Discover datasets

EEG recordings from an online brain-computer interface study with twelve healthy participants using a visual matrix P300 speller. Three fully unsupervised decoding methods were compared: learning from label proportions (LLP), expectation-maximization (EM), and their mixture (MIX). Participants copy-spelled a German sentence across three blocks, one per algorithm. The dataset supports research on calibration-free ERP-based BCIs.

Participants

12

Channels

31 (10-10)

Citations

27

HED

v8.4.0

Size

4.81 GB

Version

v1.0.3

Updated

Oct 8, 2026

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on005289-blue…

Participants

39

Channels

64 (10-10)

Size

22.1 GB

Version

v1.0.0

Updated

Jun 20, 2026

A BIDS-formatted dataset of high-density surface EMG (HDsEMG) recordings from the right tibialis anterior of six healthy male participants. Four 64-channel grids (256 electrodes) recorded trapezoidal isometric dorsiflexion contractions at 30% and 50% of maximal voluntary contraction, together with force signals. The dataset supports studies of electrode grid design and motor unit identification.

Participants

6

Size

448 MB

Version

v1.0.1

Updated

Jun 1, 2026

ODE is an EEG dataset formatted according to BIDS with HED annotations, contributed by Johnson, Gordon, Touryan, and King. The available documentation describes it only as a placeholder dataset, so no further details on content or purpose are provided.

Participants

1

Channels

64 (10-10)

HED

v8.1.0

Size

79.2 MB

Version

v1.0.0

Updated

May 13, 2026

…These tasks were optimized to capture neural activity manifest in perception, cognition…

Participants

127

Channels

27

Citations

8

Size

10.6 GB

Version

v1.0.0

Updated

Jun 28, 2026

…with 4 indicating the pain perception threshold akin to a pricking sensation…

Participants

95

Channels

60 (10-10)

Size

300 GB

Version

v1.0.0

Updated

Jun 26, 2026

A BIDS-formatted EEG dataset of two-class hand-grasping motor tasks (left vs. right hand) from 31 healthy participants, recorded with a 64-channel Neuroscan system at 1000 Hz across up to three sessions of 40 trials each. It is a derivative of the multi-paradigm Eye-BCI dataset, which combines EEG, eye-tracking and high-speed video for ocular activity analysis. It is provided through MOABB for benchmarking motor-related brain-computer interface decoding.

Participants

31

Channels

66 (10-10)

Citations

13

HED

v8.4.0

Size

30.3 GB

Version

v1.0.2

Updated

Aug 18, 2026

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on006104-blue…

Participants

24

Channels

61 (10-10)

Size

83.8 GB

Version

v1.0.0

Updated

Jun 28, 2026

A motor imagery brain-computer interface EEG dataset from 52 healthy subjects performing left- and right-hand kinesthetic finger movement imagery. Recordings include 64-channel EEG and 4 EMG channels sampled at 512 Hz. They are accompanied by psychological and physiological questionnaires, 3D electrode locations, and non-task-related states. This BIDS derivative was generated with MOABB from the original GigaDB deposit.

Participants

52

Channels

64 (10-10)

Citations

91

HED

v8.4.0

Size

16.7 GB

Version

v1.0.2

Updated

Aug 18, 2026

Raw 64-channel EEG, ECG, PPG and behavioral recordings from 30 healthy young adults (18–32 years) during resting state and a verbal working memory digit-span task with serial recall. The resting session alternated eyes-closed and eyes-open blocks followed by passive cartoon viewing. In the working memory task, seven-digit sequences were presented visually either simultaneously or sequentially at different rates and with different inter-stimulus intervals, allowing study of how presentation mode affects neural oscillations and peripheral physiology.

Participants

30

Channels

63 (10-10)

Citations

3

Size

41.4 GB

Version

v1.0.0

Updated

Jun 29, 2026