diff --git a/qsiprep/workflows/recon/interchange.py b/qsiprep/interfaces/interchange.py
similarity index 77%
rename from qsiprep/workflows/recon/interchange.py
rename to qsiprep/interfaces/interchange.py
index 4fbabf7b..aa4581f0 100644
--- a/qsiprep/workflows/recon/interchange.py
+++ b/qsiprep/interfaces/interchange.py
@@ -34,7 +34,7 @@
 if overlapping_names:
     raise Exception("Someone has added overlapping outputs between the anatomical "
         "and dwi inputs: " + " ".join(overlapping_names))
-    
+
 recon_workflow_input_fields = qsiprep_output_names + \
     recon_workflow_anatomical_input_fields
 default_input_set = set(recon_workflow_input_fields)
@@ -53,10 +53,34 @@ class ReconWorkflowInputs(SimpleInterface):
     output_spec = _ReconWorkflowInputsOutputSpec
 
     def _run_interface(self, runtime):
+        inputs = self.inputs.get()
         for name in recon_workflow_input_fields:
-            self._results[name] = self.inputs.get(name)
+            self._results[name] = inputs.get(name)
         return runtime
 
 for name in recon_workflow_input_fields:
     _ReconWorkflowInputsInputSpec.add_class_trait(name, traits.Any)
-    _ReconWorkflowInputsOutputSpec.add_class_trait(name, traits.Any)
\ No newline at end of file
+    _ReconWorkflowInputsOutputSpec.add_class_trait(name, traits.Any)
+
+
+class _ReconAnatomicalDataInputSpec(BaseInterfaceInputSpec):
+    pass
+
+
+class _ReconAnatomicalDataOutputSpec(TraitedSpec):
+    pass
+
+
+class ReconAnatomicalData(SimpleInterface):
+    input_spec = _ReconAnatomicalDataInputSpec
+    output_spec = _ReconAnatomicalDataOutputSpec
+
+    def _run_interface(self, runtime):
+        inputs = self.inputs.get()
+        for name in anatomical_workflow_outputs:
+            self._results[name] = inputs.get(name)
+        return runtime
+
+for name in anatomical_workflow_outputs:
+    _ReconAnatomicalDataInputSpec.add_class_trait(name, traits.Any)
+    _ReconAnatomicalDataOutputSpec.add_class_trait(name, traits.Any)
\ No newline at end of file
diff --git a/qsiprep/interfaces/mrtrix.py b/qsiprep/interfaces/mrtrix.py
index 03ada1a4..653154c1 100644
--- a/qsiprep/interfaces/mrtrix.py
+++ b/qsiprep/interfaces/mrtrix.py
@@ -214,16 +214,16 @@ class GenerateMasked5ttInputSpec(Generate5ttInputSpec):
         mandatory=True,
         desc='tissue segmentation algorithm')
     in_file = traits.Either(
-        File(exists=True), 
+        File(exists=True),
         traits.Directory(exists=True),
         argstr='%s',
         mandatory=True,
         position=1,
         desc='input T1w image or FreeSurfer directory')
     out_file = File(
-        argstr='%s', 
-        genfile=True, 
-        position=2, 
+        argstr='%s',
+        genfile=True,
+        position=2,
         desc='output image')
     mask = File(exists=True, argstr='-mask %s')
     amygdala_hipppocampi_subcortical_gm = traits.Bool(
@@ -232,7 +232,7 @@ class GenerateMasked5ttInputSpec(Generate5ttInputSpec):
     thalami_method = traits.Enum(
         "nuclei",
         "first",
-        "aseg", 
+        "aseg",
         argstr="-thalami %s")
     hippocampi_method = traits.Enum(
         "subfields",
@@ -880,10 +880,10 @@ def _run_interface(self, runtime):
         merge_weights = pe.Node(niu.Merge(num_nodes),
                                 name='merge_weights')
         merge_exemplars = pe.Node(niu.Merge(3), name='merge_exemplars')
-        compress_exemplars = pe.Node(CompressConnectome2Tck(), 
+        compress_exemplars = pe.Node(CompressConnectome2Tck(),
                                      name='compress_exemplars')
         outputnode = pe.Node(
-            niu.IdentityInterface(fields=['matfiles', 'tckfiles', 'weights']), 
+            niu.IdentityInterface(fields=['matfiles', 'tckfiles', 'weights']),
             name='outputnode')
