DS006434#

The auditory brainstem response to natural speech is not affected by selective attention

Access recordings and metadata through EEGDash.

Citation: Thomas J Stoll, Nathan D Vandjelovic, Melissa J Polonenko, Nadja R S Li, Adrian K C Lee, Ross K Maddox (2025). The auditory brainstem response to natural speech is not affected by selective attention. 10.18112/openneuro.ds006434.v1.2.0

Modality: eeg Subjects: 66 Recordings: 898 License: CC0 Source: openneuro

Metadata: Complete (100%)

Quickstart#

Get Started

Install

pip install eegdash

Access the data

from eegdash.dataset import DS006434

dataset = DS006434(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 = DS006434(cache_dir="./data", subject="01")

Advanced query

dataset = DS006434(
    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{ds006434,
  title = {The auditory brainstem response to natural speech is not affected by selective attention},
  author = {Thomas J Stoll and Nathan D Vandjelovic and Melissa J Polonenko and Nadja R S Li and Adrian K C Lee and Ross K Maddox},
  doi = {10.18112/openneuro.ds006434.v1.2.0},
  url = {https://doi.org/10.18112/openneuro.ds006434.v1.2.0},
}

About This Dataset#

Overview

This is the dataset for our study investigating the effects of selective attention to speech stimuli in the subcortex and cortex, entitled “The auditory brainstem response to natural speech is not affected by selective attention” by Stoll et al. (2025). Please cite our paper if you use our dataset.

It contains EEG data for three experiments, detailed in the paper and

View full README

Overview

This is the dataset for our study investigating the effects of selective attention to speech stimuli in the subcortex and cortex, entitled “The auditory brainstem response to natural speech is not affected by selective attention” by Stoll et al. (2025). Please cite our paper if you use our dataset.

It contains EEG data for three experiments, detailed in the paper and briefly summarized below. Code and stimuli to derive the responses are provided in the Dataset folder and on our lab’s github: maddoxlab/stoll_et_al_selective_attention.

Experiment 1 - diotic stimuli (exp1Diotic) This “task” includes EEG data for 28 subjects who listened to 120 trials each (64 s each; total 128 minutes) of two audiobooks - A Wrinkle in Time (Female narrator) and The Alchemyst (male narrator). Stimuli were set to 65 dB SPL then summed together to be presented diotically. Subjects sat at a computer desk in a soundproof room. They were instructed to attend to only one narrator on each trial, with cues given before they started the trial and through a fixation dot which remained for the duration of the trial. For details, see the Details about the experiment section and refer to our paper.

EEG was recorded simultaneously from a 32 channel activate montage (to examine cortical responses) and a 2 channel passive bipolar montage (FCz to earlobes, to examine subcortical responses). On a subset of the subjects (1, 3, 4, 7, 8, 9, 10, 11, 12, 13, 16, 18) an additional electrode was placed on the eardrum. Data are split into cortical (active) electrodes and subcortical (passive) electrodes. Since data was collected simultaneously, data from all electrodes were sampled at 25 kHz. To reduce file size and computation time, the cortical electrodes were downsampled to 1 kHz and the subcortical electrodes were downsampled to 10 kHz.

Experiment 2 - dichotic stimuli (exp2Dichotic) This “task” contains EEG data for 25 subjects who listened to 60 trials each (64 s each; total 64 minutes) of two audiobooks - A Wrinkle in Time (Female narrator) and The Alchemyst (male narrator). Stimuli were set to 65 dB SPL and presented diotically. Subjects sat at a computer desk in a soundproof room. They were instructed to attend to only one narrator on each trial (indicated by the story name, talker sex, and direction) with cues given before they started the trial and through a fixation dot with an arrow which remained for the duration of the trial. For details, see the Details about the experiment section and refer to our paper. The records of individual participant age and sex no longer exist, but overall statistics are reported in the paper.

EEG was recorded simultaneously from a 32 channel activate montage (to examine cortical responses) and passive electrodes using a bipolar montage, with the noninverting electrode placed on FCz and the inverting electrode on the earlobe, with ground on the forehead. The side the electrode was placed on was counterbalanced across subjects.

Experiment 3 - passive listening to stimuli from Forte et al. (exp3Passive) This “task” contains EEG data for 14 subjects who listened to 32 trials each (~117 s each; total ~62 minutes) of four audiobooks - Tales of Troy: Ulysses the Sacker of Cities and The Green Forest Fairy Book narrated by James K. White for the male speech and The Children of Odin and The Adventures of Odysseus and the Tale of Troy narrated by Elizabeth Klett for the female speech. These audiobooks were selected to match the study by Forte et al. (2017), who provided us with the audio files. Stimuli were set to 73 dB SPL then summed together to be presented diotically (i.e., at 76 dB SPL). The stories were paired in the same manner as in Forte et al. (2017). Subjects sat at a computer desk in a soundproof room. They were instructed to ignore the audio as best they could and distract themselves by watching silent captioned videos of their choosing or by reading. For details, see the Details about the experiment section and refer to our paper.

EEG was recorded with a passive electrodes using a bipolar montage, with the noninverting electrode placed on FCz and the inverting electrode on the earlobe, with ground on the forehead.

Format

The dataset is formatted according to the EEG Brain Imaging Data Structure. See the dataset_description.json file for the specific version used. Generally, you can find detailed event data in the .tsv files and descriptions in the accompanying .json files. Raw eeg files are provided in the Brain Products format.

Details about the experiment

For a detailed description of the task, see Stoll et al. (2025) as well as the supplied file json files.

Trigger onset times have already been corrected for the tubing delay of the insert earphones. Trial numbers and more metadata of the events are in each of the ‘*_eeg_events.tsv” file, which is sufficient to know which trial corresponded to which chapter and which narrator the subjects were instructed to attend. As chapters were organized to allow subjects to follow to stories, all subjects had the same trial order in experiment 1 and 2. Story order was randomized in experiment 3, with that information stored in the ‘*_eeg_evnets.tsv” file.

Dataset Information#

Dataset ID	`DS006434`
Title	The auditory brainstem response to natural speech is not affected by selective attention
Year	2025
Authors	Thomas J Stoll, Nathan D Vandjelovic, Melissa J Polonenko, Nadja R S Li, Adrian K C Lee, Ross K Maddox
License	CC0
Citation / DOI	doi:10.18112/openneuro.ds006434.v1.2.0
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: 66
Recordings: 898
Tasks: 3

Channels & sampling rate

Channels: 32 (104), 2 (56), 1 (48), 3 (28)
Sampling rate (Hz): 10000.0 (104), 1000.0 (56), 500.0 (48), 25000.0 (28)
Duration (hours): 0.0

API Reference#

Use the DS006434 class to access this dataset programmatically.

class eegdash.dataset.DS006434(cache_dir: str, query: dict | None = None, s3_bucket: str | None = None, **kwargs)[source]#

Bases: EEGDashDataset

OpenNeuro dataset ds006434. Modality: eeg; Experiment type: Attention; Subject type: Healthy. Subjects: 66; recordings: 118; tasks: 5.

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/ds006434 NeMAR dataset: https://nemar.org/dataexplorer/detail?dataset_id=ds006434

Examples

>>> from eegdash.dataset import DS006434
>>> dataset = DS006434(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