DS004703#

sEEG Passive listening to natural speech

Access recordings and metadata through EEGDash.

Citation: Anna Mai, Stephanie Ries, Sharona Ben-Haim, Jerry Shih, Timothy Gentner (2023). sEEG Passive listening to natural speech. 10.18112/openneuro.ds004703.v1.1.0

Modality: ieeg Subjects: 10 Recordings: 325 License: CC0 Source: openneuro Citations: 2.0

Metadata: Complete (100%)

Quickstart#

Get Started

Install

pip install eegdash

Access the data

from eegdash.dataset import DS004703

dataset = DS004703(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 = DS004703(cache_dir="./data", subject="01")

Advanced query

dataset = DS004703(
    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{ds004703,
  title = {sEEG Passive listening to natural speech},
  author = {Anna Mai and Stephanie Ries and Sharona Ben-Haim and Jerry Shih and Timothy Gentner},
  doi = {10.18112/openneuro.ds004703.v1.1.0},
  url = {https://doi.org/10.18112/openneuro.ds004703.v1.1.0},
}

About This Dataset#

CONTACT

For questions about this data set, please contact Anna Mai (anna.mai@mpi.nl; ORCiD 0000-0002-8343-9216).

PERMISSIONS

These data may not be used for commericial purposes, including but not limited to use in any kind of training set for commercial machine learning applications.

These data may not be used in any way that either in part or in whole disambiguates participant identity, including but not limited to attempts at 3D facial reconstruction.

RECORDING SETUP

These data were collected from June 2018 to August 2019.

For all patients, a scalp electrode was used for referencing and ground. These were 13mm, 2.5M single lead subdermal electrodes made by Rochester Electro-Medical with serial number S81025-A-24RM.

Depth electrodes were manufactured by Ad-Tech and are Spencer Probe depth electrodes. Each electrode has 10 leads evenly spaced 3-7mm apart.

With the exception of patients SD012 and SD022, all implants are depth electrodes. Patients SD012 and SD022 had grid and strip electrodes implanted in addition to several depth electrodes.

Any channel names beginning with ``C’’ were not used and should be dropped from analyses.

TASK

Participants passively listened to 30-45s passages of conversational speech and verbally answered a 2AC content question after each passage. 6 blocks with 7 passages per block.

MISSING DATA

Anatomical scans for particpant SD012 are not available due to excessive movement artifacts.

Dataset Information#

Dataset ID	`DS004703`
Title	sEEG Passive listening to natural speech
Year	2023
Authors	Anna Mai, Stephanie Ries, Sharona Ben-Haim, Jerry Shih, Timothy Gentner
License	CC0
Citation / DOI	doi:10.18112/openneuro.ds004703.v1.1.0
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: 10
Recordings: 325
Tasks: 1

Channels & sampling rate

Channels: 148 (8), 276 (4), 279 (4), 277 (4), 280 (2)
Sampling rate (Hz): 1024.0 (14), 512.0 (8)
Duration (hours): 0.0

API Reference#

Use the DS004703 class to access this dataset programmatically.

class eegdash.dataset.DS004703(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

OpenNeuro dataset ds004703. Modality: ieeg; Experiment type: Memory; Subject type: Surgery. Subjects: 10; recordings: 11; 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/ds004703 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds004703

Examples

>>> from eegdash.dataset import DS004703
>>> dataset = DS004703(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