         workflow.connect(merge_mats, 'out', outputnode, 'matfiles')
         workflow.connect(merge_tcks, 'out', outputnode, 'tckfiles')
@@ -935,7 +935,7 @@ def _run_interface(self, runtime):
                     workflow.connect(c2t_nodes[-1], 'exemplar_weights',
                                      merge_weights, 'in%d' % in_num)
                 in_num += 1
-        
+
         # Get the exemplar tcks and weights
         workflow.connect([
             (merge_tcks, merge_exemplars, [('out', "in1")]),
@@ -960,7 +960,7 @@ def _run_interface(self, runtime):
             wf_result = workflow.run(**plugin_settings)
         else:
             wf_result = workflow.run()
-        
+
         # Merge the connectivity matrices into a single file
         merge_node, = [node for node in list(wf_result.nodes) if node.name.endswith('merge_mats')]
         merged_connectivity_file = op.join(cwd, "combined_connectivity.mat")
@@ -1061,30 +1061,30 @@ class _CompressConnectome2TckOutputSpec(TraitedSpec):
 class CompressConnectome2Tck(SimpleInterface):
     input_spec = _CompressConnectome2TckInputSpec
     output_spec = _CompressConnectome2TckOutputSpec
-    
+
     def _run_interface(self, runtime):
         out_zip = op.join(runtime.cwd, self.inputs.out_zip)
         zipfh = zipfile.ZipFile(out_zip, "w")
         # Get the matrix csvs and add them to the zip
-        csvfiles = [fname for fname in self.inputs.files if fname.endswith(".csv") 
+        csvfiles = [fname for fname in self.inputs.files if fname.endswith(".csv")
                     and not fname.endswith("weights.csv")]
         for csvfile in csvfiles:
             zipfh.write(csvfile, arcname=_rename_connectome(csvfile, suffix='connectome.csv'),
                         compresslevel=8, compress_type=zipfile.ZIP_DEFLATED)
-        
+
         # Get the sift weights if they exist
         weightfiles = [fname for fname in self.inputs.files if fname.endswith("weights.csv")]
         for weightfile in weightfiles:
             zipfh.write(weightfile, arcname=_rename_connectome(weightfile, suffix='_weights.csv'),
                         compresslevel=8, compress_type=zipfile.ZIP_DEFLATED)
-        
+
         # Get the tck files
         tckfiles = [fname for fname in self.inputs.files if fname.endswith(".tck")
                     or fname.endswith(".tck.gz")]
         for tckfile in tckfiles:
-            zipfh.write(tckfile, arcname=_rename_connectome(tckfile, suffix='_exemplars.tck'), 
+            zipfh.write(tckfile, arcname=_rename_connectome(tckfile, suffix='_exemplars.tck'),
                         compresslevel=8, compress_type=zipfile.ZIP_DEFLATED)
-        
+
         zipfh.close()
         self._results["out_zip"] = out_zip
         return runtime
@@ -1101,7 +1101,10 @@ def _rename_connectome(connectome_csv, suffix="_connectome.csv"):
     """
     parts = connectome_csv.split(os.sep)
     conn_name = parts[-2]
-    image_name, = [part for part in parts if part.startswith("sub_") and part.endswith("recon_wf")]
+    try:
+        image_name, = [part for part in parts if part.startswith("sub_") and part.endswith("recon_wf")]
+    except Exception as ex:
+        raise Exception(f"unable to detect image name from these parts {parts}")
     image_name = image_name[:-len("_recon_wf")]
     return "connectome2tck/" +_rebids(image_name) + "_" + conn_name + suffix
 
@@ -1303,9 +1306,9 @@ class _ITKTransformConvertInputSpec(CommandLineInputSpec):
         mandatory=True,
         position=0)
     operation = traits.Enum(
-        "itk_import", 
-        default="itk_import", 
-        usedefault=True, 
+        "itk_import",
+        default="itk_import",
+        usedefault=True,
         posision=1,
         argstr="%s")
     out_transform = traits.File(
@@ -1328,13 +1331,13 @@ class ITKTransformConvert(CommandLine):
 
