DS003825#

Human electroencephalography recordings from 50 subjects for 22,248 images from 1,854 object concepts

Access recordings and metadata through EEGDash.

Citation: Grootswagers, Tijl, Zhou, Ivy, Robinson, Amanda, Hebart, Martin, Carlson, Thomas (2021). Human electroencephalography recordings from 50 subjects for 22,248 images from 1,854 object concepts. 10.18112/openneuro.ds003825.v1.2.0

Modality: eeg Subjects: 50 Recordings: 257 License: CC0 Source: openneuro Citations: 2.0

Metadata: Complete (100%)

Quickstart#

Get Started

Install

pip install eegdash

Access the data

from eegdash.dataset import DS003825

dataset = DS003825(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 = DS003825(cache_dir="./data", subject="01")

Advanced query

dataset = DS003825(
    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{ds003825,
  title = {Human electroencephalography recordings from 50 subjects for 22,248 images from 1,854 object concepts},
  author = {Grootswagers, Tijl and Zhou, Ivy and Robinson, Amanda and Hebart, Martin and Carlson, Thomas},
  doi = {10.18112/openneuro.ds003825.v1.2.0},
  url = {https://doi.org/10.18112/openneuro.ds003825.v1.2.0},
}

About This Dataset#

Experiment Details Human electroencephalography recordings from 50 subjects for 1,854 concepts and 22,248 images in the THINGS stimulus database. Images were presented in rapid serial visual presentation streams at 10Hz rates. Participants performed an orthogonal fixation colour change detection task.

Experiment length: 1 hour

More information:

https://osf.io/hd6zk/ (osf repository with more information and example analysis code)

Grootswagers, T., Zhou, I., Robinson, A.K. et al. Human EEG recordings for 1,854 concepts presented in rapid serial visual presentation streams. Sci Data 9, 3 (2022). https://doi.org/10.1038/s41597-021-01102-7

Dataset Information#

Dataset ID	`DS003825`
Title	Human electroencephalography recordings from 50 subjects for 22,248 images from 1,854 object concepts
Year	2021
Authors	Grootswagers, Tijl, Zhou, Ivy, Robinson, Amanda, Hebart, Martin, Carlson, Thomas
License	CC0
Citation / DOI	doi:10.18112/openneuro.ds003825.v1.2.0
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: 50
Recordings: 257
Tasks: 1

Channels & sampling rate

Channels: 63 (96), 128 (4)
Sampling rate (Hz): 1000.0
Duration (hours): 0.0

API Reference#

Use the DS003825 class to access this dataset programmatically.

class eegdash.dataset.DS003825(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

OpenNeuro dataset ds003825. Modality: eeg; Experiment type: Perception; Subject type: Healthy. Subjects: 50; recordings: 50; 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/ds003825 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds003825

Examples

>>> from eegdash.dataset import DS003825
>>> dataset = DS003825(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