diff --git a/nibabies/workflows/anatomical/apply.py b/nibabies/workflows/anatomical/apply.py
index 36a693e4..276968f4 100644
--- a/nibabies/workflows/anatomical/apply.py
+++ b/nibabies/workflows/anatomical/apply.py
@@ -2,6 +2,7 @@
 
 import nipype.interfaces.utility as niu
 import nipype.pipeline.engine as pe
+from niworkflows.engine import tag
 from smriprep.workflows.outputs import (
     init_ds_anat_volumes_wf,
     init_ds_grayord_metrics_wf,
@@ -25,6 +26,7 @@
 LOGGER = config.loggers.workflow
 
 
+@tag('anat.apply')
 def init_infant_anat_apply_wf(
     *,
     bids_root: str,
diff --git a/nibabies/workflows/anatomical/brain_extraction.py b/nibabies/workflows/anatomical/brain_extraction.py
index fb6cc1ea..95e1dbc1 100644
--- a/nibabies/workflows/anatomical/brain_extraction.py
+++ b/nibabies/workflows/anatomical/brain_extraction.py
@@ -4,8 +4,10 @@
 
 from nipype.interfaces import utility as niu
 from nipype.pipeline import engine as pe
+from niworkflows.engine import tag
 
 
+@tag('anat.brain-extraction')
 def init_infant_brain_extraction_wf(
     *,
     omp_nthreads: int,
diff --git a/nibabies/workflows/anatomical/fit.py b/nibabies/workflows/anatomical/fit.py
index 164fc81b..9807cde8 100644
--- a/nibabies/workflows/anatomical/fit.py
+++ b/nibabies/workflows/anatomical/fit.py
@@ -5,7 +5,7 @@
 from nipype.interfaces import utility as niu
 from nipype.pipeline import engine as pe
 from niworkflows.anat.ants import init_n4_only_wf
-from niworkflows.engine.workflows import LiterateWorkflow as Workflow
+from niworkflows.engine import Workflow, tag
 from niworkflows.interfaces.fixes import FixHeaderApplyTransforms as ApplyTransforms
 from niworkflows.interfaces.header import ValidateImage
 from niworkflows.interfaces.nibabel import ApplyMask, Binarize
@@ -53,6 +53,7 @@
 LOGGER = logging.getLogger('nipype.workflow')
 
 
+@tag('anat.fit')
 def init_infant_anat_fit_wf(
     *,
     age_months: int,
@@ -1374,6 +1375,7 @@ def init_infant_anat_fit_wf(
     return workflow
 
 
+@tag('anat.fit')
 def init_infant_single_anat_fit_wf(
     *,
     age_months: int,
diff --git a/nibabies/workflows/anatomical/outputs.py b/nibabies/workflows/anatomical/outputs.py
index 842003bf..4cf5df3f 100644
--- a/nibabies/workflows/anatomical/outputs.py
+++ b/nibabies/workflows/anatomical/outputs.py
@@ -9,7 +9,7 @@
 
 from nipype.interfaces import utility as niu
 from nipype.pipeline import engine as pe
-from niworkflows.engine.workflows import LiterateWorkflow as Workflow
+from niworkflows.engine import Workflow, tag
 from niworkflows.interfaces.fixes import FixHeaderApplyTransforms as ApplyTransforms
 from smriprep.workflows.outputs import init_template_iterator_wf
 
@@ -21,6 +21,7 @@
 BIDS_TISSUE_ORDER = ('GM', 'WM', 'CSF')
 
 
+@tag('anat.coreg-report')
 def init_coreg_report_wf(*, output_dir, name='coreg_report_wf'):
     """
     Generate and store a report in the right location.
@@ -85,6 +86,7 @@ def init_coreg_report_wf(*, output_dir, name='coreg_report_wf'):
     return workflow
 
 
+@tag('anat.reports')
 def init_anat_reports_wf(
     *,
     spaces: SpatialReferences,
@@ -283,6 +285,7 @@ def init_anat_reports_wf(
     return workflow
 