 class _TransformHeaderInputSpec(CommandLineInputSpec):
     transform_file = traits.File(
-        exists=True, 
-        position=0, 
+        exists=True,
+        position=0,
         mandatory=True,
         argstr="-linear %s")
     in_image = traits.File(
-        exists=True, 
-        mandatory=True, 
+        exists=True,
+        mandatory=True,
         position=1,
         argstr="%s")
     out_image = traits.File(
diff --git a/qsiprep/workflows/recon/amico.py b/qsiprep/workflows/recon/amico.py
index a626f6d9..e4b5e001 100644
--- a/qsiprep/workflows/recon/amico.py
+++ b/qsiprep/workflows/recon/amico.py
@@ -9,7 +9,7 @@
 import nipype.pipeline.engine as pe
 from nipype.interfaces import afni, utility as niu
 from qsiprep.interfaces.bids import ReconDerivativesDataSink
-from .interchange import recon_workflow_input_fields
+from ...interfaces.interchange import recon_workflow_input_fields
 from ...engine import Workflow
 from ...interfaces.amico import NODDI
 from ...interfaces.reports import CLIReconPeaksReport
@@ -57,7 +57,7 @@ def init_amico_noddi_fit_wf(omp_nthreads, available_anatomical_data,
 
 : """
     noddi_fit = pe.Node(
-        NODDI(**params), 
+        NODDI(**params),
         name="recon_noddi",
         n_procs=omp_nthreads)
     desc += """\
@@ -91,7 +91,7 @@ def init_amico_noddi_fit_wf(omp_nthreads, available_anatomical_data,
         (convert_to_fibgz, outputnode, [('fibgz_file', 'fibgz')])])
     if plot_reports:
         plot_peaks = pe.Node(
-            CLIReconPeaksReport(), 
+            CLIReconPeaksReport(),
             name='plot_peaks',
             n_procs=omp_nthreads)
         ds_report_peaks = pe.Node(
diff --git a/qsiprep/workflows/recon/anatomical.py b/qsiprep/workflows/recon/anatomical.py
index 4cc4c14e1..e03c491e 100644
--- a/qsiprep/workflows/recon/anatomical.py
+++ b/qsiprep/workflows/recon/anatomical.py
@@ -28,7 +28,7 @@
 from ...interfaces.freesurfer import find_fs_path
 from ...interfaces.gradients import ExtractB0s
 from ...interfaces.nilearn import MaskB0Series
-from .interchange import (qsiprep_anatomical_ingressed_fields,
+from ...interfaces.interchange import (qsiprep_anatomical_ingressed_fields,
     FS_FILES_TO_REGISTER, anatomical_workflow_outputs, recon_workflow_input_fields)
 from qsiprep.interfaces.utils import GetConnectivityAtlases
 
diff --git a/qsiprep/workflows/recon/base.py b/qsiprep/workflows/recon/base.py
index f50613e2..f3cfdadd 100644
--- a/qsiprep/workflows/recon/base.py
+++ b/qsiprep/workflows/recon/base.py
@@ -16,19 +16,23 @@
 from glob import glob
 from copy import deepcopy
 from nipype import __version__ as nipype_ver
+import nipype.pipeline.engine as pe
+from nipype.utils.filemanip import split_filename
 from nilearn import __version__ as nilearn_ver
 from dipy import __version__ as dipy_ver
 from pkg_resources import resource_filename as pkgrf
 from ...engine import Workflow
 from ...utils.sloppy_recon import make_sloppy
 from ...__about__ import __version__
-
+from ...interfaces.bids import QsiReconIngress
 import logging
 import json
 from bids.layout import BIDSLayout
 from .build_workflow import init_dwi_recon_workflow
-from .anatomical import init_recon_anatomical_wf
-from .interchange import anatomical_workflow_outputs
+from .anatomical import init_recon_anatomical_wf, init_dwi_recon_anatomical_workflow
+from ...interfaces.interchange import (anatomical_workflow_outputs, recon_workflow_anatomical_input_fields,
+                                       ReconWorkflowInputs,
+                                       qsiprep_output_names, recon_workflow_input_fields)
 
 LOGGER = logging.getLogger('nipype.workflow')
 
@@ -211,7 +215,10 @@ def init_single_subject_wf(
         extras_to_make=spec.get('anatomical', []),
         freesurfer_dir=freesurfer_input,
         name='anat_ingress_wf')
-    
+
+    # Connect the anatomical-only inputs. NOTE this is not to the inputnode!
+    LOGGER.info("Anatomical (T1w) available for recon: %s", available_anatomical_data)
+
     # Fill-in datasinks and reportlet datasinks for the anatomical workflow
     for _node in anat_ingress_wf.list_node_names():
         node_suffix = _node.split('.')[-1]
@@ -221,31 +228,81 @@ def init_single_subject_wf(
             anat_ingress_wf.get_node(_node).inputs.source_file = \
                 "anat/sub-{}_desc-preproc_T1w.nii.gz".format(subject_id)
 
