Discover datasets

A multimodal mobile brain/body imaging dataset from 32 young adults walking over uneven terrain at different speeds. It includes high-density dual-layer EEG, neck EMG, IMU acceleration, ground reaction forces, and head models built from T1-weighted MR images. Each participant also completed a seated rest trial, and digitized electrode locations are provided for every subject.

Participants

32

Channels

120 (other)

Size

62.5 GB

Version

v1.0.0

Updated

Jun 25, 2026

EEG dataset from a visual working memory experiment in which participants judged whether a probe grating was rotated clockwise or counterclockwise relative to a memorized orientation. Color cues either predicted a 90° segment of possible orientations or gave no information about orientation. The dataset supports investigation of how diffuse predictions stabilize and reshape neural codes during memory encoding.

Participants

47

Channels

66 (10-10)

Size

145 GB

Version

v1.0.0

Updated

Jul 2, 2026

…two eyes-open (EO) runs and two eyes-closed (EC) runs. Conditions…

Participants

43

Channels

128 (biosemi)

Size

38.2 GB

Version

v1.0.0

Updated

Jun 30, 2026

…RESTING CALIBRATION (eyes-open / eyes-closed) — IMPORTANT NOTE ------------------------------------------------------------- The eyes-open and…

Participants

30

Channels

14 (10-10)

Size

23.4 MB

Version

v1.0.0

Updated

Jun 30, 2026

…minimize artifacts by reducing eye blinks and movements. - **Stimulus presentation**: display=22…

Participants

11

Channels

14 (10-10)

Citations

35

HED

v8.4.0

Size

277 MB

Version

v1.0.3

Updated

Oct 8, 2026

HAD-MEEG is a magnetoencephalography (MEG) and electroencephalography (EEG) dataset on human action recognition. It extends the Human Action Dataset fMRI resource (HAD-fMRI) and was recorded in the same 30 participants with the same stimuli, 21,600 video clips spanning 180 categories of human action. The millisecond temporal resolution of M/EEG complements the spatial precision of fMRI, enabling spatiotemporal study of the neural mechanisms of action recognition.

Participants

32

Channels

62 (10-10)

Size

221 GB

Version

v1.0.0

Updated

Jun 30, 2026

NOD-EEG is an electroencephalography dataset of human responses to naturalistic ImageNet object images. It extends the Natural Object Dataset-fMRI (NOD-fMRI) by recording EEG, and MEG in a companion dataset, from the same subjects viewing the same stimuli. Together the three modalities support study of object recognition with both high spatial and high temporal resolution. The dataset includes raw BIDS data, preprocessed continuous data, epoched data, and detailed trial-level metadata.

Participants

19

Channels

62 (10-10)

Citations

5

Size

24.3 GB

Version

v1.0.0

Updated

Jun 28, 2026

…Minimize eye movements and muscle artifacts. Count targets during calibration. Spell sentences…

Participants

10

Channels

63 (10-10)

Citations

84

HED

v8.4.0

Size

7.62 GB

Version

v1.0.3

Updated

Oct 8, 2026

…Motion artifacts from eye/head movements were also recorded. Signal processing included…

Participants

29

Channels

30 (10-05)

Citations

95

HED

v8.4.0

Size

6.50 GB

Version

v1.0.3

Updated

Aug 18, 2026

EEG recordings from four participants performing motor imagery of the left hand, right hand, and feet, originally reported by Zhou et al. (2016) in a study on automated trial selection for motor imagery brain-computer interfaces. Each participant completed three sessions of two runs, giving 450 trials per subject. Data were recorded from 14 channels at 250 Hz and reformatted into BIDS from a MOABB-generated Zenodo version.

Participants

4

Channels

14 (10-10)

Citations

87

Size

152 MB

Version

v1.0.0

Updated

Mar 3, 2026