 
+@tag('anat.derivatives')
 def init_anat_derivatives_wf(
     *,
     bids_root: Path | str,
diff --git a/nibabies/workflows/anatomical/preproc.py b/nibabies/workflows/anatomical/preproc.py
index 12fbe814..814961ec 100644
--- a/nibabies/workflows/anatomical/preproc.py
+++ b/nibabies/workflows/anatomical/preproc.py
@@ -1,13 +1,14 @@
 import nipype.interfaces.utility as niu
 import nipype.pipeline.engine as pe
-from niworkflows.engine.workflows import LiterateWorkflow
+from niworkflows.engine import Workflow, tag
 
 
+@tag('anat.preproc')
 def init_anat_preproc_wf(
     *,
     bspline_fitting_distance: int = 200,
     name: str = 'anat_preproc_wf',
-) -> LiterateWorkflow:
+) -> Workflow:
     """Polish up raw anatomical data.
 
     This workflow accepts T1w/T2w images as inputs (either raw or a merged template) and performs:
@@ -30,7 +31,7 @@ def init_anat_preproc_wf(
     from niworkflows.interfaces.header import ValidateImage
     from niworkflows.interfaces.nibabel import IntensityClip
 
-    wf = LiterateWorkflow(name=name)
+    wf = Workflow(name=name)
     inputnode = pe.Node(
         niu.IdentityInterface(fields=['in_anat']),
         name='inputnode',
@@ -68,10 +69,11 @@ def init_anat_preproc_wf(
     return wf
 
 
-def init_csf_norm_wf(name: str = 'csf_norm_wf') -> LiterateWorkflow:
+@tag('anat.csf_norm')
+def init_csf_norm_wf(name: str = 'csf_norm_wf') -> Workflow:
     """Replace low intensity voxels within the CSF mask with the median value."""
 
-    workflow = LiterateWorkflow(name=name)
+    workflow = Workflow(name=name)
     workflow.__desc__ = (
         'The CSF mask was used to normalize the anatomical template by the median of voxels '
         'within the mask.'
diff --git a/nibabies/workflows/anatomical/registration.py b/nibabies/workflows/anatomical/registration.py
index d23f253e..096c4fba 100644
--- a/nibabies/workflows/anatomical/registration.py
+++ b/nibabies/workflows/anatomical/registration.py
@@ -11,7 +11,7 @@
 )
 from nipype.interfaces.ants.base import Info as ANTsInfo
 from nipype.pipeline import engine as pe
-from niworkflows.engine.workflows import LiterateWorkflow as Workflow
+from niworkflows.engine import Workflow, tag
 from niworkflows.interfaces.fixes import FixHeaderApplyTransforms as ApplyTransforms
 from smriprep.workflows.fit.registration import (
     TemplateDesc,
@@ -21,6 +21,7 @@
 )
 
 
+@tag('anat.coreg')
 def init_coregistration_wf(
     *,
     bspline_fitting_distance: int = 200,
@@ -249,6 +250,7 @@ def init_coregistration_wf(
     return workflow
 
 
+@tag('anat.coreg-derivatives')
 def init_coregister_derivatives_wf(
     *, t1w_mask: bool, t1w_aseg: bool, t2w_aseg: bool, name: str = 'coregister_derivatives_wf'
 ):
@@ -301,6 +303,7 @@ def init_coregister_derivatives_wf(
     return workflow
 
 
+@tag('anat.concat-reg')
 def init_concat_registrations_wf(
     *,
     templates,
diff --git a/nibabies/workflows/anatomical/resampling.py b/nibabies/workflows/anatomical/resampling.py
index 410927a9..4881ecb4 100644
--- a/nibabies/workflows/anatomical/resampling.py
+++ b/nibabies/workflows/anatomical/resampling.py
@@ -3,7 +3,7 @@
 import nipype.interfaces.utility as niu
 import nipype.pipeline.engine as pe
 import templateflow.api as tf
-from niworkflows.engine.workflows import LiterateWorkflow
+from niworkflows.engine import Workflow, tag
 from smriprep.interfaces.workbench import SurfaceResample
 from smriprep.workflows.surfaces import init_morph_grayords_wf
 
