Discover datasets

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

…on the presence of user input and interaction in the experiment. #### Passive…

Participants

150

Channels

129 (egi-geodesic)

Citations

21

HED

v8.3.0

Size

112 GB

Version

v1.0.0

Updated

May 25, 2026

Intracranial EEG (iEEG) recordings used to evaluate a flexible, scalable, high-channel-count micro-stereo-electrode for recording neural activity in the brain. The dataset includes raw and preprocessed (epoched) recordings from multiple species, including human patients, non-human primates, pigs and rodents. Direct electrical stimulation was used to examine the effects of stimulation on brain activity. Data are organized in iEEG-BIDS format, with binary files and channel maps in the derivatives folder.

Participants

1

Citations

3

Size

1.36 GB

Version

v1.0.0

Updated

Jun 25, 2026

…on the presence of user input and interaction in the experiment. #### Passive…

Participants

324

Channels

129 (egi-geodesic)

Citations

21

HED

v8.3.0

Size

230 GB

Version

v1.0.0

Updated

May 25, 2026

A multimodal dataset of high-density, dual-layer EEG, neck EMG, inertial measurement unit acceleration, T1 structural MRI, and video recorded from 25 participants playing real-world table tennis. Each participant played 60 minutes of table tennis against a ball machine and a human player, plus a 10-minute standing baseline. Processed data include ICA decompositions and dipole models, with raw data in the sourcedata folder.

Participants

25

Channels

120 (other)

Citations

25

Size

523 GB

Version

v1.0.0

Updated

Jun 24, 2026

…OSAT/PR/Pleth and unused inputs (C99-C128, typed MISC). Channel types…

Participants

13

Channels

28 (10-10)

Size

514 GB

Version

v1.0.0

Updated

Oct 13, 2026

This dataset is Study Q of bigP3BCI, an open, machine-learning-ready collection of P300-based brain-computer interface EEG recordings. It contains 32-channel EEG from 36 participants, each recorded over 3 sessions, while they used a 6x6 character speller with color intensification. Target and non-target events are annotated with HED tags. The dataset is a BIDS-formatted derivative of the PhysioNet bigP3BCI release, prepared with MOABB.

Participants

36

Channels

32 (10-10)

Citations

2

HED

v8.4.0

Size

3.70 GB

Version

v1.0.4

Updated

Oct 8, 2026

…on the presence of user input and interaction in the experiment. #### Passive…

Participants

257

Channels

129 (egi-geodesic)

Citations

21

HED

v8.3.0

Size

157 GB

Version

v1.0.0

Updated

May 25, 2026

EEG recordings from healthy participants performing self-initiated palmar and lateral reach-and-grasp actions, acquired simultaneously across three recording systems: gel-based laboratory EEG, water-based mobile EEG, and dry-electrode mobile EEG. The dataset supports investigation of the feasibility of decoding natural reach-and-grasp movement-related cortical potentials across EEG acquisition modalities for brain-computer interface applications. It is distributed in BIDS format as part of the MOABB benchmark collection.

Participants

45

Channels

58 (10-05)

Citations

50

HED

v8.4.0

Size

8.67 GB

Version

v1.0.4

Updated

Oct 8, 2026

…on the presence of user input and interaction in the experiment. #### Passive…

Participants

135

Channels

129 (egi-geodesic)

Citations

21

HED

v8.3.0

Size

90.8 GB

Version

v1.0.0

Updated

May 25, 2026