DS006386: eeg dataset, 30 subjects#

PhysioMotion_Artifact

Access recordings and metadata through EEGDash.

Citation: Jiangwei Yu, Aonan He (2025). PhysioMotion_Artifact. 10.18112/openneuro.ds006386.v1.0.1

Modality: eeg Subjects: 30 Recordings: 180 License: CC0 Source: openneuro

Metadata: Complete (100%)

Quickstart#

Install

pip install eegdash

Access the data

from eegdash.dataset import DS006386

dataset = DS006386(cache_dir="./data")
# Get the raw object of the first recording
raw = dataset.datasets[0].raw
print(raw.info)

Filter by subject

dataset = DS006386(cache_dir="./data", subject="01")

Advanced query

dataset = DS006386(
    cache_dir="./data",
    query={"subject": {"$in": ["01", "02"]}},
)

Iterate recordings

for rec in dataset:
    print(rec.subject, rec.raw.info['sfreq'])

If you use this dataset in your research, please cite the original authors.

BibTeX

@dataset{ds006386,
  title = {PhysioMotion_Artifact},
  author = {Jiangwei Yu and Aonan He},
  doi = {10.18112/openneuro.ds006386.v1.0.1},
  url = {https://doi.org/10.18112/openneuro.ds006386.v1.0.1},
}

About This Dataset#

References

Appelhoff, S., Sanderson, M., Brooks, T., Vliet, M., Quentin, R., Holdgraf, C., Chaumon, M., Mikulan, E., Tavabi, K., Höchenberger, R., Welke, D., Brunner, C., Rockhill, A., Larson, E., Gramfort, A. and Jas, M. (2019). MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis. Journal of Open Source Software 4: (1896). https://doi.org/10.21105/joss.01896 Pernet, C. R., Appelhoff, S., Gorgolewski, K. J., Flandin, G., Phillips, C., Delorme, A., Oostenveld, R. (2019). EEG-BIDS, an extension to the brain imaging data structure for electroencephalography. Scientific Data, 6, 103. https://doi.org/10.1038/s41597-019-0104-8

Dataset Information#

Dataset ID

DS006386

Title

PhysioMotion_Artifact

Author (year)

Yu2025

Canonical

Yu2019

Importable as

DS006386, Yu2025, Yu2019

Year

2025

Authors

Jiangwei Yu, Aonan He

License

CC0

Citation / DOI

doi:10.18112/openneuro.ds006386.v1.0.1

Source links

OpenNeuro | NeMAR | Source URL
Copy-paste BibTeX
@dataset{ds006386,
  title = {PhysioMotion_Artifact},
  author = {Jiangwei Yu and Aonan He},
  doi = {10.18112/openneuro.ds006386.v1.0.1},
  url = {https://doi.org/10.18112/openneuro.ds006386.v1.0.1},
}

Found an issue with this dataset?

If you encounter any problems with this dataset (missing files, incorrect metadata, loading errors, etc.), please let us know!

Report an Issue on GitHub

Technical Details#

Subjects & recordings

  • Subjects: 30

  • Recordings: 180

  • Tasks: 1

Channels & sampling rate

  • Channels: 59

  • Sampling rate (Hz): 1000.0

  • Duration (hours): 57.99939444444445

Tags

  • Pathology: Healthy

  • Modality: Motor

  • Type: Other

Files & format

  • Size on disk: 23.0 GB

  • File count: 180

  • Format: BIDS

License & citation

  • License: CC0

  • DOI: doi:10.18112/openneuro.ds006386.v1.0.1

Provenance

API Reference#

Use the DS006386 class to access this dataset programmatically.

class eegdash.dataset.DS006386(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

PhysioMotion_Artifact

Study:

ds006386 (OpenNeuro)

Author (year):

Yu2025

Canonical:

Yu2019

Also importable as: DS006386, Yu2025, Yu2019.

Modality: eeg; Experiment type: Other; Subject type: Healthy. Subjects: 30; recordings: 180; tasks: 1.

Parameters:

  • cache_dir (str | Path) – Directory where data are cached locally.

  • query (dict | None) – Additional MongoDB-style filters to AND with the dataset selection. Must not contain the key dataset.

  • s3_bucket (str | None) – Base S3 bucket used to locate the data.

  • **kwargs (dict) – Additional keyword arguments forwarded to EEGDashDataset.

data_dir#

Local dataset cache directory (cache_dir / dataset_id).

Type:

Path

query#

Merged query with the dataset filter applied.

Type:

dict

records#

Metadata records used to build the dataset, if pre-fetched.

Type:

list[dict] | None

Notes

Each item is a recording; recording-level metadata are available via dataset.description. query supports MongoDB-style filters on fields in ALLOWED_QUERY_FIELDS and is combined with the dataset filter. Dataset-specific caveats are not provided in the summary metadata.

References

OpenNeuro dataset: https://openneuro.org/datasets/ds006386 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds006386 DOI: https://doi.org/10.18112/openneuro.ds006386.v1.0.1

Examples

>>> from eegdash.dataset import DS006386
>>> dataset = DS006386(cache_dir="./data")
>>> recording = dataset[0]
>>> raw = recording.load()
__init__(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#
save(path, overwrite=False)[source]#

Save the dataset to disk.

Parameters:

  • path (str or Path) – Destination file path.

  • overwrite (bool, default False) – If True, overwrite existing file.

Return type:

None

See Also#