@@ -12,11 +12,12 @@
 from nibabies.interfaces.utils import CiftiSelect
 
 
+@tag('anat.resample-surfs')
 def init_anat_fsLR_resampling_wf(
     grayord_density: ty.Literal['91k'], mcribs: bool, name='anat_fsLR_resampling_wf'
-) -> LiterateWorkflow:
+) -> Workflow:
     """Resample the surfaces into fsLR space"""
-    workflow = LiterateWorkflow(name=name)
+    workflow = Workflow(name=name)
     fslr_density = '32k' if grayord_density == '91k' else '59k'
 
     workflow.__desc__ = """\
@@ -93,7 +94,7 @@ def init_anat_fsLR_resampling_wf(
     # resample surfaces / morphometrics to 32k
     if mcribs:
         morph_grayords_wf = init_mcribs_morph_grayords_wf(grayord_density)
-        # fmt:off
+
         workflow.connect([
             (inputnode, morph_grayords_wf, [
                 ('morphometrics', 'inputnode.morphometrics'),
@@ -101,12 +102,10 @@ def init_anat_fsLR_resampling_wf(
                 ('sphere_reg_fsLR', 'inputnode.sphere_reg')]),
             (joinnode, morph_grayords_wf, [
                 ('midthickness_fsLR', 'inputnode.midthickness_fsLR')]),
-        ])
-        # fmt:on
+        ])  # fmt:skip
     else:
         morph_grayords_wf = init_morph_grayords_wf(grayord_density)
 
-    # fmt:off
     workflow.connect([
         (inputnode, select_surfaces, [
             ('surfaces', 'surfaces'),
@@ -126,11 +125,11 @@ def init_anat_fsLR_resampling_wf(
         (morph_grayords_wf, outputnode, [
             ('outputnode.cifti_morph', 'cifti_morph'),
             ('outputnode.cifti_metadata', 'cifti_metadata')]),
-    ])
-    # fmt:on
+    ])  # fmt:skip
     return workflow
 
 
+@tag('anat.resample-morphs-grayords')
 def init_mcribs_morph_grayords_wf(
     grayord_density: ty.Literal['91k'],  # Only 91k supported ATM
     name: str = 'morph_grayords_wf',
@@ -174,7 +173,6 @@ def init_mcribs_morph_grayords_wf(
 
     """
     from nipype.interfaces.workbench import MetricResample
-    from niworkflows.engine.workflows import LiterateWorkflow as Workflow
     from smriprep.interfaces.cifti import GenerateDScalar
 
     from nibabies.interfaces.workbench import SurfaceVertexAreas
diff --git a/nibabies/workflows/anatomical/segmentation.py b/nibabies/workflows/anatomical/segmentation.py
index b538c2fd..95a75ac6 100644
--- a/nibabies/workflows/anatomical/segmentation.py
+++ b/nibabies/workflows/anatomical/segmentation.py
@@ -7,7 +7,7 @@
 from nipype.interfaces.ants.segmentation import JointFusion
 from nipype.pipeline import engine as pe
 from niworkflows.data import load as load_nwf
-from niworkflows.engine.workflows import LiterateWorkflow as Workflow
+from niworkflows.engine import Workflow, tag
 from niworkflows.interfaces.fixes import FixHeaderApplyTransforms as ApplyTransforms
 from niworkflows.interfaces.fixes import FixHeaderRegistration as Registration
 from niworkflows.utils.connections import listify
@@ -23,6 +23,7 @@
 LOGGER = config.loggers.workflow
 
 
+@tag('anat.segmentation')
 def init_segmentation_wf(
     *,
     sloppy: bool,
@@ -129,6 +130,7 @@ def init_segmentation_wf(
     return workflow
 