-    # Connect the anatomical-only inputs. NOTE this is not to the inputnode!
-    LOGGER.info("Anatomical (T1w) available for recon: %s", available_anatomical_data)
-    to_connect = [('outputnode.' + name, 'qsirecon_anat_wf.inputnode.' + name) 
-                  for name in anatomical_workflow_outputs]
+    # Get the anatomical data (masks, atlases, etc)
+    atlas_names = spec.get('atlases', [])
 
     # create a processing pipeline for the dwis in each session
     dwi_recon_wfs = {}
+    dwi_individual_anatomical_wfs = {}
+    recon_full_inputs = {}
+    dwi_ingress_nodes = {}
     for dwi_file in dwi_files:
+        wf_name = _get_wf_name(dwi_file)
+
+        # Get the preprocessed DWI and all the related preprocessed images
+        dwi_ingress_nodes[dwi_file] = pe.Node(
+            QsiReconIngress(dwi_file=dwi_file),
+            name=wf_name + "_ingressed_dwi_data")
+
+        # Create scan-specific anatomical data (mask, atlas configs, odf ROIs for reports)
+        dwi_individual_anatomical_wfs[dwi_file], dwi_available_anatomical_data = \
+            init_dwi_recon_anatomical_workflow(
+                atlas_names=atlas_names,
+                omp_nthreads=omp_nthreads,
+                infant_mode=False,
+                prefer_dwi_mask=False,
+                sloppy=sloppy,
+                b0_threshold=b0_threshold,
+                freesurfer_dir=freesurfer_input,
+                extras_to_make=spec.get('anatomical', []),
+                name=wf_name + "_anat_wf",
+                **available_anatomical_data)
+
+        # This node holds all the inputs that will go to the recon workflow.
+        # It is the definitive place to check what the input files are
+        recon_full_inputs[dwi_file] = pe.Node(ReconWorkflowInputs(), name=wf_name + "_recon_inputs")
+
+        # This is the actual recon workflow for this dwi file
         dwi_recon_wfs[dwi_file] = init_dwi_recon_workflow(
-            dwi_file=dwi_file,
-            available_anatomical_data=available_anatomical_data,
+            available_anatomical_data=dwi_available_anatomical_data,
             workflow_spec=spec,
-            sloppy=sloppy,
-            prefer_dwi_mask=False,
-            infant_mode=False,
-            b0_threshold=b0_threshold,
+            name=wf_name + "_recon_wf",
             reportlets_dir=reportlets_dir,
             output_dir=output_dir,
             omp_nthreads=omp_nthreads,
             skip_odf_plots=skip_odf_plots)
-        workflow.connect([(anat_ingress_wf, dwi_recon_wfs[dwi_file], to_connect)])
+
+        # Connect the collected diffusion data (gradients, etc) to the inputnode
+        workflow.connect([
+
+            # The dwi data
+            (dwi_ingress_nodes[dwi_file], recon_full_inputs[dwi_file], [
+                (trait, trait) for trait in qsiprep_output_names]),
+
+            # subject anatomical data to dwi
+            (anat_ingress_wf, dwi_individual_anatomical_wfs[dwi_file],
+             [("outputnode."+trait, "inputnode."+trait) for trait in anatomical_workflow_outputs]),
+            (dwi_ingress_nodes[dwi_file], dwi_individual_anatomical_wfs[dwi_file],
+             [(trait, "inputnode." + trait) for trait in qsiprep_output_names]),
+
+            # subject dwi-specific anatomical to recon inputs
+            (dwi_individual_anatomical_wfs[dwi_file], recon_full_inputs[dwi_file], [
+                ("outputnode." + trait, trait) for trait in recon_workflow_anatomical_input_fields]),
+
+            # recon inputs to recon workflow
+            (recon_full_inputs[dwi_file], dwi_recon_wfs[dwi_file],
+             [(trait, "inputnode." + trait) for trait in recon_workflow_input_fields])
+        ])
 
