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eeg-fmri-natview-derived

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Tags:
eeg
fmri
neuroscience
multimodal
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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    ArrowInvalid
Message:      Schema at index 1 was different: 
atlas_map_sha256: string
canonical_channel_contract_sha256: string
canonical_channel_labels: list<item: string>
channel_presence_mask: list<item: int64>
eeg_shape_200hz_published: list<item: int64>
eeg_shape_250hz_ephemeral: list<item: int64>
fmri_affine: list<item: list<item: double>>
fmri_shape: list<item: int64>
key: string
run_id: string
source_channel_labels: list<item: string>
source_objects: struct<bold_no_gsr: struct<bytes: int64, downloaded_sha256: string, etag: string, key: string, last_modified: string, response_etag: string, response_version_id: string, url: string>, channels: struct<bytes: int64, downloaded_sha256: string, etag: string, key: string, last_modified: string, response_etag: string, response_version_id: string, url: string>, clean_eeg: struct<bytes: int64, downloaded_sha256: string, etag: string, key: string, last_modified: string, response_etag: string, response_version_id: string, url: string>, clean_events: struct<bytes: int64, downloaded_sha256: string, etag: string, key: string, last_modified: string, response_etag: string, response_version_id: string, url: string>, eeg_json: struct<bytes: int64, downloaded_sha256: string, etag: string, key: string, last_modified: string, response_etag: string, response_version_id: string, url: string>, motion: struct<bytes: int64, downloaded_sha256: string, etag: string, key: string, last_modified: string, response_etag: string, response_version_id: string, url: string>, raw_events: struct<bytes: int64, downloaded_sha256: string, etag: string, key: string, last_modified: string, response_etag: string, response_version_id: string, url: string>>
source_policy: string
split: string
synchronization_method: string
vs
canonical_eeg_channels: int64
certified_r128_count: int64
certified_segments: int64
clean_r128_count: int64
common_targets: int64
excluded_segments: int64
fd_gt_0_5_count: int64
fmri_volumes: int64
max_fd_mm: double
mean_fd_mm: double
missing_channels: list<item: string>
neurobolt_windows: int64
raw_r128_count: int64
source_eeg_channels: int64
spec2vol_frames: int64
spec2vol_sequences: int64
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1848, in _prepare_split_single
                  writer.write_table(table)
                  ~~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 764, in write_table
                  self.write_rows_on_file()  # in case there are buffered rows to write first
                  ~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 662, in write_rows_on_file
                  table = pa.concat_tables(self.current_rows)
                File "pyarrow/table.pxi", line 6320, in pyarrow.lib.concat_tables
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                  return check_status(status)
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
                  raise convert_status(status)
              pyarrow.lib.ArrowInvalid: Schema at index 1 was different: 
              atlas_map_sha256: string
              canonical_channel_contract_sha256: string
              canonical_channel_labels: list<item: string>
              channel_presence_mask: list<item: int64>
              eeg_shape_200hz_published: list<item: int64>
              eeg_shape_250hz_ephemeral: list<item: int64>
              fmri_affine: list<item: list<item: double>>
              fmri_shape: list<item: int64>
              key: string
              run_id: string
              source_channel_labels: list<item: string>
              source_objects: struct<bold_no_gsr: struct<bytes: int64, downloaded_sha256: string, etag: string, key: string, last_modified: string, response_etag: string, response_version_id: string, url: string>, channels: struct<bytes: int64, downloaded_sha256: string, etag: string, key: string, last_modified: string, response_etag: string, response_version_id: string, url: string>, clean_eeg: struct<bytes: int64, downloaded_sha256: string, etag: string, key: string, last_modified: string, response_etag: string, response_version_id: string, url: string>, clean_events: struct<bytes: int64, downloaded_sha256: string, etag: string, key: string, last_modified: string, response_etag: string, response_version_id: string, url: string>, eeg_json: struct<bytes: int64, downloaded_sha256: string, etag: string, key: string, last_modified: string, response_etag: string, response_version_id: string, url: string>, motion: struct<bytes: int64, downloaded_sha256: string, etag: string, key: string, last_modified: string, response_etag: string, response_version_id: string, url: string>, raw_events: struct<bytes: int64, downloaded_sha256: string, etag: string, key: string, last_modified: string, response_etag: string, response_version_id: string, url: string>>
              source_policy: string
              split: string
              synchronization_method: string
              vs
              canonical_eeg_channels: int64
              certified_r128_count: int64
              certified_segments: int64
              clean_r128_count: int64
              common_targets: int64
              excluded_segments: int64
              fd_gt_0_5_count: int64
              fmri_volumes: int64
              max_fd_mm: double
              mean_fd_mm: double
              missing_channels: list<item: string>
              neurobolt_windows: int64
              raw_r128_count: int64
              source_eeg_channels: int64
              spec2vol_frames: int64
              spec2vol_sequences: int64
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1869, in _prepare_split_single
                  num_examples, num_bytes = writer.finalize()
                                            ~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 781, in finalize
                  self.write_rows_on_file()
                  ~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 662, in write_rows_on_file
                  table = pa.concat_tables(self.current_rows)
                File "pyarrow/table.pxi", line 6320, in pyarrow.lib.concat_tables
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
                  raise convert_status(status)
              pyarrow.lib.ArrowInvalid: Schema at index 1 was different: 
              atlas_map_sha256: string
              canonical_channel_contract_sha256: string
              canonical_channel_labels: list<item: string>
              channel_presence_mask: list<item: int64>
              eeg_shape_200hz_published: list<item: int64>
              eeg_shape_250hz_ephemeral: list<item: int64>
              fmri_affine: list<item: list<item: double>>
              fmri_shape: list<item: int64>
              key: string
              run_id: string
              source_channel_labels: list<item: string>
              source_objects: struct<bold_no_gsr: struct<bytes: int64, downloaded_sha256: string, etag: string, key: string, last_modified: string, response_etag: string, response_version_id: string, url: string>, channels: struct<bytes: int64, downloaded_sha256: string, etag: string, key: string, last_modified: string, response_etag: string, response_version_id: string, url: string>, clean_eeg: struct<bytes: int64, downloaded_sha256: string, etag: string, key: string, last_modified: string, response_etag: string, response_version_id: string, url: string>, clean_events: struct<bytes: int64, downloaded_sha256: string, etag: string, key: string, last_modified: string, response_etag: string, response_version_id: string, url: string>, eeg_json: struct<bytes: int64, downloaded_sha256: string, etag: string, key: string, last_modified: string, response_etag: string, response_version_id: string, url: string>, motion: struct<bytes: int64, downloaded_sha256: string, etag: string, key: string, last_modified: string, response_etag: string, response_version_id: string, url: string>, raw_events: struct<bytes: int64, downloaded_sha256: string, etag: string, key: string, last_modified: string, response_etag: string, response_version_id: string, url: string>>
              source_policy: string
              split: string
              synchronization_method: string
              vs
              canonical_eeg_channels: int64
              certified_r128_count: int64
              certified_segments: int64
              clean_r128_count: int64
              common_targets: int64
              excluded_segments: int64
              fd_gt_0_5_count: int64
              fmri_volumes: int64
              max_fd_mm: double
              mean_fd_mm: double
              missing_channels: list<item: string>
              neurobolt_windows: int64
              raw_r128_count: int64
              source_eeg_channels: int64
              spec2vol_frames: int64
              spec2vol_sequences: int64
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1880, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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text
string
Superior frontal sulcus
Fusiform gyrus
Calcarine cortex posterior
Cingulate cortex posterior
Parieto-occipital sulcus superior
Insula antero-superior
Superior temporal sulcus with angular gyrus
Planum temporale
Cerebellum Crus II
Superior parts of Postcentral and Precentral gyri
Transverse sinus
Paracentral gyrus RH
Superior occipital gyrus
Cingulate gyrus mid-posterior
ventricles
Fusiform gyrus posterior
Superior frontal gyrus medial
Precuneus superior
Planum polare
Parieto-occipital sulcus middle
Cerebellum I-V
Superior fornix and isthmus
Anterior Cingulate Cortex
Descending occipital gyrus
Putamen
Cingulate gyrus mid-anterior
Superior parietal lobule posterior
Paracentral lobule
Inferior occipital gyrus
Superior rostral gyrus
Calcarine sulcus anterior
Intraparietal sulcus
Superior parietal lobule anterior
Precentral gyrus medial
Lingual gyrus anterior
Angular gyrus superior
Supramarginal gyrus
Intraparietal sulcus LH
Dorsomedial prefrontal cortex antero-superior
Precentral gyrus superior
Postcentral gyrus inferior
Lateral occipital cortex
Callosomarginal sulcus
Paracentral lobule superior
Heschl’s gyrus
Occipital pole
Thalamus
Intraparietal sulcus RH
Inferior frontal sulcus
Postcentral gyrus LH
Middle frontal gyrus
Inferior frontal gyrus
Parieto-occipital sulcus anterior
Precuneus anterior
Lingual gyrus
Superior occipital sulcus
Superior parietal lobule
Middle frontal gyrus anterior
Angular gyrus inferior
Cuneus
Middle temporal gyrus
Superior frontal gyrus
Central sulcus
Caudate
Fp1
Fp2
F3
F4
C3
C4
P3
P4
O1
O2
F7
F8
T7
T8
P7
P8
Fz
Cz
Pz
Oz
FC2
CP1
CP2
FC5
FC6
CP5
CP6
TP9
TP10
POz
F1
F2
C1
C2
P1
P2
End of preview.

