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An open-access EEG dataset containing recordings from 15 healthy Spanish-speaking subjects performing imagined speech tasks. The dataset comprises 11 imagery classes (5 Spanish vowels and 6 directional commands) acquired using 6-channel EEG at 1024 Hz with preprocessed data (bandpass filtered 2-45 Hz). This BIDS-reformatted derivative is based on the original data described in Pressel et al. 2016 and supports brain-computer interface research and motor imagery classification studies.

Participants

15

Channels

6 (10-20)

Citations

92

HED

v8.4.0

Size

2.00 GB

Version

v1.0.4

Updated

Aug 18, 2026

…In each task the goal was to learn cue-response mappings for…

Participants

12

Channels

31 (10-10)

Citations

4

Size

4.00 GB

Version

v1.0.0

Updated

Aug 19, 2026

…Tripathy K, Fogarty M, et al., "Mapping brain function in adults and…

Participants

5

Size

36.3 GB

Version

v1.0.0

Updated

Jul 10, 2026

VocalMind is a stereotactic EEG (sEEG) dataset comprising intracranial recordings from one participant performing vocalized, mimed, and imagined speech tasks in Mandarin Chinese, a tonal language. The dataset supports research on speech decoding, brain-computer interfaces, and neural mechanisms of overt and covert speech production. Raw recordings sampled at 1000 Hz were converted to BIDS iEEG format with event markers indicating stimulus onsets for each speech modality.

Participants

1

Citations

15

Size

1.89 GB

Version

v1.0.0

Updated

Jul 10, 2026

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on004774-blue…

Participants

14

Citations

1

Size

30.2 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains EEG recordings from 12 healthy human subjects performing three-class motor imagery tasks involving the same upper extremity: rest, imagined grasping, and imagined elbow flexion. Data were collected across four sessions per subject using a 32-channel EEG system, and the dataset is a BIDS-formatted derivative of the original study on classifying imaginary motor states using time-domain features. The dataset supports research in brain-computer interfaces (BCI) for motor rehabilitation applications.

Participants

12

Channels

32 (egi-geodesic)

Citations

44

HED

v8.4.0

Size

52.0 GB

Version

v1.0.3

Updated

Aug 20, 2026

…M., Carlson T.A. (2024). Mapping the Dynamics of Visual Feature Coding…

Participants

16

Citations

27

Size

69.6 GB

Version

v1.0.0

Updated

Jul 10, 2026

BIDS-EMG dataset - HDsEMG recordings of tibialis anterior during isometric contractions at 30% and 50% MVC, 6 subjects, 256-channel grids (MUniverse benchmark)

Participants

6

Size

448 MB

Version

v1.0.1

Updated

Jul 10, 2026

…type=gray arrow on black background, direction_mapping=downward=feet, leftward=left…

Participants

14

Channels

128 (10-05)

Citations

76

HED

v8.4.0

Size

31.3 GB

Version

v1.0.3

Updated

Aug 18, 2026

This dataset comprises 64-channel EEG recordings from 11 healthy participants performing an auditory P300-based brain-computer interface task using selective attention to multiple tone streams. Participants attended to one of three auditory streams of musical tones and counted target stimuli while P300 event-related potentials were recorded. Classification using Riemannian geometry achieved >80% accuracy for 5 subjects and >75% for 9 subjects, demonstrating the feasibility of multi-class auditory BCIs based on auditory stream segregation.

Participants

11

Channels

64 (10-10)

Citations

11

HED

v8.4.0

Size

6.31 GB

Version

v1.0.4

Updated

Aug 18, 2026