     return workflow
 
 
+def _get_wf_name(dwi_file):
+    basedir, fname, ext = split_filename(dwi_file)
+    tokens = fname.split("_")
+    return "_".join(tokens[:-1]).replace("-", "_")
+
+
 def _load_recon_spec(spec_name, sloppy=False):
     prepackaged_dir = pkgrf("qsiprep", "data/pipelines")
     prepackaged = [op.split(fname)[1][:-5] for fname in glob(prepackaged_dir+"/*.json")]
diff --git a/qsiprep/workflows/recon/build_workflow.py b/qsiprep/workflows/recon/build_workflow.py
index edacbfd9..1e09a385 100644
--- a/qsiprep/workflows/recon/build_workflow.py
+++ b/qsiprep/workflows/recon/build_workflow.py
@@ -4,7 +4,7 @@
 from nipype.interfaces import ants, utility as niu
 from nipype.utils.filemanip import split_filename
 from qsiprep.interfaces import anatomical
-from qsiprep.interfaces.bids import QsiReconIngress, ReconDerivativesDataSink
+
 from .dsi_studio import (init_dsi_studio_recon_wf, init_dsi_studio_export_wf,
                          init_dsi_studio_connectivity_wf, init_dsi_studio_tractography_wf,
                          init_dsi_studio_autotrack_wf)
@@ -19,10 +19,7 @@
 from .utils import init_conform_dwi_wf, init_discard_repeated_samples_wf
 from .steinhardt import init_steinhardt_order_param_wf
 from ...engine import Workflow
-from .interchange import (qsiprep_output_names, default_input_set,
-    recon_workflow_input_fields, recon_workflow_anatomical_input_fields,
-    ReconWorkflowInputs)
-from .anatomical import init_dwi_recon_anatomical_workflow
+from ...interfaces.interchange import (default_input_set, recon_workflow_input_fields)
 
 LOGGER = logging.getLogger('nipype.interface')
 
@@ -33,50 +30,18 @@ def _check_repeats(nodelist):
         raise Exception
 
 
-def init_dwi_recon_workflow(dwi_file, workflow_spec, output_dir, prefer_dwi_mask,
-                            reportlets_dir, available_anatomical_data, omp_nthreads, b0_threshold,
-                            infant_mode, skip_odf_plots, freesurfer_dir=None,
-                            sloppy=False, name="recon_wf"):
+def init_dwi_recon_workflow(workflow_spec, output_dir,
+                            reportlets_dir, available_anatomical_data, omp_nthreads,
+                            skip_odf_plots, name="recon_wf"):
     """Convert a workflow spec into a nipype workflow.
 
     """
-    # Get the preprocessed DWI and all the related preprocessed images
-    qsiprep_preprocessed_dwi_data = pe.Node(
-        QsiReconIngress(dwi_file=dwi_file),
-        name="qsiprep_preprocessed_dwi_data")
-
-    # Get the anatomical data (masks, atlases, etc)
-    atlas_names = workflow_spec.get('atlases', [])
-    registered_anat_wf, available_anatomical_data = init_dwi_recon_anatomical_workflow(
-        atlas_names=atlas_names,
-        omp_nthreads=omp_nthreads,
-        infant_mode=infant_mode,
-        prefer_dwi_mask=prefer_dwi_mask,
-        sloppy=sloppy,
-        b0_threshold=b0_threshold,
-        extras_to_make=workflow_spec.get('anatomical', []),
-        freesurfer_dir=freesurfer_dir,
-        name="qsirecon_anat_wf",
-        **available_anatomical_data)
-
-    # For doctests
-    # if not workflow_spec['name'] == 'fake':
-    #     inputnode.inputs.dwi_file = dwi_file
-
-    workflow = Workflow(name=_get_wf_name(dwi_file) + "_" + name)
+
+    workflow = Workflow(name=name)
     inputnode = pe.Node(
         niu.IdentityInterface(fields=recon_workflow_input_fields),
         name='inputnode')
 
-    # Connect the collected diffusion data (gradients, etc) to the inputnode
-    workflow.connect([
-        (qsiprep_preprocessed_dwi_data, registered_anat_wf, [
-            (trait, 'inputnode.' + trait) for trait in qsiprep_output_names]),
-        (registered_anat_wf, inputnode, [
-            ('outputnode.'+trait, trait) for trait in
-            recon_workflow_input_fields])
-    ])
-
     # Read nodes from workflow spec, make sure we can implement them
     nodes_to_add = []
     for node_spec in workflow_spec['nodes']:
@@ -239,8 +204,3 @@ def workflow_from_spec(omp_nthreads, available_anatomical_data, node_spec,
 def _as_connections(attr_list, src_prefix='', dest_prefix=''):
     return [(src_prefix + item, dest_prefix + item) for item in attr_list]
 
