DS004520#

Changes in behavioral priority influence the accessibility of working memory content - Experiment 2

Access recordings and metadata through EEGDash.

Citation: Edward Ester, Paige Pytel (2023). Changes in behavioral priority influence the accessibility of working memory content - Experiment 2. 10.18112/openneuro.ds004520.v1.0.1

Modality: eeg Subjects: 33 Recordings: 235 License: CC0 Source: openneuro Citations: 3.0

Metadata: Complete (100%)

Quickstart#

Install

pip install eegdash

Access the data

from eegdash.dataset import DS004520

dataset = DS004520(cache_dir="./data")
# Get the raw object of the first recording
raw = dataset.datasets[0].raw
print(raw.info)

Filter by subject

dataset = DS004520(cache_dir="./data", subject="01")

Advanced query

dataset = DS004520(
    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{ds004520,
  title = {Changes in behavioral priority influence the accessibility of working memory content - Experiment 2},
  author = {Edward Ester and Paige Pytel},
  doi = {10.18112/openneuro.ds004520.v1.0.1},
  url = {https://doi.org/10.18112/openneuro.ds004520.v1.0.1},
}

About This Dataset#

Preprocessed data from Experiment 2 of Ester & Pytel “Changes in behavioral priority influence the accessibility of working memory content”. Analytic scripts for this project can be found on OSF: https://osf.io/gtd5f/. Note that to analyze the BIDS data, you’ll need to modify the analysis scripts to read in the BIDS .set files rather than the expected .mat files. See the OSF wiki for more information

Dataset Information#

Dataset ID

DS004520

Title

Changes in behavioral priority influence the accessibility of working memory content - Experiment 2

Year

2023

Authors

Edward Ester, Paige Pytel

License

CC0

Citation / DOI

doi:10.18112/openneuro.ds004520.v1.0.1

Source links

OpenNeuro | NeMAR | Source URL
Copy-paste BibTeX
@dataset{ds004520,
  title = {Changes in behavioral priority influence the accessibility of working memory content - Experiment 2},
  author = {Edward Ester and Paige Pytel},
  doi = {10.18112/openneuro.ds004520.v1.0.1},
  url = {https://doi.org/10.18112/openneuro.ds004520.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: 33

  • Recordings: 235

  • Tasks: 1

Channels & sampling rate

  • Channels: 62

  • Sampling rate (Hz): 250.0

  • Duration (hours): 0.0

Tags

  • Pathology: Not specified

  • Modality: —

  • Type: —

Files & format

  • Size on disk: 10.4 GB

  • File count: 235

  • Format: BIDS

License & citation

  • License: CC0

  • DOI: doi:10.18112/openneuro.ds004520.v1.0.1

Provenance

API Reference#

Use the DS004520 class to access this dataset programmatically.

class eegdash.dataset.DS004520(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

OpenNeuro dataset ds004520. Modality: eeg; Experiment type: Memory. Subjects: 33; recordings: 33; 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/ds004520 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds004520

Examples

>>> from eegdash.dataset import DS004520
>>> dataset = DS004520(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#