 
+@tag('anat.segmentation.jlf')
 def init_jlf_wf(
     jlf_template_dir: Path,
     sloppy: bool,
diff --git a/nibabies/workflows/anatomical/surfaces.py b/nibabies/workflows/anatomical/surfaces.py
index 1432cf46..52b6756e 100644
--- a/nibabies/workflows/anatomical/surfaces.py
+++ b/nibabies/workflows/anatomical/surfaces.py
@@ -8,7 +8,7 @@
 from nipype.interfaces import utility as niu
 from nipype.interfaces.ants import N4BiasFieldCorrection
 from nipype.pipeline import engine as pe
-from niworkflows.engine.workflows import LiterateWorkflow
+from niworkflows.engine import Workflow, tag
 from niworkflows.interfaces.freesurfer import (
     PatchedLTAConvert as LTAConvert,
 )
@@ -41,6 +41,7 @@
 ]
 
 
+@tag('anat.recon')
 def init_mcribs_surface_recon_wf(
     *,
     omp_nthreads: int,
@@ -67,7 +68,7 @@ def init_mcribs_surface_recon_wf(
     inputnode = pe.Node(niu.IdentityInterface(fields=SURFACE_INPUTS), name='inputnode')
     outputnode = pe.Node(niu.IdentityInterface(fields=SURFACE_OUTPUTS), name='outputnode')
 
-    workflow = LiterateWorkflow(name=name)
+    workflow = Workflow(name=name)
     workflow.__desc__ = (
         'Brain surfaces were reconstructed with a modified `MCRIBReconAll` [M-CRIB-S, @mcribs]'
         'workflow, using the reference T2w and a pre-computed anatomical segmentation'
@@ -224,6 +225,7 @@ def init_mcribs_surface_recon_wf(
     return workflow
 
 
+@tag('anat.fslr-reg')
 def init_mcribs_dhcp_wf(*, name='mcribs_dhcp_wf'):
     """
     Generate GIFTI registration files to dhcp (42-week) space.
@@ -233,7 +235,7 @@ def init_mcribs_dhcp_wf(*, name='mcribs_dhcp_wf'):
     """
     from smriprep.interfaces.workbench import SurfaceSphereProjectUnproject
 
-    workflow = LiterateWorkflow(name=name)
+    workflow = Workflow(name=name)
 
     inputnode = pe.Node(
         niu.IdentityInterface(['sphere_reg', 'sulc']),
@@ -294,6 +296,7 @@ def init_mcribs_dhcp_wf(*, name='mcribs_dhcp_wf'):
     return workflow
 
 
+@tag('anat.recon')
 def init_infantfs_surface_recon_wf(
     *,
     age_months: int,
@@ -304,7 +307,7 @@ def init_infantfs_surface_recon_wf(
 ):
     from nibabies.interfaces.freesurfer import InfantReconAll
 
-    workflow = LiterateWorkflow(name=name)
+    workflow = Workflow(name=name)
     inputnode = pe.Node(niu.IdentityInterface(fields=SURFACE_INPUTS), name='inputnode')
     outputnode = pe.Node(niu.IdentityInterface(fields=SURFACE_OUTPUTS), name='outputnode')
 
@@ -382,6 +385,7 @@ def init_infantfs_surface_recon_wf(
     return workflow
 
 
+@tag('anat.midthickness')
 def init_make_midthickness_wf(
     *, omp_nthreads: int, name: str = 'make_midthickness_wf'
 ) -> pe.Workflow:
@@ -435,6 +439,7 @@ def init_make_midthickness_wf(
     return workflow
 