-
-def _get_wf_name(dwi_file):
-    basedir, fname, ext = split_filename(dwi_file)
-    tokens = fname.split("_")
-    return "_".join(tokens[:-1]).replace("-", "_")
diff --git a/qsiprep/workflows/recon/converters.py b/qsiprep/workflows/recon/converters.py
index 776d106c..bb9e761f 100644
--- a/qsiprep/workflows/recon/converters.py
+++ b/qsiprep/workflows/recon/converters.py
@@ -11,7 +11,7 @@
 import logging
 from ...interfaces.converters import FODtoFIBGZ
 from ...interfaces.bids import ReconDerivativesDataSink
-from .interchange import recon_workflow_input_fields
+from ...interfaces.interchange import recon_workflow_input_fields
 from ...engine import Workflow
 from ...interfaces.images import ConformDwi
 LOGGER = logging.getLogger('nipype.workflow')
diff --git a/qsiprep/workflows/recon/dipy.py b/qsiprep/workflows/recon/dipy.py
index e094e1bb..04029556 100644
--- a/qsiprep/workflows/recon/dipy.py
+++ b/qsiprep/workflows/recon/dipy.py
@@ -10,7 +10,7 @@
 from nipype.interfaces import afni, utility as niu
 from qsiprep.interfaces.bids import ReconDerivativesDataSink
 from ...interfaces.dipy import BrainSuiteShoreReconstruction, KurtosisReconstruction, MAPMRIReconstruction
-from .interchange import recon_workflow_input_fields
+from ...interfaces.interchange import recon_workflow_input_fields
 from ...engine import Workflow
 from ...interfaces.reports import CLIReconPeaksReport
 
@@ -359,7 +359,7 @@ def init_dipy_mapmri_recon_wf(omp_nthreads, available_anatomical_data, name="dip
                                  ('fod_sh_mif', 'fod_sh_mif')])])
     if plot_reports:
         plot_peaks = pe.Node(
-            CLIReconPeaksReport(), 
+            CLIReconPeaksReport(),
             name='plot_peaks',
             n_procs=omp_nthreads)
         ds_report_peaks = pe.Node(
@@ -431,7 +431,7 @@ def init_dipy_dki_recon_wf(omp_nthreads, available_anatomical_data, name="dipy_d
             True writes out a MRTrix mif file with sh coefficients
         radial_order: int
             An even integer that represent the order of the basis
-        
+
     """
 
     inputnode = pe.Node(niu.IdentityInterface(fields=recon_workflow_input_fields),
@@ -472,7 +472,7 @@ def init_dipy_dki_recon_wf(omp_nthreads, available_anatomical_data, name="dipy_d
 
     if plot_reports and False:
         plot_peaks = pe.Node(
-            CLIReconPeaksReport(peaks_only=True), 
+            CLIReconPeaksReport(peaks_only=True),
             name='plot_peaks',
             n_procs=omp_nthreads)
         ds_report_peaks = pe.Node(
diff --git a/qsiprep/workflows/recon/dsi_studio.py b/qsiprep/workflows/recon/dsi_studio.py
index db4b1a9c..44b68759 100644
--- a/qsiprep/workflows/recon/dsi_studio.py
+++ b/qsiprep/workflows/recon/dsi_studio.py
@@ -18,7 +18,7 @@
 import logging
 from ...interfaces.bids import ReconDerivativesDataSink
 from ...interfaces.converters import DSIStudioTrkToTck
-from .interchange import recon_workflow_input_fields
+from ...interfaces.interchange import recon_workflow_input_fields
 from ...engine import Workflow
 from ...interfaces.reports import CLIReconPeaksReport, ConnectivityReport
 
diff --git a/qsiprep/workflows/recon/dynamics.py b/qsiprep/workflows/recon/dynamics.py
index 1eee9071..ef5d239b 100644
--- a/qsiprep/workflows/recon/dynamics.py
+++ b/qsiprep/workflows/recon/dynamics.py
@@ -10,7 +10,7 @@
 import logging
 from qsiprep.interfaces.connectivity import Controllability
 from qsiprep.interfaces.bids import ReconDerivativesDataSink
-from .interchange import recon_workflow_input_fields
+from ...interfaces.interchange import recon_workflow_input_fields
 LOGGER = logging.getLogger('nipype.workflow')
 
 
diff --git a/qsiprep/workflows/recon/mrtrix.py b/qsiprep/workflows/recon/mrtrix.py
index 39590a15..ffe357db 100644
--- a/qsiprep/workflows/recon/mrtrix.py
+++ b/qsiprep/workflows/recon/mrtrix.py
@@ -2,10 +2,10 @@
 MRTrix workflows
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-Note that in nipype interfaces the threading-controlling attribute is 
-``nthreads``, not the typical ``num_threads`` expected by nipype. 
-To keep threading consistent between nipype and mrtrix, the 
-``nthreads`` attribute needs to be set in the interface and the 
+Note that in nipype interfaces the threading-controlling attribute is
+``nthreads``, not the typical ``num_threads`` expected by nipype.
+To keep threading consistent between nipype and mrtrix, the
+``nthreads`` attribute needs to be set in the interface and the
 ``n_procs`` attribute needs to be set on the Node.
 
