DS006222: eeg dataset, 69 subjects#

MultisensoryFlickerHealthyYoungAdults_AllSubjectsRawData

Access recordings and metadata through EEGDash.

Citation: Matthew Attokaren, Annabelle Singer (2025). MultisensoryFlickerHealthyYoungAdults_AllSubjectsRawData. 10.18112/openneuro.ds006222.v1.0.1

Modality: eeg Subjects: 69 Recordings: 70 License: CC0 Source: openneuro

Metadata: Complete (100%)

Quickstart#

Install

pip install eegdash

Access the data

from eegdash.dataset import DS006222

dataset = DS006222(cache_dir="./data")
# Get the raw object of the first recording
raw = dataset.datasets[0].raw
print(raw.info)

Filter by subject

dataset = DS006222(cache_dir="./data", subject="01")

Advanced query

dataset = DS006222(
    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{ds006222,
  title = {MultisensoryFlickerHealthyYoungAdults_AllSubjectsRawData},
  author = {Matthew Attokaren and Annabelle Singer},
  doi = {10.18112/openneuro.ds006222.v1.0.1},
  url = {https://doi.org/10.18112/openneuro.ds006222.v1.0.1},
}

About This Dataset#

We recorded scalp EEG activity of healthy adults during one hour of either 40 Hz audiovisual flicker, no flicker as control, or randomized flicker as sham stimulation, while subjects performed a psychomotor vigilance task.

Dataset Information#

Dataset ID

DS006222

Title

MultisensoryFlickerHealthyYoungAdults_AllSubjectsRawData

Author (year)

Attokaren2025

Canonical

—

Importable as

DS006222, Attokaren2025

Year

2025

Authors

Matthew Attokaren, Annabelle Singer

License

CC0

Citation / DOI

doi:10.18112/openneuro.ds006222.v1.0.1

Source links

OpenNeuro | NeMAR | Source URL
Copy-paste BibTeX
@dataset{ds006222,
  title = {MultisensoryFlickerHealthyYoungAdults_AllSubjectsRawData},
  author = {Matthew Attokaren and Annabelle Singer},
  doi = {10.18112/openneuro.ds006222.v1.0.1},
  url = {https://doi.org/10.18112/openneuro.ds006222.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: 69

  • Recordings: 70

  • Tasks: 1

Channels & sampling rate

  • Channels: 40

  • Sampling rate (Hz): 512.0

  • Duration (hours): 52.80083333333334

Tags

  • Pathology: Healthy

  • Modality: Multisensory

  • Type: Attention

Files & format

  • Size on disk: 14.7 GB

  • File count: 70

  • Format: BIDS

License & citation

  • License: CC0

  • DOI: doi:10.18112/openneuro.ds006222.v1.0.1

Provenance

API Reference#

Use the DS006222 class to access this dataset programmatically.

class eegdash.dataset.DS006222(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

MultisensoryFlickerHealthyYoungAdults_AllSubjectsRawData

Study:

ds006222 (OpenNeuro)

Author (year):

Attokaren2025

Canonical:

—

Also importable as: DS006222, Attokaren2025.

Modality: eeg; Experiment type: Attention; Subject type: Healthy. Subjects: 69; recordings: 70; 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/ds006222 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds006222 DOI: https://doi.org/10.18112/openneuro.ds006222.v1.0.1

Examples

>>> from eegdash.dataset import DS006222
>>> dataset = DS006222(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#