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

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on003194-blue…

Participants

15

Channels

19 (10-20)

Size

189 MB

Version

v1.0.0

Updated

May 13, 2026

A large-scale (N=356) multi-laboratory EEG replication of DeLong, Urbach & Kutas (2005), testing whether readers pre-activate the phonological form of upcoming nouns during sentence comprehension. Participants at nine UK laboratories read sentences word by word, with indefinite articles (a/an) preceding expected or unexpected nouns. The data show reliable N400 effects on target nouns but no statistically significant effect on the preceding articles, which challenges strong accounts of prediction. The release includes all subjects with available raw data and a flag marking those included in the original paper's analyses.

Participants

356

Channels

63 (10-10)

Citations

98

Size

103 GB

Version

v1.1.0

Updated

Jul 5, 2026

…medication dosage. - **MoCA** (Montreal Cognitive Assessment) - a global measure of cognitive function…

Participants

144

Channels

65 (10-10)

Citations

1

Size

4.26 GB

Version

v1.0.0

Updated

Jun 30, 2026

FOODEEG is an open dataset of electroencephalographic (EEG) and behavioural responses to food images from 117 participants. In one session, EEG was recorded during a food categorisation task in which participants judged images as healthy, tasty, or something they were willing to eat. In a second session, participants completed a food go/no-go task, a paired choice task, and questionnaires on dietary style and motivation. The dataset also includes raw and cleaned EEG data and normative ratings of the food stimuli from online samples.

Participants

117

Size

91.1 GB

Version

v1.0.0

Updated

Jun 29, 2026

…Clinical and EEG assessments were conducted at baseline (pre-intervention) and after…

Participants

45

Channels

21 (10-20)

Size

476 MB

Version

v1.0.0

Updated

Jun 19, 2026

…cross-subject and cross-dataset assessment. ## How to Access via MOABB Install…

Participants

2

Channels

32 (10-10)

Citations

1

HED

v8.4.0

Size

1.99 GB

Version

v1.0.5

Updated

Aug 20, 2026

Multimodal dataset of 31 participants watching five short educational videos while EEG, ECG, EOG, gaze, pupil size, blinks, saccades, and head motion were recorded. Each participant completed an attentive session, in which factual questions followed each video, and a distracted session, in which they silently counted backwards. Experiment 2 uses an incidental learning design, so participants did not know in advance that they would be tested. Questionnaire data, including stimulus-related questions and the ASRS adult ADHD checklist, are included.

Participants

31

Channels

64 (10-10)

Size

5.25 GB

Version

v1.0.0

Updated

Jun 3, 2026

…reported normal hearing and normal neuropsychological language testing (Boston Naming and verbal…

Participants

4

Size

104 GB

Version

v1.0.0

Updated

Oct 8, 2026

This dataset provides simultaneous EEG and fNIRS recordings from 12 participants performing a silent naming task and three sensory-based imagery tasks (visual, auditory, tactile) on objects from the semantic categories of animals and tools. It supports research on semantic decoding and brain-computer interfacing. Stimulus images and example Python scripts for loading the data with MNE and MNE-BIDS are included.

Participants

12

Channels

64 (biosemi)

Citations

11

Size

24.2 GB

Version

v1.0.0

Updated

Jun 24, 2026