 
@@ -21,7 +21,7 @@
 from qsiprep.interfaces.mrtrix import (
     EstimateFOD, SS3TEstimateFOD, MRTrixIngress, SS3TDwi2Response, GlobalTractography,
     MRTrixAtlasGraph, SIFT2, TckGen, MTNormalize)
-from .interchange import recon_workflow_input_fields
+from ...interfaces.interchange import recon_workflow_input_fields
 from ...engine import Workflow
 
 LOGGER = logging.getLogger('nipype.interface')
@@ -47,9 +47,9 @@ def init_mrtrix_csd_recon_wf(omp_nthreads, available_anatomical_data, name="mrtr
         *Default qsiprep inputs*
 
         qsiprep_5tt_hsvs
-            A hybrid surface volume segmentation 5tt image aligned with the 
+            A hybrid surface volume segmentation 5tt image aligned with the
             QSIPrep T1w
-        
+
 
     Outputs
 
@@ -137,7 +137,7 @@ def init_mrtrix_csd_recon_wf(omp_nthreads, available_anatomical_data, name="mrtr
     method_5tt = response.pop("method_5tt","dhollander")
     # Use dwi2response from 3Tissue for updated dhollander
     estimate_response = pe.Node(
-        SS3TDwi2Response(**response), 
+        SS3TDwi2Response(**response),
         name='estimate_response',
         n_procs=omp_nthreads)
 
@@ -150,13 +150,13 @@ def init_mrtrix_csd_recon_wf(omp_nthreads, available_anatomical_data, name="mrtr
 
     if fod_algorithm in ('msmt_csd', 'csd'):
         estimate_fod = pe.Node(
-            EstimateFOD(**fod), 
+            EstimateFOD(**fod),
             name='estimate_fod',
             n_procs=omp_nthreads)
         desc += ' Reconstruction was done using MRtrix3 (@mrtrix3).'
     elif fod_algorithm == 'ss3t':
         estimate_fod = pe.Node(
-            SS3TEstimateFOD(**fod), 
+            SS3TEstimateFOD(**fod),
             name='estimate_fod',
             n_procs=omp_nthreads)
         desc += """ \
@@ -191,7 +191,7 @@ def init_mrtrix_csd_recon_wf(omp_nthreads, available_anatomical_data, name="mrtr
         intensity_norm = pe.Node(
             MTNormalize(
                 nthreads=omp_nthreads,
-                inlier_mask='inliers.nii.gz', 
+                inlier_mask='inliers.nii.gz',
                 norm_image='norm.nii.gz'),
             name='intensity_norm',
             n_procs=omp_nthreads)
@@ -209,7 +209,7 @@ def init_mrtrix_csd_recon_wf(omp_nthreads, available_anatomical_data, name="mrtr
     if plot_reports:
         # Make a visual report of the model
         plot_peaks = pe.Node(
-            CLIReconPeaksReport(), 
+            CLIReconPeaksReport(),
             name='plot_peaks',
             n_procs=omp_nthreads)
         ds_report_peaks = pe.Node(
@@ -233,7 +233,7 @@ def init_mrtrix_csd_recon_wf(omp_nthreads, available_anatomical_data, name="mrtr
                 name='ds_report_odfs',
                 run_without_submitting=True)
             workflow.connect(plot_peaks, 'odf_report', ds_report_odfs, 'in_file')
-        
+
         fod_source, fod_key = (estimate_fod, "wm_odf") if not run_mtnormalize \
             else (intensity_norm, "wm_normed_odf")
         workflow.connect(fod_source, fod_key, plot_peaks, "mif_file")
@@ -452,7 +452,7 @@ def init_mrtrix_tractography_wf(omp_nthreads, available_anatomical_data, name="m
     sift_params = params.get("sift2", {})
     sift_params['nthreads'] = omp_nthreads
     tracking = pe.Node(
-        TckGen(**tracking_params), 
+        TckGen(**tracking_params),
         name='tractography',
         n_procs=omp_nthreads)
     workflow.connect([
@@ -475,7 +475,7 @@ def init_mrtrix_tractography_wf(omp_nthreads, available_anatomical_data, name="m
 
