Datasets:

xenificity
/

HumanDignityMRI

DOI:

Dataset Viewer

Split (1)

train

The dataset viewer is not available for this split.

Cannot load the dataset split (in streaming mode) to extract the first rows.

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
Modality: string
MagneticFieldStrength: int64
ImagingFrequency: double
Manufacturer: string
ManufacturersModelName: string
BodyPart: string
PatientPosition: string
SoftwareVersions: string
MRAcquisitionType: string
SeriesDescription: string
ProtocolName: string
ScanningSequence: string
SequenceVariant: string
ScanOptions: string
SequenceName: string
ImageType: list<item: string>
  child 0, item: string
NonlinearGradientCorrection: bool
SeriesNumber: int64
AcquisitionTime: string
AcquisitionNumber: int64
SliceThickness: int64
SAR: double
TablePosition: list<item: int64>
  child 0, item: int64
EchoTime: double
RepetitionTime: double
SpoilingState: bool
InversionTime: double
FlipAngle: int64
PartialFourier: int64
BaseResolution: int64
ShimSetting: list<item: int64>
  child 0, item: int64
TxRefAmp: double
PhaseResolution: int64
ReceiveCoilName: string
ReceiveCoilActiveElements: string
PulseSequenceDetails: string
RefLinesPE: int64
CoilCombinationMethod: string
ConsistencyInfo: string
MatrixCoilMode: string
PercentPhaseFOV: int64
PercentSampling: int64
PhaseEncodingSteps: int64
AcquisitionMatrixPE: int64
ReconMatrixPE: int64
ParallelReductionFactorInPlane: int64
PixelBandwidth: int64
ImageOrientationPatientDICOM: list<item: double>
  child 0, item: double
InPlanePhaseEncodingDirectionDICOM: string
BidsGuess: list<item: string>
  child 0, item: string
ConversionSoftware: string
ConversionSoftwareVersion: string
ReferencesAndLinks: list<item: null>
  child 0, item: null
Authors: list<item: string>
  child 0, item: string
Name: string
DatasetType: string
Acknowledgements: string
DatasetDOI: string
License: string
HowToAcknowledge: string
BIDSVersion: string
Funding: list<item: string>
  child 0, item: string
to
{'Name': Value('string'), 'BIDSVersion': Value('string'), 'DatasetType': Value('string'), 'License': Value('string'), 'Authors': List(Value('string')), 'Acknowledgements': Value('string'), 'HowToAcknowledge': Value('string'), 'Funding': List(Value('string')), 'ReferencesAndLinks': List(Value('null')), 'DatasetDOI': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 289, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 124, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              Modality: string
              MagneticFieldStrength: int64
              ImagingFrequency: double
              Manufacturer: string
              ManufacturersModelName: string
              BodyPart: string
              PatientPosition: string
              SoftwareVersions: string
              MRAcquisitionType: string
              SeriesDescription: string
              ProtocolName: string
              ScanningSequence: string
              SequenceVariant: string
              ScanOptions: string
              SequenceName: string
              ImageType: list<item: string>
                child 0, item: string
              NonlinearGradientCorrection: bool
              SeriesNumber: int64
              AcquisitionTime: string
              AcquisitionNumber: int64
              SliceThickness: int64
              SAR: double
              TablePosition: list<item: int64>
                child 0, item: int64
              EchoTime: double
              RepetitionTime: double
              SpoilingState: bool
              InversionTime: double
              FlipAngle: int64
              PartialFourier: int64
              BaseResolution: int64
              ShimSetting: list<item: int64>
                child 0, item: int64
              TxRefAmp: double
              PhaseResolution: int64
              ReceiveCoilName: string
              ReceiveCoilActiveElements: string
              PulseSequenceDetails: string
              RefLinesPE: int64
              CoilCombinationMethod: string
              ConsistencyInfo: string
              MatrixCoilMode: string
              PercentPhaseFOV: int64
              PercentSampling: int64
              PhaseEncodingSteps: int64
              AcquisitionMatrixPE: int64
              ReconMatrixPE: int64
              ParallelReductionFactorInPlane: int64
              PixelBandwidth: int64
              ImageOrientationPatientDICOM: list<item: double>
                child 0, item: double
              InPlanePhaseEncodingDirectionDICOM: string
              BidsGuess: list<item: string>
                child 0, item: string
              ConversionSoftware: string
              ConversionSoftwareVersion: string
              ReferencesAndLinks: list<item: null>
                child 0, item: null
              Authors: list<item: string>
                child 0, item: string
              Name: string
              DatasetType: string
              Acknowledgements: string
              DatasetDOI: string
              License: string
              HowToAcknowledge: string
              BIDSVersion: string
              Funding: list<item: string>
                child 0, item: string
              to
              {'Name': Value('string'), 'BIDSVersion': Value('string'), 'DatasetType': Value('string'), 'License': Value('string'), 'Authors': List(Value('string')), 'Acknowledgements': Value('string'), 'HowToAcknowledge': Value('string'), 'Funding': List(Value('string')), 'ReferencesAndLinks': List(Value('null')), 'DatasetDOI': Value('string')}
              because column names don't match

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Human Dignity MRI Dataset (BIDS)

Dataset Card for Hugging Face

📋 Dataset Description

This BIDS-compliant dataset contains structural and task-based functional MRI data from a study investigating neural responses to dignity-related and non-dignity-related stimuli.

Participants viewed visual stimuli associated with dignity-related and non-dignity-related contexts while undergoing fMRI. The paradigm explores cognitive and neural mechanisms underlying the perception of human dignity, moral evaluation, intention understanding, and related social-affective processes.

Each participant completed one high-resolution T1-weighted anatomical scan and one task-fMRI run (task-dignity).

Key Features

Subjects: 40 healthy adult participants
Modalities:
- T1-weighted structural MRI (sMRI)
- Task-based fMRI (dignity paradigm)
Total size: 2.7 GB
Format: Fully BIDS-compliant (with JSON sidecars and participants.tsv)

📊 Dataset Statistics

Dataset	Subjects (#)	# of Scans (sMRI, fMRI)	Size (GB)	sMRI Min Size (MB)	sMRI Max Size (MB)	fMRI Min Size (MB)	fMRI Max Size (MB)
Human Dignity Dataset	40	80 (40, 40)	2.7	12	13	53	62

📁 File Structure

human-dignity-fmri/
├── README.md
├── dataset_description.json
├── participants.tsv
├── CHANGES
├── sub-01/
│   └── ses-01/
│       ├── anat/
│       │   ├── sub-01_ses-01_T1w.json
│       │   └── sub-01_ses-01_T1w.nii.gz
│       └── func/
│           ├── sub-01_ses-01_task-dignity_run-01_bold.json
│           └── sub-01_ses-01_task-dignity_run-01_bold.nii.gz
├── sub-02/
├── ...
└── sub-40/   # (40 subjects total)

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Total file size:

2.89 GB