NATVIEW EEG-fMRI derived run objects

This public dataset repository is the persistent derivative store for the M8 external Spec2VolCAMU-Net/NeuroBOLT comparison. The source data are the NKI NATVIEW simultaneous EEG-fMRI release:

The repository does not mirror raw 5 kHz EEG or raw anatomical/fMRI data. Each source run is fetched into disposable scratch space, checked against a pinned SHA-256 key, transformed, uploaded as a compact run-level derivative, and removed from scratch. Raw-release objects are locked to NEMAR v1.0.0; official preproc_data objects are additionally locked by S3 version ID, ETag, byte count, and downloaded SHA-256.

Current contents

The repository contains the M8C signal-free inventory and one M8D training-run pipeline pilot: natview_sub-20_ses-02_task-checker. The pilot uses the authors' official FASTR/BCG/ASR/ICA-cleaned 250 Hz EEG and CCS-processed, unsmoothed, temporally unfiltered MNI fMRI. It provides:

  • 250 Hz EEG and boundary-aware 200 Hz EEG;
  • 40 strict 16-second causal windows for the NeuroBOLT comparison;
  • 74 TR-aligned 2.1-second FFT frames and 17 valid 20-frame sequences for Spec2Vol;
  • DiFuMo-64 no-GSR/GSR targets and selected 3-D residual-volume targets;
  • motion, synchronization, QC, source hashes, and full member hashes.

The short checker run is a preprocessing/synchronization validation only. It is not a training cohort and contains no model prediction or performance result.

License and citation

The official INDI host and the data paper release the data and code under CC BY 4.0. Cite Telesford et al., Scientific Data 10, 554 (2023), in any use of these derivatives. Project code and third-party model code retain their own licenses and are not distributed through this dataset repository.
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