Discover datasets

EEG recordings from a simulated driving study designed to assess fatigue-related changes in performance through EEG biomarkers. Participants completed a 60-minute driving task (six 10-minute blocks) with steering and speed control and periodic lateral perturbations. Data were collected at three sites (ARL, Teledyne, SAIC) using 64- or 256-channel BioSemi EEG systems. The dataset is part of the BCIT program and is a companion to the Calibration Driving session.

Participants

109

Channels

64 (10-10)

Citations

31

HED

v8.0.0

Size

302 GB

Version

v1.0.0

Updated

Jun 23, 2026

…standards, enabling standardized analysis and benchmarking of brain-computer interface paradigms based…

Participants

54

Channels

62 (10-05)

Citations

101

Size

72.4 GB

Version

v1.0.8

Updated

Oct 8, 2026

EEG and behavioral dataset from a prolonged simulated driving study in which participants completed two 45-minute driving sessions with lateral perturbations and auditory cues. Cues were either random or predictive of perturbation onset. The study was designed to identify driver fatigue biomarkers from EEG and to compare them with objective driving performance measures. Data are in BIDS format and include EEG, eye tracking and vehicle logs.

Participants

17

Channels

64 (10-10)

Citations

27

HED

v8.0.0

Size

20.4 GB

Version

v1.0.0

Updated

Jun 23, 2026

…BCI datasets, used extensively for benchmarking classification algorithms. The dataset was part…

Participants

5

Channels

118 (10-05)

Citations

86

HED

v8.4.0

Size

735 MB

Version

v1.0.3

Updated

Aug 18, 2026

EEG dataset from twenty-one participants performing a continuous feedback learning task in which they predicted the final level of an animated rising bar. Cues (gnomes) differed in how predictable the outcome was (highly predictable, somewhat predictable, unpredictable), enabling study of feedback processing under varying outcome uncertainty. Points were awarded according to the accuracy of each guess.

Participants

21

Channels

31 (10-10)

Citations

1

Size

3.48 GB

Version

v1.0.0

Updated

Jun 23, 2026

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.nm000336-blue…

Participants

20

Channels

32 (10-10)

Citations

2

HED

v8.4.0

Size

6.59 GB

Version

v1.0.4

Updated

Oct 8, 2026

Beetl2021-A is a preprocessed four-class motor imagery EEG dataset (rest, left hand, right hand, feet) from Task 2 of the BEETL Competition at NeurIPS 2021. It contains 63-channel recordings at 500 Hz from healthy participants playing an online BCI racing game (Cybathlon2020IC), with 1490 trials of 4 s each in a single session. It serves as a benchmark for transfer learning and domain adaptation across heterogeneous EEG datasets and subjects, and is re-hosted in BIDS format via the MOABB pipeline.

Participants

3

Channels

63 (10-10)

HED

v8.4.0

Size

2.17 GB

Version

v1.0.6

Updated

Aug 20, 2026

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.nm000303-blue…

Participants

18

Channels

32 (10-10)

Citations

2

HED

v8.4.0

Size

3.23 GB

Version

v1.0.4

Updated

Oct 8, 2026

The BETA database contains 64-channel EEG recordings from 70 healthy participants (aged 9-64 years) performing a 40-target cued-spelling SSVEP-BCI task. Stimuli used joint frequency and phase modulation (JFPM) on a 5x8 virtual keyboard, with frequencies of 8-15.8 Hz. Data were recorded in a normal classroom rather than a shielded room, giving a more realistic benchmark for SSVEP-based brain-computer interfaces.

Participants

70

Channels

64 (10-10)

Citations

97

HED

v8.4.0

Size

7.72 GB

Version

v1.0.2

Updated

Aug 18, 2026

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.nm000340-blue…

Participants

20

Channels

16 (10-10)

Citations

2

HED

v8.4.0

Size

1.49 GB

Version

v1.0.3

Updated

Aug 18, 2026