Any FreeSurfer output space is required when using --project-goodvoxels

[demidenm]

What happened?

While running fMRIPrep v23.1.0 on three separate subjects from three separate datasets, preprocessing failed at the node name *.func_derivatives_wf.ds_goodvoxels_mask which did not occur for same subject using v23.0.0rc0

One specific example of the error is below:

Traceback:
Traceback (most recent call last):
File "/opt/conda/envs/fmriprep/lib/python3.10/site-packages/nipype/interfaces/base/core.py", line 397, in run
runtime = self._run_interface(runtime)
File "/opt/conda/envs/fmriprep/lib/python3.10/site-packages/niworkflows/interfaces/bids.py", line 758, in _run_interface
sidecar.write_text(dumps(self._metadata, sort_keys=True, indent=2))
File "/opt/conda/envs/fmriprep/lib/python3.10/json/init.py", line 238, in dumps
**kw).encode(obj)
File "/opt/conda/envs/fmriprep/lib/python3.10/json/encoder.py", line 201, in encode
chunks = list(chunks)
File "/opt/conda/envs/fmriprep/lib/python3.10/json/encoder.py", line 431, in _iterencode
yield from _iterencode_dict(o, _current_indent_level)
File "/opt/conda/envs/fmriprep/lib/python3.10/json/encoder.py", line 405, in _iterencode_dict
yield from chunks
File "/opt/conda/envs/fmriprep/lib/python3.10/json/encoder.py", line 438, in _iterencode
o = _default(o)
File "/opt/conda/envs/fmriprep/lib/python3.10/json/encoder.py", line 179, in default
raise TypeError(f'Object of type {o.class.name} '
TypeError: Object of type _Undefined is not JSON serializable

What command did you use?

fMRIPrep command: /opt/conda/envs/fmriprep/bin/fmriprep /data /out participant --participant-label sub-01 -t mid --ignore slicetiming --fs-license-file /home/users/demidenm/fs/license.txt --fd-spike-threshold .9 --output-space MNI152NLin2009cAsym:res-2 --project-goodvoxels --cifti-output 91k --resource-monitor -vv -w /scratch/groups/russpold/AHRB

What version of fMRIPrep are you running?

21.1.0

How are you running fMRIPrep?

Docker

Is your data BIDS valid?

Yes

Are you reusing any previously computed results?

No

Please copy and paste any relevant log output.

Node: fmriprep_23_1_wf.single_subject_01_wf.func_preproc_ses_1_task_mid_run_01_wf.func_derivatives_wf.ds_goodvoxels_mask
Working directory: /scratch/groups/russpold/AHRB/fmriprep_23_1_wf/single_subject_01_wf/func_preproc_ses_1_task_mid_run_01_wf/func_derivatives_wf/ds_goodvoxels_mask

Node inputs:

acquisition = <undefined>
atlas = <undefined>
base_directory = /out
ceagent = <undefined>
check_hdr = True
cohort = <undefined>
compress = [True]
data_dtype = <undefined>
datatype = <undefined>
density = <undefined>
desc = goodvoxels
direction = <undefined>
dismiss_entities = ['echo']
echo = <undefined>
extension = <undefined>
flip = <undefined>
fmap = <undefined>
fmapid = <undefined>
from = <undefined>
hemi = <undefined>
in_file = ['/scratch/groups/russpold/AHRB/fmriprep_23_1_wf/single_subject_01_wf/func_preproc_ses_1_task_mid_run_01_wf/bold_fsLR_resampling_wf/goodvoxels_bold_mask_wf/goodvoxels_mask/vol0000_xform-00000_clipped_merged_std_maths_maths_maths_thresh_maths.nii.gz']
inv = <undefined>
keys = <undefined>
label = <undefined>
meta_dict = <undefined>
modality = <undefined>
mode = <undefined>
model = <undefined>
mt = <undefined>
part = <undefined>
proc = <undefined>
reconstruction = <undefined>
recording = <undefined>
resolution = <undefined>
roi = <undefined>
run = <undefined>
scans = <undefined>
session = <undefined>
source_file = ['/data/sub-01/ses-1/func/sub-01_ses-1_task-mid_run-01_bold.nii.gz']
space = T1w
subject = <undefined>
subset = <undefined>
suffix = mask
task = <undefined>
to = <undefined>

Traceback (most recent call last):
  File "/opt/conda/envs/fmriprep/lib/python3.10/site-packages/nipype/pipeline/plugins/multiproc.py", line 344, in _send_procs_to_workers
    self.procs[jobid].run(updatehash=updatehash)
  File "/opt/conda/envs/fmriprep/lib/python3.10/site-packages/nipype/pipeline/engine/nodes.py", line 527, in run
    result = self._run_interface(execute=True)
  File "/opt/conda/envs/fmriprep/lib/python3.10/site-packages/nipype/pipeline/engine/nodes.py", line 645, in _run_interface
    return self._run_command(execute)
  File "/opt/conda/envs/fmriprep/lib/python3.10/site-packages/nipype/pipeline/engine/nodes.py", line 771, in _run_command
    raise NodeExecutionError(msg)
nipype.pipeline.engine.nodes.NodeExecutionError: Exception raised while executing Node ds_goodvoxels_mask.

Traceback:
	Traceback (most recent call last):
	  File "/opt/conda/envs/fmriprep/lib/python3.10/site-packages/nipype/interfaces/base/core.py", line 397, in run
	    runtime = self._run_interface(runtime)
	  File "/opt/conda/envs/fmriprep/lib/python3.10/site-packages/niworkflows/interfaces/bids.py", line 758, in _run_interface
	    sidecar.write_text(dumps(self._metadata, sort_keys=True, indent=2))
	  File "/opt/conda/envs/fmriprep/lib/python3.10/json/__init__.py", line 238, in dumps
	    **kw).encode(obj)
	  File "/opt/conda/envs/fmriprep/lib/python3.10/json/encoder.py", line 201, in encode
	    chunks = list(chunks)
	  File "/opt/conda/envs/fmriprep/lib/python3.10/json/encoder.py", line 431, in _iterencode
	    yield from _iterencode_dict(o, _current_indent_level)
	  File "/opt/conda/envs/fmriprep/lib/python3.10/json/encoder.py", line 405, in _iterencode_dict
	    yield from chunks
	  File "/opt/conda/envs/fmriprep/lib/python3.10/json/encoder.py", line 438, in _iterencode
	    o = _default(o)
	  File "/opt/conda/envs/fmriprep/lib/python3.10/json/encoder.py", line 179, in default
	    raise TypeError(f'Object of type {o.__class__.__name__} '
	TypeError: Object of type _Undefined is not JSON serializable

Additional information / screenshots

This error occurs on two different systems with comparable resource requirements.

[mgxd]

Thanks for the report - I think the problem is that we are no longer adding a default freesurfer space. To see if you can get around this for now, could you try adding fsnative as an additional --output-spaces?

[demidenm]

@mgxd - Sounds good, thanks! Retrying now!

[demidenm]

adding fsnative to the --out-space resolved this error. Thanks again!

[mgxd]

Leaving this open since we should handle this internally, but glad to hear the workaround resolved it!