Discover datasets

EEG recordings from 10 healthy participants performing two-class motor imagery (left vs. right hand) cued by arrows. Data were recorded with a 128-channel BrainAmp system at 500 Hz, with 150 trials per participant in a single session. The dataset was collected to evaluate beamforming and spatial filtering approaches (e.g., CSP, Laplacian) for noninvasive brain-computer interfaces.

Participants

10

Channels

128 (other)

Citations

75

HED

v8.4.0

Size

5.49 GB

Version

v1.0.2

Updated

Aug 18, 2026

A 60-channel EEG dataset from 10 healthy, BCI-naive participants performing simple limb motor imagery (left hand, right hand, feet) and compound limb motor imagery (both hands, left hand with right foot, right hand with left foot), plus a rest condition. The recordings were used to examine EEG oscillatory patterns (ERD/ERS), cognitive processes, and effective connectivity during motor imagery. This is a preprocessed (bandpass filtered, downsampled to 200 Hz) BIDS version curated through MOABB.

Participants

10

Channels

60 (10-10)

Citations

93

HED

v8.4.0

Size

5.64 GB

Version

v1.0.3

Updated

Oct 8, 2026

EEG recordings from 30 healthy participants performing a left-hand grasping motor imagery task versus rest, cued by auditory stimuli, with simultaneous pupillometry. The dataset was recorded with a 32-channel BioSemi ActiveTwo system at 512 Hz across two runs of 25 trials per subject. It supports evaluating whether task-evoked pupil diameter changes can improve EEG-based motor imagery brain-computer interface classification.

Participants

30

Channels

32 (10-10)

Citations

36

HED

v8.4.0

Size

3.22 GB

Version

v1.0.2

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

The eldBETA dataset provides 64-channel EEG recordings from 100 elderly participants (aged 51-81) performing a 9-target SSVEP-based brain-computer interface speller task. Stimuli used joint frequency and phase modulation (JFPM) at 8-12 Hz in 0.5 Hz steps, with 7 blocks of 9 trials per participant. It serves as a benchmark for evaluating SSVEP-BCI decoding algorithms in an aging population.

Participants

100

Channels

64 (10-10)

Citations

28

HED

v8.4.0

Size

34.8 GB

Version

v1.0.4

Updated

Oct 8, 2026

This dataset contains 32-channel EEG recordings from 8 healthy participants performing a combined steady-state visual evoked potential (SSVEP) brain-computer interface task. Spatially overlapping arrow stimuli at a single location, flickering at distinct frequencies derived from an 85 Hz CRT refresh rate, encode four directions (up, down, left, right). Participants covertly attended to one direction per trial, and the data cover three stimulation and attention schemes across two experiments.

Participants

8

Channels

31 (10-10)

Citations

3

HED

v8.4.0

Size

5.30 GB

Version

v1.0.2

Updated

Aug 18, 2026

EEG recordings from nine end-users with central nervous system tissue damage (stroke or spinal cord injury) performing five cue-guided mental tasks: word association, mental subtraction, spatial navigation, right-hand motor imagery, and feet motor imagery. Data were recorded with 30 active EEG electrodes across two sessions per participant, on different days. The dataset supports brain-computer interface research on individually adapted imagery and binary classification of mental tasks.

Participants

9

Channels

30 (10-10)

Citations

78

HED

v8.4.0

Size

2.74 GB

Version

v1.0.2

Updated

Aug 18, 2026

EEG recordings from five healthy participants performing cued motor imagery (right hand versus foot) with 118 electrodes, originally published to demonstrate improved single-trial classification through feature combination and multiclass paradigms. The data were downsampled to 100 Hz and comprise 280 cued trials per subject, split into labeled training and unlabeled test sets. The dataset was part of BCI Competition III and is widely used for benchmarking BCI classification algorithms.

Participants

5

Channels

118 (10-05)

Citations

86

HED

v8.4.0

Size

735 MB

Version

v1.0.3

Updated

Aug 18, 2026

This dataset contains simultaneous scalp and ear-EEG recordings from six healthy right-handed participants performing cued left- and right-hand fist clenching (motor execution). It comprises 1114 trials recorded at 1000 Hz with a Neuroscan SynAmps2 amplifier. The data support evaluation of in-ear sensing for motor task classification and brain-computer interface research. This BIDS version was generated with MOABB from the original Zenodo deposit.

Participants

6

Channels

122 (10-05)

Citations

12

HED

v8.4.0

Size

18.4 GB

Version

v1.0.3

Updated

Aug 20, 2026

EEG recordings from 14 healthy, BCI-naive participants performing asynchronous voluntary index-finger tapping (right, left) and rest, originally reported by Wairagkar et al. (2018). Data were recorded at 1024 Hz from 19 scalp channels and preprocessed with filtering and ICA artifact removal. Trials are segmented around movement onset to study neural correlates of movement intention, and the dataset is distributed in BIDS format via MOABB.

Participants

14

Channels

19 (10-20)

Citations

10

HED

v8.4.0

Size

1.23 GB

Version

v1.0.2

Updated

Aug 18, 2026