eegdash.dataset.DS006036#

task-photomark_events.json (OpenNeuro ds006036). Access recordings and metadata through EEGDash.

Modality: [‘eeg’] Tasks: 0 License: CC0 Subjects: 0 Recordings: 0 Source: openneuro

Dataset Information#

Dataset ID

DS006036

Title

task-photomark_events.json

Year

2025

Authors

Aimilia Ntetska, Andreas Miltiadous, Alexandros T. Tzallas, Katerina D. Tzimourta, Theodora Afrantou, Panagiotis Ioannidis, Dimitrios G. Tsalikakis, Nikolaos Grigoriadis, Pantelis Angelidis, Konstantinos Sakkas, Emmanouil D. Oikonomou, Nikolaos Giannakeas, Markos G. Tsipouras

License

CC0

Citation / DOI

doi:10.18112/openneuro.ds006036.v1.0.5

Source links

OpenNeuro | NeMAR | Source URL
Copy-paste BibTeX
@dataset{ds006036,
  title = {task-photomark_events.json},
  author = {Aimilia Ntetska and Andreas Miltiadous and Alexandros T. Tzallas and Katerina D. Tzimourta and Theodora Afrantou and Panagiotis Ioannidis and Dimitrios G. Tsalikakis and Nikolaos Grigoriadis and Pantelis Angelidis and Konstantinos Sakkas and Emmanouil D. Oikonomou and Nikolaos Giannakeas and Markos G. Tsipouras},
  doi = {10.18112/openneuro.ds006036.v1.0.5},
  url = {https://doi.org/10.18112/openneuro.ds006036.v1.0.5},
}

Highlights#

Subjects & recordings

  • Subjects: 0

  • Recordings: 0

  • Tasks: 0

Channels & sampling rate

  • Channels: 19

  • Sampling rate (Hz): 500.0

  • Duration (hours): 0

Tasks & conditions

  • Tasks: 0

  • Experiment type: Unknown

  • Subject type: Unknown

Files & format

  • Size on disk: Unknown

  • File count: Unknown

  • Format: Unknown

License & citation

  • License: CC0

  • DOI: doi:10.18112/openneuro.ds006036.v1.0.5

Provenance

Quickstart#

Install

pip install eegdash

Load a recording

from eegdash.dataset import DS006036

dataset = DS006036(cache_dir="./data")
recording = dataset[0]
raw = recording.load()

Filter/query

dataset = DS006036(cache_dir="./data", subject="01")

dataset = DS006036(
    cache_dir="./data",
    query={"subject": {"$in": ["01", "02"]}},
)

Quality & caveats#

  • No dataset-specific caveats are listed in the available metadata.

API#

class eegdash.dataset.DS006036(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

OpenNeuro dataset ds006036. Modality: eeg; Experiment type: Unknown; Subject type: Unknown. Subjects: 88; recordings: 88; 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/ds006036 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds006036 DOI: https://doi.org/10.18112/openneuro.ds006036.v1.0.5

Examples

>>> from eegdash.dataset import DS006036
>>> dataset = DS006036(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#