 
+@tag('anat.resample-surfs')
 def init_resample_surfaces_dhcp_wf(
     surfaces: list[str],
     grayord_density: ty.Literal['91k', '170k'],
@@ -470,7 +475,7 @@ def init_resample_surfaces_dhcp_wf(
     midthickness
         GIFTI surface mesh corresponding to the midthickness surface, resampled to fsLR
     """
-    workflow = LiterateWorkflow(name=name)
+    workflow = Workflow(name=name)
 
     fslr_density = '32k' if grayord_density == '91k' else '59k'
 
diff --git a/pyproject.toml b/pyproject.toml
index 2c6fd2c0..503d4cc8 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -25,7 +25,7 @@ dependencies = [
     "nireports >= 23.2.0",
     "nitime",
     "nitransforms >= 24.1.1",
-    "niworkflows >= 1.12.2",
+    "niworkflows >= 1.13.1",
     "numpy >= 1.21.0",
     "packaging",
     "pandas",
diff --git a/requirements.txt b/requirements.txt
index 3a13ac1f..d8d299ea 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -4,8 +4,9 @@
 #
 #    pip-compile --extra=container --output-file=requirements.txt --strip-extras pyproject.toml
 #
-acres==0.2.0
+acres==0.3.0
     # via
+    #   bidsschematools
     #   nibabies (pyproject.toml)
     #   nipype
     #   nireports
@@ -17,44 +18,40 @@ annexremote==1.6.6
     #   datalad
     #   datalad-next
     #   datalad-osf
-astor==0.8.1
-    # via formulaic
-attrs==25.1.0
+attrs==25.3.0
     # via
-    #   jsonschema
     #   niworkflows
-    #   referencing
     #   sdcflows
 backports-tarfile==1.2.0
     # via jaraco-context
 bids-validator==1.14.7.post0
     # via pybids
-bidsschematools==1.0.0
+bidsschematools==1.0.7
     # via bids-validator
-bokeh==3.5.2
+bokeh==3.6.3
     # via tedana
-boto3==1.36.13
+boto3==1.38.17
     # via datalad
-botocore==1.36.13
+botocore==1.38.17
     # via
     #   boto3
     #   s3transfer
-certifi==2025.1.31
+certifi==2025.4.26
     # via requests
 chardet==5.2.0
     # via datalad
-charset-normalizer==3.4.1
+charset-normalizer==3.4.2
     # via requests
 ci-info==0.3.0
     # via
     #   etelemetry
     #   migas
-click==8.1.8
+click==8.2.0
     # via
     #   bidsschematools
     #   nipype
     #   pybids
-contourpy==1.3.1
+contourpy==1.3.2
     # via
     #   bokeh
     #   matplotlib
@@ -77,17 +74,19 @@ etelemetry==0.3.1
     # via nipype
 fasteners==0.19
     # via datalad
-filelock==3.17.0
+filelock==3.18.0
     # via nipype
-fonttools==4.55.8
+fonttools==4.58.0
     # via matplotlib
-formulaic==0.5.2
+formulaic==1.1.1
+    # via pybids
+frozendict==2.4.6
     # via pybids
-fsspec==2025.2.0
+fsspec==2025.3.2
     # via universal-pathlib
-h5py==3.12.1
+h5py==3.13.0
     # via nitransforms
-humanize==4.11.0
+humanize==4.12.3
     # via
     #   datalad
     #   datalad-next
@@ -95,12 +94,10 @@ idna==3.10
     # via requests
 imageio==2.37.0
     # via scikit-image
-importlib-metadata==8.6.1
+importlib-metadata==8.7.0
     # via keyring
 importlib-resources==6.5.2
-    # via
-    #   nibabel
-    #   nireports
+    # via nibabel
 indexed-gzip==1.9.4
     # via smriprep
 interface-meta==1.3.0
@@ -119,7 +116,7 @@ jaraco-context==6.0.1
