Discover datasets

Subdural electrocorticography (ECoG) recorded at the University Medical Center Utrecht from three epilepsy patients (S4-S6) who imagined grasping a cylinder with the left or right hand. The data are the subset of participants from Stolk et al. (2019) who gave permission to share, and they support investigation of dissociated alpha and beta rhythmic activity in the human sensorimotor system. Data are released as unprocessed trial segments, stored as epoched recordings with electrode positions and author-provided atlas labels.

Participants

3

Size

663 MB

Version

v1.0.0

Updated

Oct 8, 2026

…edit used in several prior neuroimaging studies; the movie has a frame…

Participants

16

Size

34.2 GB

Version

v1.0.0

Updated

Oct 8, 2026

This dataset contains 32-channel EEG recorded from 22 healthy participants performing visual imagery of ten cued items: animals (dog, bird, fish), geometric figures (pentagram, square, circle), and objects (scissor, watch, cup, chair). Each participant completed up to two sessions of three runs, giving 16,800 trials in total. It is intended for developing visual imagery-based brain-computer interfaces and is distributed in BIDS format with HED event annotations.

Participants

22

Channels

32 (10-10)

Citations

3

HED

v8.4.0

Size

75.4 GB

Version

v1.0.3

Updated

Aug 20, 2026

This dataset contains 63-channel EEG recorded at 512 Hz from 15 stroke patients performing cue-based left-hand versus right-hand motor imagery, with 40 trials per class. For each patient one hand is paretic and the other unaffected, and both were imagined. It is a BIDS re-release of the original figshare deposit, prepared via MOABB with HED event annotations, and is intended for brain-computer interface and neurorehabilitation research.

Participants

15

Channels

63 (other)

HED

v8.4.0

Size

1.74 GB

Version

v1.0.0

Updated

Oct 8, 2026

EEG recordings from 13 healthy participants performing a copy-spelling task with a visual 6x7 matrix ERP speller. The speller was designed for learning from label proportions (LLP), an unsupervised, calibrationless classification approach for ERP-based brain-computer interfaces. Two stimulus sequences with different target/non-target ratios allowed LLP to reconstruct mean target and non-target responses without labeled data. In the original online study, 84.5% of characters were spelled correctly on average without prior calibration.

Participants

13

Channels

31 (10-10)

Citations

46

HED

v8.4.0

Size

5.15 GB

Version

v1.0.3

Updated

Oct 8, 2026

High-density (127-channel) EEG recordings from 30 healthy, right-handed, native Chinese-speaking adults performing imagined and executed vocalization and writing tasks. Stimuli were four Chinese strokes (heng, shu, pie, na) and four English letters (a, b, c, d). The factorial design crossed task mode, action, script and token identity, yielding 32 event-coded conditions and 15,360 task events. The release also includes EEGLAB preprocessing derivatives and subject-level machine-learning exports.

Participants

30

Channels

124 (10-05)

Size

181 GB

Version

v1.0.0

Updated

Sep 8, 2026

This dataset contains simultaneous EEG and fMRI recordings from participants performing an inner speech task, in which eight words were presented in random order and repeated across trials. Data were acquired with a 3T MRI scanner and a 64-channel BrainProducts EEG system in three subjects across two sessions each. EEG data include pulse artifact removal and are organized in BIDS format.

Participants

3

Channels

64

Size

15.3 GB

Version

v1.0.0

Updated

Jun 28, 2026

A cross-session motor imagery EEG dataset from 10 healthy participants who performed cued left- versus right-hand motor imagery across two sessions. Recordings used 28 EEG channels sampled at 250 Hz with a Neuroscan SynAmps2 amplifier, with roughly 180 trials per session. In session 2, test trials included online feedback. The data were re-released in BIDS format via MOABB for brain-computer interface research.

Participants

10

Channels

28 (10-10)

HED

v8.4.0

Size

1.01 GB

Version

v1.0.0

Updated

Oct 8, 2026

This dataset contains simultaneous multimodal EEG and functional near-infrared spectroscopy (fNIRS) recordings from patients undergoing general anesthesia. It is organized in BIDS format and supports research on brain activity and hemodynamics during anesthetic administration and changes in consciousness.

Participants

8

Channels

58 (10-10)

Size

2.90 GB

Version

v1.0.0

Updated

Jun 24, 2026

MEG dataset from 22 participants performing a visual working memory task in which two Gabor stimuli were presented and a retro-cue indicated which stimulus and attribute to maintain for comparison with a probe. Each participant was recorded in two MEG sessions, with a one-back control task and anatomical T1 MRI. The data support investigation of the distinct brain mechanisms of selecting and maintaining information in working memory.

Participants

22

Size

168 GB

Version

v1.0.0

Updated

Jun 21, 2026