Discover datasets

Open-access EEG dataset from Experiment B of Shin et al. (2017), recorded alongside NIRS for hybrid brain-computer interface research. 29 healthy participants performed cued mental arithmetic (serial subtraction) versus resting-baseline trials across alternating sessions. This derivative release contains preprocessed 30-channel EEG (CAR, 0.5-50 Hz bandpass, ICA-based EOG rejection, 200 Hz) with HED event annotations, formatted for benchmarking single-trial classification in MOABB.

Participants

29

Channels

30 (10-05)

Citations

95

HED

v8.4.0

Size

6.62 GB

Version

v1.0.3

Updated

Aug 18, 2026

EEG recordings from 10 persons with cervical spinal cord injury performing attempted arm and hand movements: hand open, palmar grasp, lateral grasp, pronation and supination. Sixty-one EEG channels and 3 EOG channels were recorded across 9 runs per participant. Low-frequency time-domain EEG (movement-related cortical potentials) was used to decode the five movement classes offline, and an online proof-of-concept for self-paced movement detection was also run. The dataset supports research on neuroprosthetic and upper-limb control brain-computer interfaces.

Participants

10

Channels

61 (10-05)

Citations

96

HED

v8.4.0

Size

4.51 GB

Version

v1.0.3

Updated

Oct 8, 2026

EEG recordings of motor imagery and motor execution for six activities (raising and lowering each hand, standing and sitting) from 30 healthy participants over two sessions. Data were acquired with a 14-channel Emotiv EPOC X headset at 128 Hz. This BIDS re-release, produced via MOABB, exposes a 3-class imagery task (left hand, right hand, trunk) for brain-computer interface research. The distributed imagery files carry no per-repetition activity label, so only folder-level 3-class labels are available.

Participants

30

Channels

14 (10-10)

HED

v8.4.0

Size

41.2 MB

Version

v1.0.0

Updated

Oct 8, 2026

Beetl2021-B is a preprocessed 32-channel EEG dataset from the NeurIPS 2021 BEETL competition, built to benchmark transfer learning for motor imagery decoding. It contains recordings from 2 healthy subjects performing four-class motor imagery (left hand, right hand, feet, rest) at 200 Hz, totaling 1590 trials. The dataset supports evaluation of cross-subject and cross-dataset generalization and domain adaptation in brain-computer interfaces.

Participants

2

Channels

32 (10-10)

Citations

1

HED

v8.4.0

Size

1.99 GB

Version

v1.0.5

Updated

Aug 20, 2026

A multi-day EEG dataset for motor imagery brain-computer interface (MI-BCI) research collected at Shanghai University (WBCIC-SHU). It contains recordings from 51 healthy, BCI-naive participants who performed left- and right-hand motor imagery over three sessions on different days. A subset of 11 participants also performed a three-class paradigm that adds foot-hooking imagery. Recordings were made with a 59-channel EEG system and the dataset is accompanied by benchmark classification results using CSP, FBCSP, EEGNet, deepConvNet and FBCNet.

Participants

51

Channels

59 (10-10)

Citations

44

HED

v8.4.0

Size

154 GB

Version

v1.0.5

Updated

Aug 18, 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

EEG recordings from 9 healthy, BCI-naive participants performing two-class motor imagery (left vs. right hand), originally released as BCI Competition 2008 (IV) Graz data set B (Dataset 2b). Each participant completed five sessions: two screening sessions without feedback and three sessions with smiley visual feedback. Three bipolar EEG channels (C3, Cz, C4) and three EOG channels were recorded at 250 Hz.

Participants

1

Channels

3 (10-20)

Citations

83

HED

v8.4.0

Size

478 MB

Version

v1.0.3

Updated

Oct 8, 2026

This dataset contains functional near-infrared spectroscopy (fNIRS) recordings collected while participants performed spatial attention tasks during complex auditory scene analysis. It supports research on decoding the focus of spatial attention from hemodynamic signals. The data are organized in BIDS format and accompany a published data paper.

Participants

12

Size

2.19 GB

Version

v1.0.0

Updated

Jun 18, 2026

Magnetoencephalography and anatomical MRI recorded from 10 participants during a passive hMT+ (human visual motion area) localizer task. Participants viewed random dot clouds that either stayed incoherent or turned coherent (up or down) after 500 ms. The data come from the vision-only training group of a study on supramodal processing, visual perceptual learning, and plasticity.

Participants

12

Citations

31

Size

10.1 GB

Version

v1.0.0

Updated

Jun 21, 2026

This dataset provides eyes-open scalp EEG recordings acquired during intermittent photic stimulation (5 to 30 Hz in 5 Hz steps) from 36 participants with Alzheimer's disease, 23 with frontotemporal dementia, and 29 healthy controls. It complements an earlier eyes-closed resting-state dataset of the same cohort, and participant numbers match between the two. Raw and preprocessed (filtered, ASR- and ICA-cleaned) recordings are provided in BIDS format alongside clinical MMSE scores and demographics.

Participants

88

Channels

19 (10-20)

Citations

21

Size

2.11 GB

Version

v1.0.0

Updated

Jun 28, 2026