     #   keyrings-alt
 jaraco-functools==4.1.0
     # via keyring
-jinja2==3.1.5
+jinja2==3.1.6
     # via
     #   bokeh
     #   niworkflows
@@ -127,15 +124,11 @@ jmespath==1.0.1
     # via
     #   boto3
     #   botocore
-joblib==1.4.2
+joblib==1.5.0
     # via
     #   nilearn
     #   robustica
     #   scikit-learn
-jsonschema==4.23.0
-    # via bidsschematools
-jsonschema-specifications==2024.10.1
-    # via jsonschema
 keyring==25.6.0
     # via datalad
 keyrings-alt==5.0.2
@@ -154,16 +147,17 @@ looseversion==1.3.0
     #   nipype
     #   niworkflows
     #   smriprep
-lxml==5.3.0
+lxml==5.4.0
     # via
     #   nilearn
+    #   nireports
     #   prov
     #   svgutils
 mapca==0.0.5
     # via tedana
 markupsafe==3.0.2
     # via jinja2
-matplotlib==3.10.0
+matplotlib==3.10.3
     # via
     #   nireports
     #   nitime
@@ -175,7 +169,7 @@ migas==0.4.0
     # via
     #   nibabies (pyproject.toml)
     #   sdcflows
-more-itertools==10.6.0
+more-itertools==10.7.0
     # via
     #   datalad-next
     #   jaraco-classes
@@ -187,7 +181,7 @@ networkx==3.4.2
     #   nipype
     #   prov
     #   scikit-image
-nibabel==5.2.1
+nibabel==5.3.2
     # via
     #   mapca
     #   nibabies (pyproject.toml)
@@ -200,21 +194,23 @@ nibabel==5.2.1
     #   sdcflows
     #   smriprep
     #   tedana
-nilearn==0.10.4
+nilearn==0.11.1
     # via
     #   mapca
     #   nireports
     #   niworkflows
     #   tedana
-nipype==1.9.2
+nipype==1.10.0
     # via
     #   nibabies (pyproject.toml)
     #   nireports
     #   niworkflows
     #   sdcflows
     #   smriprep
-nireports==24.1.0
-    # via nibabies (pyproject.toml)
+nireports==25.0.1
+    # via
+    #   nibabies (pyproject.toml)
+    #   sdcflows
 nitime==0.11
     # via nibabies (pyproject.toml)
 nitransforms==24.1.1
@@ -222,14 +218,14 @@ nitransforms==24.1.1
     #   nibabies (pyproject.toml)
     #   niworkflows
     #   sdcflows
-niworkflows==1.12.2
+niworkflows==1.13.3
     # via
     #   nibabies (pyproject.toml)
     #   sdcflows
     #   smriprep
 num2words==0.5.14
     # via pybids
-numpy==2.1.1
+numpy==2.2.4
     # via
     #   bokeh
     #   contourpy
@@ -260,7 +256,7 @@ numpy==2.1.1
     #   transforms3d
 osfclient==0.0.5
     # via datalad-osf
-packaging==24.2
+packaging==25.0
     # via
     #   bokeh
     #   datalad
@@ -275,7 +271,7 @@ packaging==24.2
     #   pooch
     #   scikit-image
     #   smriprep
-pandas==2.2.2
+pandas==2.2.3
     # via
     #   bokeh
     #   formulaic
@@ -287,15 +283,15 @@ pandas==2.2.2
     #   robustica
     #   seaborn
     #   tedana
-patool==3.1.0
+patool==4.0.1
     # via datalad
-pillow==11.1.0
+pillow==11.2.1
     # via
     #   bokeh
     #   imageio
     #   matplotlib
     #   scikit-image
-platformdirs==4.3.6
+platformdirs==4.3.8
     # via
     #   datalad
     #   pooch
@@ -303,11 +299,11 @@ pooch==1.8.2
     # via nibabies (pyproject.toml)
 prov==2.0.1
     # via nipype
-psutil==6.1.1
+psutil==7.0.0
     # via nibabies (pyproject.toml)
-puremagic==1.28
+puremagic==1.29
