Discover datasets

EEG recordings from 25 college-age participants performing a probabilistic reinforcement learning task with affective feedback (Experiment 2). The dataset was collected to examine how the Reward Positivity (RewP) event-related potential is sensitive to affective liking of feedback stimuli. Data were acquired circa 2019 at the University of New Mexico.

Participants

25

Channels

66 (10-10)

Size

4.62 GB

Version

v1.0.0

Updated

Jun 22, 2026

EEG dataset from a semantic fear conditioning task, collected to examine how awareness of stimulus contingencies shapes neural responses during fear conditioning. The recordings were used in an accompanying study by Pavlov and colleagues on contingency awareness. The data are organized in BIDS format with HED annotations.

Participants

81

Channels

63 (10-10)

Size

19.8 GB

Version

v1.0.0

Updated

Jun 27, 2026

This dataset contains human EEG recorded during three cross-species behavioral paradigms from 57 participants, collected to identify electrophysiological biomarkers of behavioral dimensions. Mouse data from the same paradigms are included in the code folder to support translational comparisons. Trigger codes were recorded as binary recombinations and can be re-translated to 0-255 values using the provided MATLAB scripts.

Participants

57

Channels

64 (10-10)

Citations

1

Size

16.3 GB

Version

v1.0.0

Updated

Jun 22, 2026

EEG dataset from the Advanced Guard Duty study, which measured sustained vigilance in a realistic setting. Participants verified replica ID badges against reference face images while the ID presentation rate and verification criteria varied across ten 5-minute blocks. Recordings include 256-channel BioSemi EEG with eye and mastoid channels, along with eye tracking and behavioral data on accuracy and processing time. The driving tasks that accompanied the guard duty task are not included.

Participants

27

Channels

256 (biosemi)

Citations

25

HED

v8.0.0

Size

67.6 GB

Version

v1.0.0

Updated

Jun 23, 2026

This dataset is a BIDS-formatted derivative of Study M from the bigP3BCI collection, a large open P300-based brain-computer interface resource. It contains 16-channel EEG recorded at 256 Hz from 21 participants using a 9x8 character speller grid with adaptive and checkerboard stimulus paradigms. Target and non-target events are annotated with HED tags, supporting machine-learning work on P300 speller classification.

Participants

21

Channels

16 (10-10)

Citations

2

HED

v8.4.0

Size

2.38 GB

Version

v1.0.2

Updated

Aug 18, 2026

EEG recordings from 25 healthy volunteers playing Brain Invaders, a visual P300 brain-computer interface inspired by the video game Space Invaders. Data were acquired with 16 electrodes at GIPSA-lab (Grenoble, France) in 2012, using a training-test design with Target and NonTarget flashes of alien groups. This BIDS version was generated from the original Zenodo deposit through MOABB.

Participants

23

Channels

17 (10-20)

Citations

1

HED

v8.4.0

Size

312 MB

Version

v1.0.5

Updated

Oct 8, 2026

This dataset is Study Q of bigP3BCI, an open, machine-learning-ready collection of P300-based brain-computer interface EEG recordings. It contains 32-channel EEG from 36 participants, each recorded over 3 sessions, while they used a 6x6 character speller with color intensification. Target and non-target events are annotated with HED tags. The dataset is a BIDS-formatted derivative of the PhysioNet bigP3BCI release, prepared with MOABB.

Participants

36

Channels

32 (10-10)

Citations

2

HED

v8.4.0

Size

3.70 GB

Version

v1.0.4

Updated

Oct 8, 2026

This dataset contains functional near-infrared spectroscopy (fNIRS) recordings of prefrontal cortex activity from 20 participants (ages 21-46; 5 female, 15 male) in a driving simulator. Participants experienced fourteen types of highly automated driving scenarios, and the dataset accompanies scenario data and subjective danger ratings. It is intended to support study of prefrontal activity differences between low-risk and high-risk driving episodes, with potential application to brain-computer interfaces and improving safety of the intended functionality (SOTIF).

Participants

20

Size

2.32 GB

Version

v1.0.0

Updated

Jun 18, 2026

Neuma is a multimodal neuromarketing dataset from 42 participants who browsed supermarket advertising brochures and selected the products they intended to buy. It combines EEG, eye tracking, questionnaire responses (demographic, profiling and product-related) and computer mouse data. The dataset supports research on consumer behavior and decision-making.

Participants

42

Channels

24 (10-20)

Size

602 MB

Version

v1.0.0

Updated

May 13, 2026

This dataset is Study F of the bigP3BCI collection, a P300-based brain-computer interface speller dataset. It contains 16-channel EEG recorded at 256 Hz over three sessions per subject from 10 participants using a 6x6 character grid with multiple stimulus paradigms. Target and non-target events are annotated with HED tags. The data is a BIDS-formatted derivative of the PhysioNet bigP3BCI release, prepared through MOABB.

Participants

10

Channels

16 (10-10)

Citations

2

HED

v8.4.0

Size

1.91 GB

Version

v1.0.2

Updated

Aug 18, 2026