Error code:   ConfigNamesError
Exception:    ValueError
Message:      Feature type 'Nifti' not found. Available feature types: ['Value', 'ClassLabel', 'Translation', 'TranslationVariableLanguages', 'LargeList', 'List', 'Array2D', 'Array3D', 'Array4D', 'Array5D', 'Audio', 'Image', 'Video', 'Pdf']
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 66, in compute_config_names_response
                  config_names = get_dataset_config_names(
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 161, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                                   ^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1031, in dataset_module_factory
                  raise e1 from None
                File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1004, in dataset_module_factory
                  ).get_module()
                    ^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 605, in get_module
                  dataset_infos = DatasetInfosDict.from_dataset_card_data(dataset_card_data)
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/info.py", line 386, in from_dataset_card_data
                  dataset_info = DatasetInfo._from_yaml_dict(dataset_card_data["dataset_info"])
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/info.py", line 317, in _from_yaml_dict
                  yaml_data["features"] = Features._from_yaml_list(yaml_data["features"])
                                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 2031, in _from_yaml_list
                  return cls.from_dict(from_yaml_inner(yaml_data))
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1876, in from_dict
                  obj = generate_from_dict(dic)
                        ^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1463, in generate_from_dict
                  return {key: generate_from_dict(value) for key, value in obj.items()}
                               ^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 1469, in generate_from_dict
                  raise ValueError(f"Feature type '{_type}' not found. Available feature types: {list(_FEATURE_TYPES.keys())}")
              ValueError: Feature type 'Nifti' not found. Available feature types: ['Value', 'ClassLabel', 'Translation', 'TranslationVariableLanguages', 'LargeList', 'List', 'Array2D', 'Array3D', 'Array4D', 'Array5D', 'Audio', 'Image', 'Video', 'Pdf']

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Aphasia Recovery Cohort (ARC) Dataset - Mini Sample

Dataset Description

This is a mini sample of the Aphasia Recovery Cohort (ARC) Dataset, formatted in BIDS (Brain Imaging Data Structure). The full dataset is available on OpenNeuro.

The Aphasia Recovery Cohort is an open-source chronic stroke repository containing neuroimaging data from aphasia patients.

Dataset Information

Full Dataset Name: Aphasia Recovery Cohort (ARC) Dataset
BIDS Version: 1.6.0
Dataset Type: raw
Original DOI: doi:10.18112/openneuro.ds004884.v1.0.2
License: CC0 (Public Domain)

Authors

Makayla Gibson
Roger Newman-Norlund
Leonardo Bonilha
Julius Fridriksson
Gregory Hickok
Argye E. Hillis
Dirk-Bart den Ouden
Chris Rorden

Citation

If you use this dataset, please cite:

@article{gibson2024aphasia,
  title={The Aphasia Recovery Cohort, an open-source chronic stroke repository},
  author={Gibson, Makayla and Newman-Norlund, Roger and Bonilha, Leonardo and Fridriksson, Julius and Hickok, Gregory and Hillis, Argye E and den Ouden, Dirk-Bart and Rorden, Chris},
  journal={Scientific Data},
  volume={11},
  number={1},
  pages={981},
  year={2024},
  publisher={Nature Publishing Group},
  doi={10.1038/s41597-024-03819-7},
  pmid={39251640}
}

Plain text citation: Gibson M, Newman-Norlund R, Bonilha L, Fridriksson J, Hickok G, Hillis AE, den Ouden DB, Rorden C. The Aphasia Recovery Cohort, an open-source chronic stroke repository. Sci Data. 2024 Sep 9;11(1):981. doi: 10.1038/s41597-024-03819-7. PMID: 39251640.

Funding

This work was supported by:

National Institute of Health Grant P50DC014664
National Institute of Health Grant U01DC011739
National Institute of Health Grant R01DC008355
National Institute of Health Grant RF1MH133701

Ethics

All data acquired from studies that were approved by the Institutional Review Board at the University of South Carolina. Because final dataset is fully anonymised, it meets exemption criteria.

Acknowledgements

Special thanks to the C-STAR participants, faculty and staff, as well as our collaborators.

Dataset Structure

This mini sample contains a subset of the full ARC dataset for testing and development purposes. It includes:

Subject: M2002
Multiple sessions
Anatomical (T1w, T2w), functional (BOLD), and diffusion (DWI) MRI data

Loading the Dataset

from datasets import load_dataset

# Load the mini BIDS dataset
ds = load_dataset("TobiasPitters/ds004884-mini")

# Access the data
example = ds["train"][0]
print(f"Subject: {example['subject']}")
print(f"Metadata: {example['metadata']}")  # Returns as Python dict
print(f"NIfTI data: {example['nifti']}")  # Lazy-loaded nibabel image

License

CC0 - Public Domain. You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission.

Datasets:

TobiasPitters
/

ds004884-mini