NM000251: ieeg dataset, 1 subjects#

He et al. 2025 — VocalMind: A Stereotactic EEG Dataset for Vocalized, Mimed, and Imagined Speech in Tonal Language

Access recordings and metadata through EEGDash.

Citation: Tianyu He, Mingyi Wei, Ruicong Wang, Renzhi Wang, Shiwei Du, Siqi Cai, Wei Tao, Haizhou Li (2019). He et al. 2025 — VocalMind: A Stereotactic EEG Dataset for Vocalized, Mimed, and Imagined Speech in Tonal Language. 10.1038/s41597-025-04741-2

Modality: ieeg Subjects: 1 Recordings: 6 License: CC BY 4.0 Source: nemar

Metadata: Complete (100%)

Quickstart#

Install

pip install eegdash

Access the data

from eegdash.dataset import NM000251

dataset = NM000251(cache_dir="./data")
# Get the raw object of the first recording
raw = dataset.datasets[0].raw
print(raw.info)

Filter by subject

dataset = NM000251(cache_dir="./data", subject="01")

Advanced query

dataset = NM000251(
    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{nm000251,
  title = {He et al. 2025 — VocalMind: A Stereotactic EEG Dataset for Vocalized, Mimed, and Imagined Speech in Tonal Language},
  author = {Tianyu He and Mingyi Wei and Ruicong Wang and Renzhi Wang and Shiwei Du and Siqi Cai and Wei Tao and Haizhou Li},
  doi = {10.1038/s41597-025-04741-2},
  url = {https://doi.org/10.1038/s41597-025-04741-2},
}

About This Dataset#

References

Appelhoff, S., Sanderson, M., Brooks, T., Vliet, M., Quentin, R., Holdgraf, C., Chaumon, M., Mikulan, E., Tavabi, K., Höchenberger, R., Welke, D., Brunner, C., Rockhill, A., Larson, E., Gramfort, A. and Jas, M. (2019). MNE-BIDS: Organizing electrophysiological data into the BIDS format and facilitating their analysis. Journal of Open Source Software 4: (1896).https://doi.org/10.21105/joss.01896 Holdgraf, C., Appelhoff, S., Bickel, S., Bouchard, K., D’Ambrosio, S., David, O., … Hermes, D. (2019). iEEG-BIDS, extending the Brain Imaging Data Structure specification to human intracranial electrophysiology. Scientific Data, 6, 102. https://doi.org/10.1038/s41597-019-0105-7

Dataset Information#

Dataset ID

NM000251

Title

He et al. 2025 — VocalMind: A Stereotactic EEG Dataset for Vocalized, Mimed, and Imagined Speech in Tonal Language

Author (year)

He2025

Canonical

—

Importable as

NM000251, He2025

Year

2019

Authors

Tianyu He, Mingyi Wei, Ruicong Wang, Renzhi Wang, Shiwei Du, Siqi Cai, Wei Tao, Haizhou Li

License

CC BY 4.0

Citation / DOI

doi:10.1038/s41597-025-04741-2

Source links

OpenNeuro | NeMAR | Source URL
Copy-paste BibTeX
@dataset{nm000251,
  title = {He et al. 2025 — VocalMind: A Stereotactic EEG Dataset for Vocalized, Mimed, and Imagined Speech in Tonal Language},
  author = {Tianyu He and Mingyi Wei and Ruicong Wang and Renzhi Wang and Shiwei Du and Siqi Cai and Wei Tao and Haizhou Li},
  doi = {10.1038/s41597-025-04741-2},
  url = {https://doi.org/10.1038/s41597-025-04741-2},
}

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: 1

  • Recordings: 6

  • Tasks: 3

Channels & sampling rate

  • Channels: 110

  • Sampling rate (Hz): 1000

  • Duration (hours): 1.130831666666667

Tags

  • Pathology: Not specified

  • Modality: —

  • Type: —

Files & format

  • Size on disk: 1.9 GB

  • File count: 6

  • Format: BIDS

License & citation

  • License: CC BY 4.0

  • DOI: doi:10.1038/s41597-025-04741-2

Provenance

API Reference#

Use the NM000251 class to access this dataset programmatically.

class eegdash.dataset.NM000251(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

He et al. 2025 — VocalMind: A Stereotactic EEG Dataset for Vocalized, Mimed, and Imagined Speech in Tonal Language

Study:

nm000251 (NeMAR)

Author (year):

He2025

Canonical:

—

Also importable as: NM000251, He2025.

Modality: ieeg. Subjects: 1; recordings: 6; tasks: 3.

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/nm000251 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=nm000251 DOI: https://doi.org/10.1038/s41597-025-04741-2

Examples

>>> from eegdash.dataset import NM000251
>>> dataset = NM000251(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#