Discover datasets

A single-pulse transcranial magnetic stimulation (TMS) combined with electroencephalography (EEG) dataset acquired in open-loop configuration. This dataset provides concurrent TMS-EEG recordings suitable for investigating cortical responses to magnetic stimulation and characterizing brain reactivity to non-invasive neuromodulation. The dataset comprises recordings from multiple subjects across multiple sessions with concurrent TMS-EEG acquisition.

Participants

20

Channels

30 (10-10)

Size

39.4 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset contains 62-channel EEG recordings from 25 healthy, right-handed subjects performing kinesthetic motor imagery of the right hand versus right elbow, a within-limb discrimination paradigm. Each subject completed 15 sessions over 3 days, yielding 600 trials total, designed to study brain-computer interface (BCI) decoding of different joint movements from the same limb. The dataset supports research into motor rehabilitation and prosthetic control applications using EEG-based BCI systems.

Participants

25

Channels

62 (10-10)

Citations

52

HED

v8.4.0

Size

53.8 GB

Version

v1.0.2

Updated

Aug 18, 2026

This dataset comprises simultaneous EEG and eye-tracking recordings from 21 participants performing a matrix-based brain-computer interface (BCI) typing task using a single-character-presentation paradigm. Data were collected at Northeastern University in 2023 using the BciPy software platform, including calibration and copy-spelling sessions with event markers for target and non-target stimuli. The dataset supports research on multimodal sensor fusion for EEG-based BCI typing systems.

Participants

21

Channels

19 (10-20)

Size

616 MB

Version

v1.0.0

Updated

Aug 19, 2026

An EEG dataset of imagined speech from 15 healthy participants comparing traditional cue-based and gamified paradigm designs for brain-computer interface applications. The dataset comprises 1,800 trials of four Spanish directional commands recorded at 500 Hz from 24 electrodes using the mBrainTrain Smarting system. This derivative dataset enables systematic evaluation of paradigm design effects on imagined speech decoding performance.

Participants

15

Channels

24 (10-10)

Citations

1

HED

v8.4.0

Size

1.52 GB

Version

v1.0.3

Updated

Aug 18, 2026

This dataset contains preprocessed EEG recordings from 6 healthy participants performing imagined speech tasks with three short word conditions (out, in, up). Data were acquired at 256 Hz using 64 channels and analyzed using Riemannian manifold methods and relevance vector machines for brain-computer interface applications. The motor imagery paradigm employed auditory and visual cueing, yielding 5,400 trials suitable for BCI research and benchmarking.

Participants

6

Channels

60 (10-10)

Citations

98

HED

v8.4.0

Size

1.90 GB

Version

v1.0.3

Updated

Aug 18, 2026

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

Participants

100

Size

20.6 GB

Version

v2.0.0

Updated

Jul 10, 2026

Chisco-2.0 is an imagined speech EEG dataset comprising raw EDF recordings from two participants (sub-01 and sub-02). It is intended to support research into decoding imagined speech from electroencephalographic signals, providing a resource for brain-computer interface and speech neuroscience studies.

Participants

2

Channels

124 (10-05)

Size

52.9 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises simultaneous 64-channel EEG and 3T fMRI recordings from 16 subjects performing motor imagery and neurofeedback tasks. Participants were randomly assigned to receive either mono-dimensional or bi-dimensional neurofeedback displays during five experimental runs with alternating rest and task blocks. The dataset includes raw EEG data in Brain Vision format, preprocessed EEG data, BOLD fMRI acquisitions, computed neurofeedback scores from both modalities (EEG and fMRI), and event timing files, providing a comprehensive resource for multimodal neuroimaging data integration studies.

Participants

17

Size

25.9 GB

Version

v1.0.0

Updated

Jul 10, 2026

Imported from OpenNeuro ds004018

Participants

16

Citations

98

Size

10.5 GB

Version

v1.0.0

Updated

Jul 10, 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