DS006269#

Tethered EEG Recordings in Syngap1 rats

Access recordings and metadata through EEGDash.

Citation: Lucy Pritchard, Ingrid Buller-Peralta, Sally M Till, Peter C Kind, Alfredo Gonzalez-Sulser (2025). Tethered EEG Recordings in Syngap1 rats. 10.18112/openneuro.ds006269.v1.0.0

Modality: eeg Subjects: 24 Recordings: 164 License: CC0 Source: openneuro

Metadata: Complete (100%)

Quickstart#

Get Started

Install

pip install eegdash

Access the data

from eegdash.dataset import DS006269

dataset = DS006269(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 = DS006269(cache_dir="./data", subject="01")

Advanced query

dataset = DS006269(
    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{ds006269,
  title = {Tethered EEG Recordings in Syngap1 rats},
  author = {Lucy Pritchard and Ingrid Buller-Peralta and Sally M Till and Peter C Kind and Alfredo Gonzalez-Sulser},
  doi = {10.18112/openneuro.ds006269.v1.0.0},
  url = {https://doi.org/10.18112/openneuro.ds006269.v1.0.0},
}

About This Dataset#

This dataset consists of 6-hour long EEG recordings in wildtype (WT) and rats Syngap+/Δ−GAP (HET) rats (male, 12-16 weeks old) starting at zeitgeber time (ZT) 3 to 9 (under a 12 light hr:12 dark hr schedule with lights on at 07:00 am). Associated with each rat is two 6-hour recording files, expect for those which only underwent one recording session (S7020, , S7025, S7030, S7031, S7032, 39, S7040, S7041). Recordings were acquired with an OpenEphys acquisition system (OpenEphys, Portugal) and head-mounted 32-channel EEG array probe (H32-EEG—NeuroNexus, USA) with accelerometers (NeuroNexus, USA), at a sampling rate of 1 kHz. For more detailed methods, please see our associated publication doi: 10.1016/j.celrep.2024.114733.

Dataset Information#

Dataset ID	`DS006269`
Title	Tethered EEG Recordings in Syngap1 rats
Year	2025
Authors	Lucy Pritchard, Ingrid Buller-Peralta, Sally M Till, Peter C Kind, Alfredo Gonzalez-Sulser
License	CC0
Citation / DOI	doi:10.18112/openneuro.ds006269.v1.0.0
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: 24
Recordings: 164
Tasks: 1

Channels & sampling rate

Channels: 32
Sampling rate (Hz): 1000.0
Duration (hours): 0.0

API Reference#

Use the DS006269 class to access this dataset programmatically.

class eegdash.dataset.DS006269(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

OpenNeuro dataset ds006269. Modality: eeg; Experiment type: Resting-state; Subject type: Other. Subjects: 24; recordings: 40; tasks: 2.

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/ds006269 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds006269

Examples

>>> from eegdash.dataset import DS006269
>>> dataset = DS006269(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