registration"]["overwrite_transform"]["using"] == 'FSL':
-        reg_tool = 'fsl'
+    if (
+        cfg.registration_workflows["anatomical_registration"]["overwrite_transform"]
+        and cfg.registration_workflows["anatomical_registration"][
+            "overwrite_transform"
+        ]["using"]
+        == "FSL"
+    ):
+        reg_tool = "fsl"
     else:
         reg_tool = strat_pool.reg_tool("from-T1w_to-template_mode-image_xfm")
 

From 54994b09287a2c2f4779bfe02d433a892a2c8348 Mon Sep 17 00:00:00 2001
From: "birajstha:construction_worker::penguin" <birajstha@gmail.com>
Date: Wed, 3 Sep 2025 21:06:51 -0400
Subject: [PATCH 15/17] updating the changelog

---
 CHANGELOG.md | 1 -
 1 file changed, 1 deletion(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 7a97e6345..4de4717bf 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -57,7 +57,6 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   - Removed broken support for native-space masking.
   - Introduced a new `template_space_func_masking` section in the pipeline config for template-space-only methods.
   - Moved `Anatomical_Resampled` masking method from `func_masking` to the `template_space_func_masking`.
-- Moved `reference` in the bbreg config out to the whole co-registration block in all configs.
 - Turned `On` boundary_based_registration for abcd-options preconfig.
 - Refactored `transform_timeseries_to_T1template_abcd` nodeblock removing unnecessary nodes, changing `desc-preproc_T1w` inputs as reference to `desc-head_T1w`.
 - Appended `T1w to Template` FOV match transform to the XFM.

From e408c74c2dce7fd139031959a4ea71b2091c3256 Mon Sep 17 00:00:00 2001
From: "birajstha:construction_worker::penguin" <birajstha@gmail.com>
Date: Fri, 5 Sep 2025 16:58:05 -0400
Subject: [PATCH 16/17] moving the addition of bold masking below and enabling
 previously blocked nodeblocks

---
 CPAC/pipeline/cpac_pipeline.py | 15 ++++++++-------
 1 file changed, 8 insertions(+), 7 deletions(-)

diff --git a/CPAC/pipeline/cpac_pipeline.py b/CPAC/pipeline/cpac_pipeline.py
index b9e686593..12ff690f4 100644
--- a/CPAC/pipeline/cpac_pipeline.py
+++ b/CPAC/pipeline/cpac_pipeline.py
@@ -1291,13 +1291,6 @@ def build_workflow(subject_id, sub_dict, cfg, pipeline_name=None):
             mask_sbref,
         ]
 
-    # Template space functional mask
-    if cfg.functional_preproc["template_space_func_masking"]["run"]:
-        if not rpool.check_rpool("space-template_desc-bold_mask"):
-            pipeline_blocks += [
-                bold_mask_anatomical_resampled,
-            ]
-
         # Distortion/Susceptibility Correction
         distcor_blocks = []
         if "fmap" in sub_dict:
@@ -1320,6 +1313,14 @@ def build_workflow(subject_id, sub_dict, cfg, pipeline_name=None):
 
         pipeline_blocks += stack_motion_blocks(func_blocks, cfg, rpool)
 
+    
+    # Template space functional mask
+    if cfg.functional_preproc["template_space_func_masking"]["run"]:
+        if not rpool.check_rpool("space-template_desc-bold_mask"):
+            pipeline_blocks += [
+                bold_mask_anatomical_resampled,
+            ]
+            
     # BOLD to T1 coregistration
     if cfg.registration_workflows["functional_registration"]["coregistration"][
         "run"

From fb7e86f0622f4b5fff7bd119e59195a2eaeae69e Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Fri, 5 Sep 2025 20:58:51 +0000
Subject: [PATCH 17/17] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 CPAC/pipeline/cpac_pipeline.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/CPAC/pipeline/cpac_pipeline.py b/CPAC/pipeline/cpac_pipeline.py
index 12ff690f4..a54fa929b 100644
--- a/CPAC/pipeline/cpac_pipeline.py
+++ b/CPAC/pipeline/cpac_pipeline.py
@@ -1313,14 +1313,13 @@ def build_workflow(subject_id, sub_dict, cfg, pipeline_name=None):
 
         pipeline_blocks += stack_motion_blocks(func_blocks, cfg, rpool)
 
-    
     # Template space functional mask
     if cfg.functional_preproc["template_space_func_masking"]["run"]:
         if not rpool.check_rpool("space-template_desc-bold_mask"):
             pipeline_blocks += [
                 bold_mask_anatomical_resampled,
             ]
-            
+
     # BOLD to T1 coregistration
     if cfg.registration_workflows["functional_registration"]["coregistration"][
         "run"