Discover datasets

This dataset contains EEG recordings from 8 healthy adult participants during real-time control of an affective brain-computer music interface (BCMI). Participants listened to 60-second music clips designed to induce specific emotional states defined by valence and arousal dimensions. The dataset includes continuous EEG data sampled at 1 kHz alongside self-reported affective state ratings, enabling investigation of neural correlates of emotion and the efficacy of real-time music-based emotional state modulation.

Participants

8

Channels

32 (10-10)

Size

2.60 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset contains intracranial EEG (iEEG) recordings from human patients, rodents, pigs, and non-human primates acquired using novel flexible, scalable, high-resolution micro-stereo-electrodes. The study evaluates the performance of these custom-fabricated depth electrodes for neural recording and includes direct electrical stimulation experiments to assess stimulation effects on brain activity. Raw and preprocessed epoched data are provided in iEEG-BIDS format with accompanying channel maps and derivatives.

Participants

1

Size

1.36 GB

Version

vv1.0.0

Updated

Jul 10, 2026

Participants

12

Channels

32 (egi-geodesic)

Citations

44

HED

v8.4.0

Size

3.20 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset comprises synchronized multimodal neurophysiological and biomechanical recordings from 128-channel EEG, electromyography (EMG), electrooculography (EOG), and motion capture during a perturbed beam-walking task. Participants performed four 10-minute sessions of standing or walking on a narrow balance beam while exposed to sensorimotor perturbations (visual field rotations or waist pulls). The dataset includes preprocessed EEG data with identified good channels and independent component analysis results, enabling investigation of cortical mechanisms underlying balance control and responses to perturbations.

Participants

30

Channels

128 (biosemi)

Citations

162

Size

10.9 GB

Version

vv1.0.0

Updated

Jul 10, 2026

BigP3BCI Study Q is a P300-based brain-computer interface dataset comprising EEG recordings from 36 ALS subjects across 3 sessions each, using a 6x6 color intensification speller paradigm. The dataset contains 32-channel EEG data sampled at 256 Hz with standardized 10-20 electrode montage, annotated with target and non-target event labels for machine learning applications. This derivative dataset is part of the larger BigP3BCI collection, the largest public P300 BCI dataset with recordings from approximately 267 subjects across 20 studies.

Participants

36

Channels

32 (10-10)

HED

v8.4.0

Size

1.09 GB

Version

vv1.0.1

Updated

Jul 10, 2026

This EEG dataset comprises recordings from 54 healthy participants performing a P300-based copy-spelling task using a 36-symbol row-column speller paradigm. The dataset includes 62 EEG channels and 4 EMG channels sampled at 1000 Hz, with offline training and online test phases designed to investigate BCI illiteracy. Data are provided in BIDS format with HED event annotations and represent a benchmark resource for evaluating brain-computer interface performance across different user populations.

Participants

54

Channels

62 (10-05)

Citations

100

HED

v8.4.0

Size

38.6 GB

Version

vv1.0.1

Updated

Jul 10, 2026

BigP3BCI Study J is a P300-based brain-computer interface dataset comprising EEG recordings from 20 healthy subjects performing a 9x8 character grid speller task. This derivative dataset is part of the larger BigP3BCI collection, the largest public P300 BCI dataset with ~267 subjects across 20 studies. The data were acquired at 256 Hz using 16-channel EEG with a standard 10-20 montage and are organized in BIDS format with HED event annotations for standardized analysis and machine learning applications.

Participants

20

Channels

16 (10-10)

HED

v8.4.0

Size

426 MB

Version

vv1.0.1

Updated

Jul 10, 2026

IACKD is a multimodal neurophysiological dataset combining electroencephalography (EEG) recordings with hand kinematics data collected during a task designed to investigate intention-action conflict. The dataset comprises raw EEG signals and synchronized kinematic measurements from participants performing motor tasks, providing a resource for studying the neural mechanisms underlying motor planning and conflict resolution.

Participants

15

Channels

26 (10-10)

Size

7.35 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset comprises multimodal neurophysiological and kinematic recordings from 25 participants engaged in real-world table tennis gameplay. The collection includes high-density dual-layer electroencephalography, cervical electromyography, inertial measurement unit acceleration data, structural MRI, and synchronized video recordings. Participants completed 60 minutes of table tennis play against both a ball machine and human opponent, with 10 minutes of standing baseline recording. Processed data include independent component analysis decomposition and dipole modeling for EEG signals.

Participants

25

Channels

120 (other)

Citations

24

Size

523 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This EEG dataset comprises recordings from children performing letter discrimination and visual search tasks across three experimental stages: pre-intervention baseline, intervention measurement, and post-intervention assessment. Participants were assigned to intervention and control groups to evaluate the effects of embodied learning on literacy-related neural processing. The dataset includes event markers corresponding to stimulus presentations of letters 'b' and 'd', enabling analysis of neural responses to letter discrimination and visual search performance.

Participants

21

Channels

64 (10-10)

Size

36.6 GB

Version

vv1.0.0

Updated

Jul 10, 2026