DS004580#

Simon-conflict Task.

Access recordings and metadata through EEGDash.

Citation: Arun Singh arun.singh@usd.edu, Rachel Cole rachel-cole@uiowa.edu, Arturo Espinoza arturo-espinoza@uiowa.edu, Jan R Wessel jan-wessel@uiowa.edu, Jim Cavanagh jcavanagh@unm.edu, Nandakumar Narayanan nandakumar-narayanan@uiowa.edu (2023). Simon-conflict Task.. 10.18112/openneuro.ds004580.v1.0.0

Modality: eeg Subjects: 147 Recordings: 1182 License: CC0 Source: openneuro Citations: 1.0

Metadata: Complete (100%)

Quickstart#

Get Started

Install

pip install eegdash

Access the data

from eegdash.dataset import DS004580

dataset = DS004580(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 = DS004580(cache_dir="./data", subject="01")

Advanced query

dataset = DS004580(
    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{ds004580,
  title = {Simon-conflict Task.},
  author = {Arun Singh arun.singh@usd.edu and Rachel Cole rachel-cole@uiowa.edu and Arturo Espinoza arturo-espinoza@uiowa.edu and Jan R Wessel jan-wessel@uiowa.edu and Jim Cavanagh jcavanagh@unm.edu and Nandakumar Narayanan nandakumar-narayanan@uiowa.edu},
  doi = {10.18112/openneuro.ds004580.v1.0.0},
  url = {https://doi.org/10.18112/openneuro.ds004580.v1.0.0},
}

About This Dataset#

This experiment includes 146 subjects: 98 individuals with Parkinsons disease, and 48 controls. Subjects completed this Simon task (along with multiple other cognitive tasks) while EEG was recorded with a 64-channel BrainVision cap. This task included a stimulus presented to the left or right side of the screen. The researchers instructed participants to press a left key when the was yellow or red and a right key when it was cyan or blue. The stimulus was either spatially congruent with the screen side matching the response hand or incongruent with the screen side contralateral to the response hand. The researchers analyzed data from congruent and incongruent trials separately.

Dataset Information#

Dataset ID	`DS004580`
Title	Simon-conflict Task.
Year	2023
Authors	Arun Singh arun.singh@usd.edu, Rachel Cole rachel-cole@uiowa.edu, Arturo Espinoza arturo-espinoza@uiowa.edu, Jan R Wessel jan-wessel@uiowa.edu, Jim Cavanagh jcavanagh@unm.edu, Nandakumar Narayanan nandakumar-narayanan@uiowa.edu
License	CC0
Citation / DOI	doi:10.18112/openneuro.ds004580.v1.0.0
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: 147
Recordings: 1182
Tasks: 1

Channels & sampling rate

Channels: 63 (236), 64 (56), 66 (2)
Sampling rate (Hz): 500.0
Duration (hours): 0.0

API Reference#

Use the DS004580 class to access this dataset programmatically.

class eegdash.dataset.DS004580(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

OpenNeuro dataset ds004580. Modality: eeg; Experiment type: Decision-making; Subject type: Parkinson's. Subjects: 147; recordings: 147; 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/ds004580 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds004580

Examples

>>> from eegdash.dataset import DS004580
>>> dataset = DS004580(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