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OPEN DATA

The lab is committed to data sharing and providing other researchers with the opportunity to explore new research questions and avenues using our data. Below you find links to EEG, eye-tracking, pupillometry, and other datasets under a Creative Commons license. We continue to add new datasets when the lab publishes new work.

Acknowledging our work

Please cite our work if you use one of our datasets. We also encourage you to reach out to the corresponding and/or senior author and to consider involving them in your project. This may help you get additional insights about the data that may not be detailed in the paper, and it values our contribution, in line with common authorship contributions, for example, Nature's statement: "Each author is expected to have made substantial contributions to the conception or design of the work; or the acquisition, ..."

Story recall data in 11 different languages

​Description: 2-min spoken stories (AI synthesized speech), story texts, and spoken recall data by younger participants from 11 different language backgrounds. Participants listened to and recalled the stories in their native language.

Link: download data

Reference: Herrmann B (2025) Language-agnostic, automated assessment of listeners' speech recall using large language models. Trends in Hearing.

MEG and eye-tracking data during effortful listening and different levels of motivation

Pupil-size and eye-movement data during listening and different levels of motivation

​Description: MEG and eye-movement data from younger adults who listened to noise sounds and performed a gap detection task. Gap detection was either easy or difficult and motivation was manipulated.

Link: download data

Reference: Kraus F, Ross B, Herrmann B, Obleser J (2024) Neurophysiology of effortful listening: decoupling motivational modulation from task demands. The Journal of Neuroscience 44:e0589242024.

​Description: Pupil-size and eye-movement data from younger adults who listened to noise sounds and performed a gap detection task. Gap detection was either easy or difficult and motivation was manipulated.

Link: download data

Reference: Kraus F, Obleser J, Herrmann B (2023) Pupil size sensitivity to listening demand depends on motivational state. eNeuro 10:ENEURO.0288-23.2023.

EEG data from younger adults performing an audio-visual dual or single task

Eye-movement and pupillometry data from younger adults listening to speech

​Description: Eye-link eye-tracking and pupillometry recordings for three experiments. In the experiments, participants listened to sentence or stories under varying degrees of background masking and different visual screen displays.

Link: download data

Reference: Cui ME, Herrmann B (2023) Eye movements decrease during effortful speech listening. The Journal of Neuroscience 43:5856-5869.

​Description: 64-channel EEG data from two sessions in which participants performed an auditory-gap detection task and concurrently (dual task) or independently (single task) performed a multiple-object tracking task.

Link: download data

Reference: Kraus F, Tune S, Obleser J, Herrmann B (2023) Neural alpha oscillations and pupil size differentially index cognitive demand under competing audio-visual task conditions. The Journal of Neuroscience 43:4352-4364.

Speech-intelligibility data from younger and older adults listening to masked speech

Intelligibility data from younger and older adults listening to AI synthesized speech

​Description: Intelligibility data for three experiments in younger and older adults listening to speech masked by different degrees of background sound and maskers with different envelope shapes. Participants listened either to speech spoken by a human or to speech generated using modern AI speech synthesizers.

Link: download data

Reference: Herrmann B (2023) The perception of artificial-intelligence (AI) based synthesized speech in younger and older adults. Int J Speech Tech. 26:395-415.

​Description: Intelligibility data for three experiments in younger and older adults listening to speech masked by different degrees of background sound and maskers with different envelope shapes. In one experiment, participants listened to disconnected sentences. In two other experiments, they listened to spoken stories.

Link: download data

Reference: Irsik VC, Johnsrude IS, Herrmann B (2022) Age-related deficits in dip-listening evident for isolated sentences but not for spoken stories. Scientific Reports 12:5898.

MEG data from younger and older adults listening to sounds with regular patterns

EEG data from younger and older adults listening to amplitude-modulated sounds

​Description: 16-channel Biosemi EEG data. Younger and older adults listened to 4-Hz amplitude-modulated sounds with different envelope shapes. The data set comprises raw data and related information.

Link: download data

Reference: Irsik V, Almanaseer A, Johnsrude IS, Herrmann B (2021) Cortical responses to the amplitude envelopes of sounds change with age. The Journal of Neuroscience 41:5045-5055.

​Description: 306-channel Neuromag MEG. Younger and older adults listened to sounds that contained a regular pattern and sounds without a pattern. The data set comprises raw data and related information.

Link: download data

Reference: Herrmann B, Maess B, Johnsrude IS (2022) A neural signature of regularity in sound is reduced in older adults. Neurobiology of Aging 109:1-10.

EEG data from five experiments on perceptual learning of auditory patterns

Eye-tracking & pupillometry during sentence listening

​Description: 16-channel Biosemi EEG data from five experiments and behavioral data from one experiment. Participants listened to sounds containing auditory patterns that either repeated or were novel. The data set comprises raw data and related information.

Link: download data

Reference: Herrmann B, Araz K, Johnsrude IS (2021) Sustained neural activity correlates with rapid perceptual learning of auditory patterns. NeuroImage 238:118238.

​Description: Eye-link 1000 data from participants listening to sentences with low- and high-ambiguity words presented under different acoustic degradation conditions.

Link: download data

Reference: Kadem M, Herrmann B, Rodd JM, Johnsrude IS (2020) Pupil dilation is sensitive to semantic ambiguity and acoustic degradation. Trends in Hearing 24:1-16.

©2025 by Auditory Aging

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