     # via nipype
-pybids==0.18.1
+pybids==0.19.0
     # via
     #   nibabies (pyproject.toml)
     #   nireports
@@ -319,9 +315,9 @@ pybtex==0.24.0
     # via tedana
 pybtex-apa-style==1.3
     # via tedana
-pydot==3.0.4
+pydot==4.0.0
     # via nipype
-pyparsing==3.2.1
+pyparsing==3.2.3
     # via
     #   matplotlib
     #   pydot
@@ -335,7 +331,7 @@ python-dateutil==2.9.0.post0
     #   prov
 python-gitlab==5.6.0
     # via datalad
-pytz==2025.1
+pytz==2025.2
     # via pandas
 pyyaml==6.0.2
     # via
@@ -349,10 +345,6 @@ rdflib==6.3.2
     # via
     #   nipype
     #   prov
-referencing==0.36.2
-    # via
-    #   jsonschema
-    #   jsonschema-specifications
 requests==2.32.3
     # via
     #   datalad
@@ -368,23 +360,19 @@ requests-toolbelt==1.0.0
     # via python-gitlab
 robustica==0.1.4
     # via tedana
-rpds-py==0.22.3
-    # via
-    #   jsonschema
-    #   referencing
-s3transfer==0.11.2
+s3transfer==0.12.0
     # via boto3
-scikit-image==0.25.1
+scikit-image==0.25.2
     # via
     #   niworkflows
     #   sdcflows
-scikit-learn==1.5.2
+scikit-learn==1.6.1
     # via
     #   mapca
     #   nilearn
     #   robustica
     #   tedana
-scipy==1.14.1
+scipy==1.15.2
     # via
     #   formulaic
     #   mapca
@@ -399,15 +387,15 @@ scipy==1.14.1
     #   scikit-learn
     #   sdcflows
     #   tedana
-sdcflows==2.11.0
+sdcflows @ git+https://github.com/nipreps/sdcflows.git@main
     # via nibabies (pyproject.toml)
 seaborn==0.13.2
     # via
     #   nireports
     #   niworkflows
-simpleitk==2.4.1
+simpleitk==2.5.0
     # via nibabies (pyproject.toml)
-simplejson==3.19.3
+simplejson==3.20.1
     # via nipype
 six==1.17.0
     # via
@@ -415,15 +403,13 @@ six==1.17.0
     #   osfclient
     #   pybtex
     #   python-dateutil
-smriprep==0.17.0
+smriprep==0.18.0
     # via nibabies (pyproject.toml)
-sqlalchemy==2.0.37
+sqlalchemy==2.0.41
     # via pybids
 svgutils==0.3.4
-    # via
-    #   nireports
-    #   niworkflows
-tedana==24.0.2
+    # via niworkflows
+tedana==25.0.0
     # via nibabies (pyproject.toml)
 templateflow==24.2.2
     # via
@@ -432,17 +418,17 @@ templateflow==24.2.2
     #   niworkflows
     #   sdcflows
     #   smriprep
-threadpoolctl==3.5.0
+threadpoolctl==3.6.0
     # via
     #   scikit-learn
     #   tedana
-tifffile==2025.1.10
+tifffile==2025.5.10
     # via scikit-image
 toml==0.10.2
     # via
     #   nibabies (pyproject.toml)
     #   sdcflows
-tornado==6.4.2
+tornado==6.5
     # via bokeh
 tqdm==4.67.1
     # via
@@ -455,23 +441,22 @@ traits==7.0.2
     # via nipype
 transforms3d==0.4.2
     # via niworkflows
-typing-extensions==4.12.2
+typing-extensions==4.13.2
     # via
     #   formulaic
     #   nibabel
-    #   referencing
     #   sqlalchemy
-tzdata==2025.1
+tzdata==2025.2
     # via pandas
 universal-pathlib==0.2.6
     # via pybids
-urllib3==2.3.0
+urllib3==2.4.0
     # via
     #   botocore
     #   requests
 wrapt==1.17.2
     # via formulaic
-xyzservices==2025.1.0
+xyzservices==2025.4.0
     # via bokeh
 zipp==3.21.0
     # via importlib-metadata