Discover datasets

EEG recordings from four participants performing motor imagery of the left hand, right hand, and feet, originally reported by Zhou et al. (2016) in a study on automated trial selection for motor imagery brain-computer interfaces. Each participant completed three sessions of two runs, giving 450 trials per subject. Data were recorded from 14 channels at 250 Hz and reformatted into BIDS from a MOABB-generated Zenodo version.

Participants

4

Channels

14 (10-10)

Citations

87

Size

152 MB

Version

v1.0.0

Updated

Mar 3, 2026

…condition during MEG recording (4D NeuroImaging system with 248 magnetometer channels). Current…

Participants

17

Size

225 GB

Version

v1.0.0

Updated

May 18, 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

…Preprocessing was carried out with fMRIPrep (v20.2.0), following standard neuroimaging…

Participants

60

Citations

4

Size

112 GB

Version

v1.0.0

Updated

Jun 26, 2026

This dataset contains EEG recordings from 9 healthy subjects performing cued motor imagery of left hand, right hand, feet, and tongue movements, known as BCI Competition IV Dataset 2a. Each subject completed two sessions of six runs, with 22 EEG and 3 EOG channels sampled at 250 Hz. It is widely used as a benchmark for multi-class motor imagery classification in brain-computer interface research.

Participants

9

Channels

22 (10-10)

Citations

89

HED

v8.4.0

Size

1.38 GB

Version

v1.0.3

Updated

Oct 8, 2026

…Multi-subject, multi-modal (sMRI+fMRI+MEG+EEG) neuroimaging dataset on face…

Participants

17

Citations

82

Size

169 GB

Version

v1.0.0

Updated

Mar 8, 2026

A collection of 2,417 clinical scalp EEG recordings labeled as normal or abnormal, acquired using the standard 10-20 montage with 19 EEG channels plus 2 reference electrodes. Recordings are stored in EDF format with variable sampling rates and durations. The dataset supports EEG-based pathology detection and normal/abnormal classification.

Participants

2417

Channels

21 (10-20)

Size

13.8 GB

Version

v1.0.0

Updated

Jun 1, 2026

A mobile EEG motor imagery dataset from two pilots, one tetraplegic and one able-bodied, recorded during development of the neuroTUM brain-computer interface for the 2024 Cybathlon BCI race. Data were acquired with a 24-channel wireless Smarting mobi system at 250 Hz using an arrow-cue paradigm with subject-specific sets of three mental tasks (rest, hand and/or foot motor imagery). The dataset is re-released in BIDS format with HED annotations via MOABB.

Participants

2

Channels

24 (10-10)

HED

v8.4.0

Size

408 MB

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

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on006525-blue…

Participants

34

Channels

128 (other)

Size

3.00 GB

Version

v1.0.0

Updated

Jun 29, 2026