DS005520#

Research data supporting ‘EEG recording during playing MOBA game’

Access recordings and metadata through EEGDash.

Citation: Hong-Zhi Li, Jia-Jia Yang, Zhen Lv, Li-Yang Wan, Wo Wang, Da-Qi Li, Dong-Dong Zhou, Li Kuang (2024). Research data supporting ‘EEG recording during playing MOBA game’. 10.18112/openneuro.ds005520.v1.0.1

Modality: eeg Subjects: 23 Recordings: 396 License: CC0 Source: openneuro Citations: 0.0

Metadata: Complete (100%)

Quickstart#

Install

pip install eegdash

Access the data

from eegdash.dataset import DS005520

dataset = DS005520(cache_dir="./data")
# Get the raw object of the first recording
raw = dataset.datasets[0].raw
print(raw.info)

Filter by subject

dataset = DS005520(cache_dir="./data", subject="01")

Advanced query

dataset = DS005520(
    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{ds005520,
  title = {Research data supporting 'EEG recording during playing MOBA game'},
  author = {Hong-Zhi Li and Jia-Jia Yang and Zhen Lv and Li-Yang Wan and Wo Wang and Da-Qi Li and Dong-Dong Zhou and Li Kuang},
  doi = {10.18112/openneuro.ds005520.v1.0.1},
  url = {https://doi.org/10.18112/openneuro.ds005520.v1.0.1},
}

About This Dataset#

General information

This dataset contains resting(eyes closed, eyes open) and EEG recordings during playing real MOBA game with 23 participants.

Dataset

View full README

General information

This dataset contains resting(eyes closed, eyes open) and EEG recordings during playing real MOBA game with 23 participants.

Dataset

Presentation

The data collection was initiated in April 2023 and was terminated in July 2023. The detailed description of the dataset is currently under working by Hong-Zhi Li and Dong-Dong Zhou, and will submit to Scientific Data for publication.

EEG acquisition

  • EEG system (Neuroscan, 64 electrodes)

  • Sampling frequency: 1000Hz

event type

  • 13 indicates a kill during playing game

  • 14 indicates a death during playing game

  • 66 indicates game start

  • 444 indicates game failure

  • 666 indicates game victory

Contact

Dataset Information#

Dataset ID

DS005520

Title

Research data supporting ‘EEG recording during playing MOBA game’

Year

2024

Authors

Hong-Zhi Li, Jia-Jia Yang, Zhen Lv, Li-Yang Wan, Wo Wang, Da-Qi Li, Dong-Dong Zhou, Li Kuang

License

CC0

Citation / DOI

doi:10.18112/openneuro.ds005520.v1.0.1

Source links

OpenNeuro | NeMAR | Source URL
Copy-paste BibTeX
@dataset{ds005520,
  title = {Research data supporting 'EEG recording during playing MOBA game'},
  author = {Hong-Zhi Li and Jia-Jia Yang and Zhen Lv and Li-Yang Wan and Wo Wang and Da-Qi Li and Dong-Dong Zhou and Li Kuang},
  doi = {10.18112/openneuro.ds005520.v1.0.1},
  url = {https://doi.org/10.18112/openneuro.ds005520.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: 23

  • Recordings: 396

  • Tasks: 3

Channels & sampling rate

  • Channels: 67

  • Sampling rate (Hz): 1000.0

  • Duration (hours): 0.0

Tags

  • Pathology: Healthy

  • Modality: Visual

  • Type: Other

Files & format

  • Size on disk: 43.9 GB

  • File count: 396

  • Format: BIDS

License & citation

  • License: CC0

  • DOI: doi:10.18112/openneuro.ds005520.v1.0.1

Provenance

API Reference#

Use the DS005520 class to access this dataset programmatically.

class eegdash.dataset.DS005520(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

OpenNeuro dataset ds005520. Modality: eeg; Experiment type: Other; Subject type: Healthy. Subjects: 23; recordings: 69; tasks: 3.

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/ds005520 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds005520

Examples

>>> from eegdash.dataset import DS005520
>>> dataset = DS005520(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#