DS005697#

PerceiveImagine

Access recordings and metadata through EEGDash.

Citation: Weilong Li, Hua Fan (2024). PerceiveImagine. 10.18112/openneuro.ds005697.v1.0.2

Modality: eeg Subjects: 52 Recordings: 210 License: CC0 Source: openneuro Citations: 3.0

Metadata: Complete (100%)

Quickstart#

Install

pip install eegdash

Access the data

from eegdash.dataset import DS005697

dataset = DS005697(cache_dir="./data")
# Get the raw object of the first recording
raw = dataset.datasets[0].raw
print(raw.info)

Filter by subject

dataset = DS005697(cache_dir="./data", subject="01")

Advanced query

dataset = DS005697(
    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{ds005697,
  title = {PerceiveImagine},
  author = {Weilong Li and Hua Fan},
  doi = {10.18112/openneuro.ds005697.v1.0.2},
  url = {https://doi.org/10.18112/openneuro.ds005697.v1.0.2},
}

About This Dataset#

This dataset consists of electroencephalogram (EEG) signals collected by the 64 channel EEG device SynAmps2. ###Participants and Conversations This experiment included 54 participants. 2 participants gave up the experiment midway due to physical reasons, and 6 participants had poor signal collection results during the first collection and underwent a second collection. All participants met the experimental requirements ###Task This experiment requires participants to watch the image for 6 seconds according to the requirements, and then imagine the image they see for 6 seconds. The total dataset contains 340 images ###Dataset version The provided dataset consists of the original dataset ###contact If you have any questions, please contact:yingxmbio@foxmail.com

Dataset Information#

Dataset ID

DS005697

Title

PerceiveImagine

Year

2024

Authors

Weilong Li, Hua Fan

License

CC0

Citation / DOI

doi:10.18112/openneuro.ds005697.v1.0.2

Source links

OpenNeuro | NeMAR | Source URL
Copy-paste BibTeX
@dataset{ds005697,
  title = {PerceiveImagine},
  author = {Weilong Li and Hua Fan},
  doi = {10.18112/openneuro.ds005697.v1.0.2},
  url = {https://doi.org/10.18112/openneuro.ds005697.v1.0.2},
}

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: 52

  • Recordings: 210

  • Tasks: 1

Channels & sampling rate

  • Channels: 65 (46), 64 (44), 69 (6), 66 (6)

  • Sampling rate (Hz): 1000.0

  • Duration (hours): 0.0

Tags

  • Pathology: Healthy

  • Modality: Visual

  • Type: Memory

Files & format

  • Size on disk: 66.6 GB

  • File count: 210

  • Format: BIDS

License & citation

  • License: CC0

  • DOI: doi:10.18112/openneuro.ds005697.v1.0.2

Provenance

API Reference#

Use the DS005697 class to access this dataset programmatically.

class eegdash.dataset.DS005697(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

OpenNeuro dataset ds005697. Modality: eeg; Experiment type: Memory; Subject type: Healthy. Subjects: 51; recordings: 51; 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/ds005697 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds005697

Examples

>>> from eegdash.dataset import DS005697
>>> dataset = DS005697(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#