DS003517#

EEG: Continuous gameplay of an 8-bit style video game

Access recordings and metadata through EEGDash.

Citation: James F Cavanagh, Joel Castellanos (2021). EEG: Continuous gameplay of an 8-bit style video game. 10.18112/openneuro.ds003517.v1.1.0

Modality: eeg Subjects: 17 Recordings: 389 License: CC0 Source: openneuro Citations: 5.0

Metadata: Complete (100%)

Quickstart#

Get Started

Install

pip install eegdash

Access the data

from eegdash.dataset import DS003517

dataset = DS003517(cache_dir="./data")
# Get the raw object of the first recording
raw = dataset.datasets[0].raw
print(raw.info)

Query & Filter

Filter by subject

dataset = DS003517(cache_dir="./data", subject="01")

Advanced query

dataset = DS003517(
    cache_dir="./data",
    query={"subject": {"$in": ["01", "02"]}},
)

Iterate recordings

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

Cite This Dataset

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

BibTeX

@dataset{ds003517,
  title = {EEG: Continuous gameplay of an 8-bit style video game},
  author = {James F Cavanagh and Joel Castellanos},
  doi = {10.18112/openneuro.ds003517.v1.1.0},
  url = {https://doi.org/10.18112/openneuro.ds003517.v1.1.0},
}

About This Dataset#

EEG during during continuous gameplay of an 8-bit style video game. EEG published here: 10.1016/j.neuroimage.2016.02.075. N=17 participants. in addition to the video game, participants first completed a 2-stim visual oddball and a 2-doors gambling task. Tasks included in Java programming language. Its pretty fun… Each task sends triggers to the EEG file, and also outputs continuous data in a .csv log file. For the Escape from Asteroid Axon video game this has a wealth of movement, player position and action, antagonist position, loot box, etc info. Data collected circa 2015 in Cognitive Rhythms and Computation Lab at University of New Mexico. Some analytic scripts are inlcuded, but I cant verify that these were what I used in the final analysis. Some (ExAAx_Log.m) are clearly pilot analyses. Your best bet would be to play the game and record some triggers and examine how those line up with the .csv log, etc. - James F Cavanagh 02/10/2021

Dataset Information#

Dataset ID	`DS003517`
Title	EEG: Continuous gameplay of an 8-bit style video game
Year	2021
Authors	James F Cavanagh, Joel Castellanos
License	CC0
Citation / DOI	10.18112/openneuro.ds003517.v1.1.0
Source links	OpenNeuro \| NeMAR \| Source URL

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: 17
Recordings: 389
Tasks: 1

Channels & sampling rate

Channels: 64 (34), 65 (34)
Sampling rate (Hz): 500.0
Duration (hours): 0.0

API Reference#

Use the DS003517 class to access this dataset programmatically.

class eegdash.dataset.DS003517(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

OpenNeuro dataset ds003517. Modality: eeg; Experiment type: Learning; Subject type: Healthy. Subjects: 17; recordings: 34; 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/ds003517 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds003517

Examples

>>> from eegdash.dataset import DS003517
>>> dataset = DS003517(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