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HAD-MEEG is a magnetoencephalography (MEG) and electroencephalography (EEG) dataset recorded from 30 participants viewing 21,600 video clips spanning 180 categories of human action, extending the previously released Human Action Dataset (HAD) fMRI resource. It was collected in the same participants and with the same stimuli as HAD-fMRI to enable combined spatiotemporal investigation of neural mechanisms underlying human action recognition. The dataset leverages the millisecond-level temporal resolution of M/EEG to complement the spatial precision of fMRI.

Participants

32

Channels

62 (10-10)

Citations

5

Size

221 GB

Version

v1.0.0

Updated

Aug 18, 2026

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on004448-blue…

Participants

56

Channels

129 (egi-geodesic)

Citations

8

Size

38.2 GB

Version

v1.0.0

Updated

Jul 10, 2026

BCIComp2020UpperLimb is a preprocessed EEG dataset from BCI Competition 2020 Track 4 containing motor imagery recordings of three grasping tasks (cylindrical, spherical, lumbrical) from 15 healthy subjects across three sessions. The dataset comprises 60-channel EEG data sampled at 250 Hz with 450 trials per subject (150 trials per session across 3 sessions), designed to evaluate session-to-session transfer learning in brain-computer interface applications. Data were preprocessed with 60 Hz notch filtering and cue-aligned epoching, with the 4-second motor imagery window extracted for analysis.

Participants

14

Channels

60 (10-10)

Citations

73

HED

v8.4.0

Size

2.76 GB

Version

v1.0.3

Updated

Aug 18, 2026

…Alertness and movement were monitored via camera during recording. ------------------------------------------------------------------------ ## Acquisition ### MEG MEG…

Participants

58

Citations

29

Size

445 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises EEG recordings from 15 healthy participants performing a visual P300 oddball task during treadmill walking at 1.6 m/s. The study includes simultaneous scalp-EEG (46 channels), ear-EEG (14 channels), electrooculography (4 channels), and inertial measurement unit recordings (6 channels) sampled at 100 Hz. The dataset was collected as part of BCI Competition 2020 Track 5 to evaluate brain-computer interface performance under ambulatory conditions. This is a BIDS-formatted derivative dataset converted from the original data using the MOABB (Mother of All BCI Benchmarks) pipeline.

Participants

15

Channels

46 (10-10)

Citations

71

HED

v8.4.0

Size

224 MB

Version

v1.0.3

Updated

Aug 18, 2026

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on005486-blue…

Participants

159

Citations

6

Size

371 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises EEG recordings collected using a Visual Attribute-Specific Contextual Trajectory Paradigm, designed to investigate visual attention and perceptual processing of moving stimuli. It provides raw electrophysiological data intended to support research into contextual and attribute-specific visual trajectory processing in humans.

Participants

35

Citations

1

Size

11.4 GB

Version

v1.0.0

Updated

Aug 19, 2026

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on006269-blue…

Participants

24

Channels

32

Citations

18

Size

107 GB

Version

v1.0.0

Updated

Aug 19, 2026

…Participants were instructed to maintain fixation and read attentively while minimizing movement…

Participants

50

Citations

29

Size

299 GB

Version

v1.0.0

Updated

Jul 10, 2026

Participants

4

Channels

14 (10-10)

Citations

82

Size

152 MB

Version

v1.0.0

Updated

Jul 10, 2026