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…The large sample, multimodal imaging, contextual diversity, and behavioural follow-ups enable…

Participants

65

Channels

64 (10-10)

Size

936 GB

Version

v1.0.0

Updated

Jun 21, 2026

NEMAR Dataset nm000105: discrete_gestures - Discrete hand gesture detection from EMG

Participants

100

Size

20.6 GB

Version

v2.0.0

Updated

Feb 23, 2026

This dataset contains MEG recordings, with eye-tracking data acquired alongside, from healthy adults performing a cross-modal cue-target discrimination task. Participants were cued to prepare for an auditory or visual target. During a 3-second waiting interval, a 36 Hz frequency-tagged visual stimulus and a 40 Hz amplitude-modulated tone were presented. Targets appeared alone in one block and alongside a distractor from the other modality in the other block. The data were collected to study alpha oscillations and inhibition of early sensory processing during target preparation.

Participants

27

Citations

1

Size

132 GB

Version

v1.0.0

Updated

Jun 30, 2026

This dataset contains 62-channel EEG recordings from 18 healthy, right-handed participants performing motor imagery of eight multi-joint movements of the unilateral upper limb. The movements involve the hand, wrist, elbow and shoulder. Each participant completed 320 cue-based trials across 8 blocks, with 40 trials per class. The data support research on brain-computer interfaces for motor rehabilitation.

Participants

18

Channels

62 (10-10)

Citations

6

HED

v8.4.0

Size

50.0 GB

Version

v1.0.2

Updated

Aug 18, 2026

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on003380-blue…

Participants

12

Size

1.43 GB

Version

v1.0.0

Updated

May 13, 2026

This dataset contains EEG recordings from motor imagery (left- and right-hand) tasks collected in different recording environments. The main dataset covers 84 healthy participants in a shielded laboratory and a simulated hospital environment, and is intended to study how environmental variability affects EEG-based brain-computer interface performance. A small supplementary dataset from 3 participants recorded in a space station environment extends the collection to a non-terrestrial, microgravity setting. Multiple paradigms are included: Graz, SSMVEP-MI, and hybrid video conditions.

Participants

84

Channels

69 (10-10)

Size

144 GB

Version

v1.0.0

Updated

Jun 30, 2026

EEG, galvanic skin response (GSR) and electrocardiogram (ECG) recordings from healthy adult volunteers listening to 40-s synthetic music clips designed to target specific affective states defined by valence and arousal. The data were collected to calibrate an affective brain-computer music interface that induces target emotional states through real-time modification of generated music. Each session comprised 5 runs of 18 music trials, and self-reported valence and arousal ratings are included. This is the calibration dataset of three related datasets from the BCMI-MIdAS project.

Participants

19

Channels

32 (10-10)

Size

6.10 GB

Version

v1.0.0

Updated

Jun 21, 2026

Alljoined-1.6M is a large-scale EEG dataset of neural responses to rapid serial visual presentation of natural images from the THINGS database. It was recorded with a consumer-grade 32-channel EMOTIV FLEX2 system in 20 adult participants over four sessions each, yielding more than 1.6 million trials. The dataset was built to test whether deep-learning-based brain-computer interface and semantic decoding research can be done with affordable EEG hardware.

Participants

20

Channels

32 (10-10)

Size

8.78 GB

Version

v1.0.3

Updated

Sep 23, 2026

EEG recordings from five participants with speech and/or physical impairments due to amyotrophic lateral sclerosis (ALS) who used a non-implantable communication brain-computer interface (cBCI) over multiple visits. Participants completed calibration and copy-spelling tasks with Matrix and RSVP layouts, in both customized and non-customized system configurations. Customization was iteratively adjusted based on typing performance, preferences, clinical observations, brain signal characteristics, and offline simulations. The data are organized in BIDS format.

Participants

5

Channels

7 (10-10)

Size

2.17 GB

Version

v1.0.0

Updated

Jun 19, 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