Discover datasets

This dataset comprises EEG recordings and behavioral data from 300 face, illusory face, and matched non-face object stimuli presented during three tasks: spontaneous dissimilarity judgments, face-likeness ratings, and face/object discrimination. Neural activity was recorded while participants performed an orthogonal target detection task during stimulus presentation at 3.75 Hz, enabling investigation of the neural correlates underlying distinct stages of spontaneous face perception.

Participants

21

Citations

2

Size

32.0 GB

Version

v1.0.0

Updated

Jul 10, 2026

…age (18-35 years); affiliation to social insurance; having read the information…

Participants

165

Channels

64 (biosemi)

Citations

16

Size

6.41 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains electroencephalogram (EEG) recordings from 15 university students (8 males, 7 females; aged 21-23 years) collected to investigate brain connectivity during learning processes involving generative AI. Participants performed essay-writing tasks under varying AI interaction conditions, enabling assessment of cognitive states such as creativity, memory, and critical thinking.

Participants

15

Channels

14 (other)

Size

1.17 GB

Version

v1.0.0

Updated

Sep 8, 2026

This dataset contains EEG recordings from an experiment investigating how stylized, exaggerated facial images enhance event-related potential (ERP) features relevant to emotion detection. The study demonstrates that artificially modified human faces elicit a stronger N170 component compared to natural faces, informing the design of affective brain-computer interfaces (BCIs). Participant identifying information has been removed for anonymization.

Participants

26

Channels

28 (10-10)

Size

2.46 GB

Version

v1.0.0

Updated

Aug 19, 2026

A P300-based brain-computer interface dataset for home appliance control, comprising EEG recordings from 14 healthy subjects performing a visual oddball task with 31-channel recordings at 500 Hz sampling rate. The dataset includes 50 training and 30 testing blocks per subject, with target and non-target stimulus classifications presented via LCD display in an online BCI paradigm.

Participants

14

Channels

31 (10-10)

Citations

9

HED

v8.4.0

Size

644 MB

Version

v1.0.3

Updated

Aug 18, 2026

This dataset comprises electroencephalography, physiological, and behavioral data collected from 103 healthy individuals (ages 21-45) during visual illusion perception tasks and resting-state recordings. Participants performed perceptual judgments on three classic visual illusions (Ebbinghaus, Müller-Lyer, and Vertical-Horizontal) with manipulated difficulty and illusion strength, followed by an 8-minute eyes-closed resting-state period. The multimodal dataset includes 64-channel EEG, electrocardiogram, photoplethysmography, and respiration signals, enabling investigation of neural correlates of visual illusion sensitivity and resting-state brain activity.

Participants

103

Channels

59 (10-10)

Size

219 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset contains EEG recordings from an affective state reinforcement learning task performed by 54 community participants classified as light or heavy drinkers. The task involved alcohol-related imagery to examine reward-related neural responses, specifically the reward positivity, in relation to drinking status. Data were collected between 2019 and 2021 at the Clinical Research Center of the University of New Mexico.

Participants

54

Channels

66 (10-10)

Size

9.48 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains EEG/ERP data from an experiment examining sensitivity to semantic and syntactic violations in deaf readers. Participants read sentences presented word-by-word (RSVP) that contained subject-verb agreement violations, semantic violations, combined violations, word-order violations, or correct control sentences, while EEG was recorded. The study aims to characterize how deaf readers process linguistic anomalies at the neural level.

Participants

62

Channels

32 (10-10)

Citations

2

Size

8.53 GB

Version

v1.0.0

Updated

Aug 19, 2026

This EEG dataset investigates how diffuse (categorical) predictions about stimulus orientation shape neural representations during memory encoding. Participants performed an orientation working-memory task in which a central color cue indicated whether an upcoming grating's orientation was drawn from a predictable 90° range or was fully unpredictable, and later judged whether a probe was rotated clockwise or counterclockwise relative to the memorized orientation. The study examines how predictive information stabilizes and reshapes neural codes for encoded visual features.

Participants

47

Channels

66 (10-10)

Size

145 GB

Version

v1.0.0

Updated

Aug 18, 2026

BigP3BCI Study S2 is a P300-based brain-computer interface dataset comprising EEG recordings from 24 healthy subjects performing a 9x8 house/tool visual speller paradigm. The dataset contains 32-channel EEG data sampled at 256 Hz, annotated with target and non-target event classifications using HED 8.4.0 schema. This dataset is part of the larger BigP3BCI collection (the largest public P300 BCI dataset with recordings from approximately 267 subjects across 20 studies), designed to support machine learning research and BCI benchmarking. Trial intervals span 0-1.0 seconds from stimulus onset.

Participants

24

Channels

32 (10-10)

HED

v8.4.0

Size

3.74 GB

Version

v1.0.3

Updated

Aug 18, 2026