DS006104: eeg dataset, 24 subjects#

Name: EEG dataset for speech decoding
Published: 2025
License: CC0

EEG dataset for speech decoding

Access recordings and metadata through EEGDash.

Citation: João Pedro Carvalho Moreira, Vinícius Rezende Carvalho, Eduardo Mazoni Andrade Marçal Mendes, Ariah Fallah, Terrence J. Sejnowski, Claudia Lainscsek, Lindy Comstock (2025). EEG dataset for speech decoding. 10.18112/openneuro.ds006104.v1.0.1

Modality: eeg Subjects: 24 Recordings: 56 License: CC0 Source: openneuro

Metadata: Complete (100%)

Quickstart#

Get Started

Install

pip install eegdash

Access the data

from eegdash.dataset import DS006104

dataset = DS006104(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 = DS006104(cache_dir="./data", subject="01")

Advanced query

dataset = DS006104(
    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{ds006104,
  title = {EEG dataset for speech decoding},
  author = {João Pedro Carvalho Moreira and Vinícius Rezende Carvalho and Eduardo Mazoni Andrade Marçal Mendes and Ariah Fallah and Terrence J. Sejnowski and Claudia Lainscsek and Lindy Comstock},
  doi = {10.18112/openneuro.ds006104.v1.0.1},
  url = {https://doi.org/10.18112/openneuro.ds006104.v1.0.1},
}

About This Dataset#

EEG dataset for speech decoding

Dataset Overview

This dataset contains EEG recordings from a phoneme discrimination task with TMS. The data were collected during two related studies in 2019 and 2021. Study 1 (2019, Session 01): - 8 participants (P01-P08)

Dataset Information#

Dataset ID	`DS006104`
Title	EEG dataset for speech decoding
Author (year)	`Moreira2025`
Canonical	—
Importable as	`DS006104`, `Moreira2025`
Year	2025
Authors	João Pedro Carvalho Moreira, Vinícius Rezende Carvalho, Eduardo Mazoni Andrade Marçal Mendes, Ariah Fallah, Terrence J. Sejnowski, Claudia Lainscsek, Lindy Comstock
License	CC0
Citation / DOI	doi:10.18112/openneuro.ds006104.v1.0.1
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: 56
Tasks: 3

Channels & sampling rate

Channels: 61 (53), 83 (3)
Sampling rate (Hz): 2000.0
Duration (hours): 50.75694444444444

API Reference#

Use the DS006104 class to access this dataset programmatically.

class eegdash.dataset.DS006104(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

EEG dataset for speech decoding

Study:: ds006104 (OpenNeuro)
Author (year):: Moreira2025
Canonical:: —

Also importable as: DS006104, Moreira2025.

Modality: eeg; Experiment type: Perception; Subject type: Healthy. Subjects: 24; recordings: 56; 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/ds006104 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds006104 DOI: https://doi.org/10.18112/openneuro.ds006104.v1.0.1

Examples

>>> from eegdash.dataset import DS006104
>>> dataset = DS006104(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