Discover datasets

This dataset comprises EEG recordings from 11 ALS patients performing a P300-based brain-computer interface speller task using a 6x6 character grid. The study is part of the BigP3BCI project, the largest public P300 BCI dataset, and includes 16-channel EEG data sampled at 256 Hz with visual stimulus presentations and target/non-target event classifications. Data were collected in a laboratory setting with online feedback to support BCI-based communication applications.

Participants

11

Channels

16 (10-10)

HED

v8.4.0

Size

2.69 GB

Version

v1.0.2

Updated

Aug 18, 2026

This dataset comprises electroencephalography (EEG) recordings from 50 healthy control participants performing a reinforcement learning task under two mood conditions: sad mood manipulation (n=25) and neutral mood manipulation (n=25). The task included training and testing phases adapted from established reinforcement learning paradigms. Data were collected between 2019-2021 at the Cognitive Rhythms and Computation Lab at the University of New Mexico to investigate the effects of mood state on learning and decision-making processes.

Participants

50

Channels

66 (10-10)

Citations

1

Size

9.81 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises steady-state visually evoked potential (SSVEP) recordings from 23 healthy participants performing a brain-computer interface task during various locomotor states (standing, walking, running). The study includes 73-channel EEG data acquired at 100 Hz across 4 sessions per subject, with visual stimuli presented at three frequencies (5.45, 8.57, and 12.0 Hz). The dataset is designed to evaluate mobile BCI performance and the feasibility of SSVEP-based control during dynamic physical activity. This is a BIDS-formatted derivative of the original dataset published by Lee et al. (2021) and available at https://osf.io/r7s9b/.

Participants

23

Channels

73 (other)

Citations

34

HED

v8.4.0

Size

1.31 GB

Version

v1.0.2

Updated

Aug 18, 2026

A multi-session EEG dataset acquired from 15 healthy participants performing resting state and graded cognitive tasks (MATB-II at three difficulty levels). The dataset comprises 62-channel EEG recordings at 500 Hz sampling rate designed for passive brain-computer interface applications and mental workload estimation in neuroergonomic contexts. Raw EEG data are provided with standardized event annotations using HED 8.4.0 schema and MOABB-compatible feature extraction pipelines (bandpower analysis and Riemannian covariance methods) for benchmarking purposes.

Participants

15

Citations

61

HED

v8.4.0

Size

1.22 GB

Version

v1.0.0

Updated

Jul 10, 2026