     if use_sift2:
         tck_sift2 = pe.Node(
-            SIFT2(**sift_params), 
+            SIFT2(**sift_params),
             name="tck_sift2",
             n_procs=omp_nthreads)
         workflow.connect([
@@ -542,13 +542,13 @@ def init_mrtrix_connectivity_wf(omp_nthreads, available_anatomical_data, name="m
         (inputnode, calc_connectivity, [('atlas_configs', 'atlas_configs'),
                                         ('tck_file', 'in_file'),
                                         ('sift_weights', 'in_weights')]),
-        
+
         (calc_connectivity, outputnode, [('connectivity_matfile', 'matfile')])
     ])
 
     if plot_reports:
         plot_connectivity = pe.Node(
-            ConnectivityReport(), 
+            ConnectivityReport(),
             name='plot_connectivity',
             n_procs=omp_nthreads)
         ds_report_connectivity = pe.Node(
diff --git a/qsiprep/workflows/recon/pyafq.py b/qsiprep/workflows/recon/pyafq.py
index 5d3f7a5f..327f842d 100644
--- a/qsiprep/workflows/recon/pyafq.py
+++ b/qsiprep/workflows/recon/pyafq.py
@@ -11,7 +11,7 @@
 import AFQ
 import AFQ.utils.bin as afb
 from qsiprep.interfaces.pyafq import PyAFQRecon
-from .interchange import recon_workflow_input_fields
+from ...interfaces.interchange import recon_workflow_input_fields
 from ...interfaces.bids import ReconDerivativesDataSink
 LOGGER = logging.getLogger('nipype.workflow')
 
diff --git a/qsiprep/workflows/recon/steinhardt.py b/qsiprep/workflows/recon/steinhardt.py
index efe7281b..0a9f906f 100644
--- a/qsiprep/workflows/recon/steinhardt.py
+++ b/qsiprep/workflows/recon/steinhardt.py
@@ -9,7 +9,7 @@
 import nipype.pipeline.engine as pe
 from nipype.interfaces import afni, utility as niu
 from qsiprep.interfaces.bids import ReconDerivativesDataSink
-from .interchange import recon_workflow_input_fields
+from ...interfaces.interchange import recon_workflow_input_fields
 from ...engine import Workflow
 from ...interfaces.mrtrix import MRConvert
 from ...interfaces.anatomical import CalculateSOP
@@ -55,7 +55,7 @@ def init_steinhardt_order_param_wf(omp_nthreads, available_anatomical_data,
 
 : """
     sh_mif_to_nifti = pe.Node(
-        MRConvert(out_file="SH.nii", args="-strides -1,-2,3"), 
+        MRConvert(out_file="SH.nii", args="-strides -1,-2,3"),
         name="sh_mif_to_nifti")
     calc_sop = pe.Node(CalculateSOP(**params), name="calc_sop")
     desc += """\
diff --git a/qsiprep/workflows/recon/utils.py b/qsiprep/workflows/recon/utils.py
index 89bfbc30..974fb87e 100644
--- a/qsiprep/workflows/recon/utils.py
+++ b/qsiprep/workflows/recon/utils.py
@@ -11,13 +11,13 @@
 import nipype.interfaces.utility as niu
 import logging
 from qsiprep.interfaces.gradients import RemoveDuplicates
-from .interchange import recon_workflow_input_fields
+from ...interfaces.interchange import recon_workflow_input_fields
 from qsiprep.interfaces import ConformDwi
 from qsiprep.interfaces.mrtrix import MRTrixGradientTable
 LOGGER = logging.getLogger('nipype.workflow')
 
 
-def init_conform_dwi_wf(omp_nthreads, available_anatomical_data, 
+def init_conform_dwi_wf(omp_nthreads, available_anatomical_data,
                         name="conform_dwi", output_suffix="", params={}):
     """If data were preprocessed elsewhere, ensure the gradients and images
     conform to LPS+ before running other parts of the pipeline."""
diff --git a/qsiprep/workflows/reports.py b/qsiprep/workflows/reports.py
index 71b8299d..e984dad7 100644
--- a/qsiprep/workflows/reports.py
+++ b/qsiprep/workflows/reports.py
@@ -20,7 +20,7 @@
 from ..interfaces.bids import QsiReconIngress
 from ..interfaces.reports import InteractiveReport
 from ..utils.bids import collect_data
-from .recon.interchange import qsiprep_output_names, recon_workflow_input_fields
+from ..interfaces.interchange import qsiprep_output_names, recon_workflow_input_fields
 
 
 LOGGER = logging.getLogger('nipype.workflow')