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A classical motor imagery EEG dataset comprising recordings from 7 healthy subjects performing left hand, right hand, and passive rest tasks. The dataset contains 19-channel EEG data sampled at 200 Hz with visual arrow cues guiding motor imagery tasks. This benchmark dataset is designed for evaluating brain-computer interface algorithms and motor imagery classification methods.

Participants

7

Channels

19 (10-20)

Citations

81

HED

v8.4.0

Size

1.20 GB

Version

v1.0.2

Updated

Aug 18, 2026

…independently ### Exclusion criteria: - History of stroke or major neurological disorder - Brain surgery…

Participants

144

Channels

65 (10-10)

Citations

4

Size

4.26 GB

Version

v1.0.0

Updated

Aug 18, 2026

64-ch EEG, 95 subjects, 2 sessions, 6 paradigms (13 tasks). BrainAmp 250Hz Easycap 64-ch. DOI:10.1016/j.neuroimage.2022.119666

Participants

95

Channels

64 (10-10)

Citations

28

Size

21.6 GB

Version

v1.0.0

Updated

Jul 10, 2026

…as dementia, Parkinson disease, or stroke); cardiovascular, oncological, and eye diseases; psychiatric…

Participants

608

Channels

64 (10-10)

Citations

21

Size

74.1 GB

Version

v1.0.0

Updated

Jul 10, 2026

VEPCON is a multimodal neuroimaging dataset comprising high-density EEG, structural MRI, and diffusion-weighted imaging from 20 participants performing visual discrimination tasks (face vs. scrambled faces, coherent vs. incoherent motion). The dataset includes preprocessed EEG single trials, individual brain parcellations at five spatial resolutions, structural connectomes derived from diffusion data, and EEG source imaging solutions based on individual anatomy. This resource supports multimodal methods development, structure-function relationship studies, and optimization of source imaging and graph analysis techniques.

Participants

20

Channels

128 (biosemi)

Citations

24

Size

58.2 GB

Version

v1.0.0

Updated

Jul 22, 2026

Brain Treebank is a large-scale intracranial EEG dataset comprising 43 hours of iEEG recordings from 10 epilepsy patients watching naturalistic Hollywood movies, with 1,688 electrodes sampled at 2048 Hz. The dataset includes time-aligned linguistic annotations with word-level transcripts and Universal Dependencies syntax trees, providing a unique resource for studying neural language processing during naturalistic stimulation.

Participants

10

Size

508 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises longitudinal motor imagery EEG recordings from 18 BCI-naive subjects across six sessions (one offline, five online), designed to study transfer learning and skill acquisition in brain-computer interfaces (BCIs). It compares two domain adaptation frameworks—Generic Recentering and Personally Assisted Recentering—for calibration-free BCI training using left/right hand motor imagery with visual feedback. Data were collected at 512 Hz with 22 EEG channels and analyzed using Riemannian geometry-based classifiers.

Participants

18

Channels

22 (10-10)

Citations

49

HED

v8.4.0

Size

14.4 GB

Version

v1.0.4

Updated

Aug 20, 2026

This dataset contains multimodal brain–machine interface (BMI) recordings from seven healthy adults who trained over nine longitudinal sessions to control a lower-limb exoskeleton via motor imagery. It includes 60-channel EEG, 4-channel EOG, dual IMU motion data, and exoskeleton control/feedback signals collected during open-loop calibration and closed-loop walk/stop trials. The dataset supports research on EEG-based decoding of motor imagery for neurorehabilitation and human-robot interaction applications.

Participants

7

Channels

60

Citations

2

Size

3.62 GB

Version

v1.0.0

Updated

Aug 18, 2026

This dataset contains EEG recordings from 20 healthy participants performing a 7-day longitudinal motor imagery brain-computer interface (BCI) task without feedback. Each subject completed 7 sessions of 6 runs, imagining left hand, right hand, feet, and rest movements, yielding 33,600 trials in total. The dataset was converted to BIDS format from the original study by Zhou et al. (2021) examining the relationship between relative power and motor imagery decoding performance across time and subjects.

Participants

20

Channels

41 (other)

Citations

15

HED

v8.4.0

Size

93.1 GB

Version

v1.0.3

Updated

Aug 20, 2026

This dataset comprises EEG and biomechanical recordings from fifteen healthy young adults who walked on a treadmill at four different speeds (0.4, 0.8, 1.2, and 1.6 m/s) and while standing stationary, viewing a static projected scene through liquid crystal lenses that generated intermittent visual occlusions. The study aimed to characterize neurophysiological responses to visual occlusion during walking at varying gait speeds using 120-channel EEG, EMG, ground reaction force, and IMU data. This resource supports research into visual-motor integration and cortical dynamics of gait.

Participants

15

Channels

120 (other)

Size

3.31 GB

Version

v1.0.0

Updated

Aug 18, 2026