DS007338: eeg dataset, 1 subjects#

EEGEyeNet Dataset

Access recordings and metadata through EEGDash.

Citation: Martyna Beata Płomecka, Ard Kastrati, Nicolas Langer (2026). EEGEyeNet Dataset. 10.18112/openneuro.ds007338.v1.0.0

Modality: eeg Subjects: 1 Recordings: 1 License: CC0 Source: openneuro

Metadata: Complete (100%)

Quickstart#

Install

pip install eegdash

Access the data

from eegdash.dataset import DS007338

dataset = DS007338(cache_dir="./data")
# Get the raw object of the first recording
raw = dataset.datasets[0].raw
print(raw.info)

Filter by subject

dataset = DS007338(cache_dir="./data", subject="01")

Advanced query

dataset = DS007338(
    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{ds007338,
  title = {EEGEyeNet Dataset},
  author = {Martyna Beata Płomecka and Ard Kastrati and Nicolas Langer},
  doi = {10.18112/openneuro.ds007338.v1.0.0},
  url = {https://doi.org/10.18112/openneuro.ds007338.v1.0.0},
}

About This Dataset#

This is a BIDS standardized version of simultaneously collected EEG and eye-tracking data, taken from one subject from the EEGEYENET dataset. Acknowledgements go to Martyna Beata Płomecka, Ard Kastrati, and Nicolas Langer who designed the study, collected the data, and published the dataset to Open Science Framework. For access to the full dataset, please refer to the dataset DOI.

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

DS007338

Title

EEGEyeNet Dataset

Author (year)

Plomecka2026

Canonical

EEGEyeNet_v2, EEGEYENET

Importable as

DS007338, Plomecka2026, EEGEyeNet_v2, EEGEYENET

Year

2026

Authors

Martyna Beata Płomecka, Ard Kastrati, Nicolas Langer

License

CC0

Citation / DOI

doi:10.18112/openneuro.ds007338.v1.0.0

Source links

OpenNeuro | NeMAR | Source URL
Copy-paste BibTeX
@dataset{ds007338,
  title = {EEGEyeNet Dataset},
  author = {Martyna Beata Płomecka and Ard Kastrati and Nicolas Langer},
  doi = {10.18112/openneuro.ds007338.v1.0.0},
  url = {https://doi.org/10.18112/openneuro.ds007338.v1.0.0},
}

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: 1

  • Recordings: 1

  • Tasks: 1

Channels & sampling rate

  • Channels: 129

  • Sampling rate (Hz): 500.0

  • Duration (hours): 0.0898511111111111

Tags

  • Pathology: Healthy

  • Modality: Visual

  • Type: Perception

Files & format

  • Size on disk: 39.9 MB

  • File count: 1

  • Format: BIDS

License & citation

  • License: CC0

  • DOI: doi:10.18112/openneuro.ds007338.v1.0.0

Provenance

API Reference#

Use the DS007338 class to access this dataset programmatically.

class eegdash.dataset.DS007338(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

EEGEyeNet Dataset

Study:

ds007338 (OpenNeuro)

Author (year):

Plomecka2026

Canonical:

EEGEyeNet_v2, EEGEYENET

Also importable as: DS007338, Plomecka2026, EEGEyeNet_v2, EEGEYENET.

Modality: eeg; Experiment type: Perception; Subject type: Healthy. Subjects: 1; recordings: 1; 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/ds007338 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds007338 DOI: https://doi.org/10.18112/openneuro.ds007338.v1.0.0

Examples

>>> from eegdash.dataset import DS007338
>>> dataset = DS007338(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#