DS004574#

Cross-modal Oddball 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). Cross-modal Oddball Task.. 10.18112/openneuro.ds004574.v1.0.0

Modality: eeg Subjects: 146 Recordings: 1174 License: CC0 Source: openneuro Citations: 1.0

Metadata: Complete (100%)

Quickstart#

Get Started

Install

pip install eegdash

Access the data

from eegdash.dataset import DS004574

dataset = DS004574(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 = DS004574(cache_dir="./data", subject="01")

Advanced query

dataset = DS004574(
    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{ds004574,
  title = {Cross-modal Oddball 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.ds004574.v1.0.0},
  url = {https://doi.org/10.18112/openneuro.ds004574.v1.0.0},
}

About This Dataset#

This experiment includes 146 subjects: 98 individuals with Parkinsons disease, and 48 controls. The data were collected from 2017-2021. Subjects completed this oddball task (along with multiple other cognitive tasks) while EEG was recorded with a 64-channel BrainVision cap. This task includes a primary GO cue, (white arrow) that required a directional response. That response could be correct or incorrect. The primary cue

was preceeded by a visual pre-cue and an auditory pre-cue, which occurred at the same time (500ms before arrow cue). Each trial had either standard for both pre-cues, oddball visual pre-cue, or oddball auditory pre-cue. Our analysis focused only on trials with both pre-cues standard or oddball auditory pre-cue.

Dataset Information#

Dataset ID	`DS004574`
Title	Cross-modal Oddball 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.ds004574.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: 146
Recordings: 1174
Tasks: 1

Channels & sampling rate

Channels: 63 (232), 64 (58), 66 (2)
Sampling rate (Hz): 500.0
Duration (hours): 0.0

API Reference#

Use the DS004574 class to access this dataset programmatically.

class eegdash.dataset.DS004574(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

OpenNeuro dataset ds004574. Modality: eeg; Experiment type: Clinical/Intervention; Subject type: Parkinson's. Subjects: 146; recordings: 146; 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/ds004574 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds004574

Examples

>>> from eegdash.dataset import DS004574
>>> dataset = DS004574(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