Discover datasets

Participants

20

Channels

32 (10-10)

Citations

1

Size

7.75 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

The BNCI2003_IVa Motor Imagery dataset comprises EEG recordings from 5 healthy subjects performing motor imagery tasks (right hand and feet movements) in response to visual cues. This preprocessed dataset, originally from BCI Competition III, contains 280 trials per subject recorded with 118 EEG channels at 100 Hz sampling rate. The dataset has been extensively used for benchmarking brain-computer interface classification algorithms, particularly for evaluating common spatial patterns and feature combination methods.

Participants

5

Channels

118 (10-05)

Citations

86

HED

v8.4.0

Size

735 MB

Version

v1.0.3

Updated

Aug 18, 2026

The BNCI 2014-002 Motor Imagery dataset comprises EEG recordings from 14 healthy subjects performing two-class motor imagery tasks (right hand and feet imagination) in a cue-guided Graz-BCI paradigm. Data were acquired at 512 Hz using 15 EEG channels with online Butterworth filtering and Laplacian montage, yielding 160 trials per subject with continuous visual feedback. This minimally preprocessed dataset has been benchmarked for brain-computer interface applications using machine learning classifiers including random forests and regularized linear discriminant analysis.

Participants

14

Channels

15 (other)

Citations

89

HED

v8.4.0

Size

1.37 GB

Version

v1.0.4

Updated

Aug 18, 2026

This high-density EEG dataset comprises resting-state and task-based recordings from 23 healthy volunteers performing visual naming and spelling tasks. Collected between 2012-2013 at Rennes University Hospital using a 256-electrode EEG system, the dataset enables investigation of dynamic functional brain network reorganization during language production and cognitive processing. The study provides insights into spatiotemporal patterns of brain connectivity during object naming and orthographic tasks.

Participants

23

Channels

256 (egi-geodesic)

Size

90.4 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises scalp EEG recordings from 27 stroke patients performing a lower-limb motor imagery task as part of a multi-paradigm, longitudinal rehabilitation training protocol. Data were collected at Tianjin University to support research on motor-imagery brain-computer interfaces for gait and lower-limb rehabilitation after stroke. The dataset is organized in BIDS format with a single EEG task (task-imagery) across repeated sessions.

Participants

27

Channels

64 (10-10)

Citations

23

HED

v8.4.0

Size

56.7 GB

Version

v1.0.5

Updated

Aug 20, 2026

This dataset contains EEG recordings from human infants who viewed 200 object images presented in rapid visual streams, designed to investigate early visual object processing. The data support representational similarity analyses examining neural responses to rapid serial visual presentation of objects. Accompanying code enables reproduction of preprocessing, RSA, and figures from the associated publication.

Participants

42

Citations

8

Size

12.6 GB

Version

v1.0.0

Updated

Aug 19, 2026

This multimodal dataset comprises EEG, ECG, and pupillometry recordings from participants performing an n-back working memory task at four difficulty levels (1-back through 4-back). Data were collected using a combined mobile EEG+ECG system synchronized with a Pupil Labs eye tracker via Lab Streaming Layer, and converted from raw XDF recordings into BIDS format. The dataset is intended to support research on cognitive workload assessment across multiple physiological modalities.

Participants

18

Channels

19 (10-20)

Size

2.13 GB

Version

v1.0.0

Updated

Aug 19, 2026

T16 is an EEG neuroimaging dataset containing electroencephalography recordings organized according to the Brain Imaging Data Structure (BIDS) standard version 1.8.0. The dataset includes hierarchical event descriptors (HED) version 8.1.0 for detailed annotation of experimental events and conditions. The dataset comprises 185 files totaling 8.2 GB of EEG data with standardized metadata and event annotations to support reproducible neuroscience research.

Participants

14

Channels

64 (10-10)

HED

v8.1.0

Size

7.66 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset provides a BIDS-standardized version of simultaneously collected EEG and eye-tracking data from one subject, derived from the larger EEGEyeNet dataset. It supports research on eye movement prediction from electroencephalography and eye-tracking signals, following an established paradigm designed for benchmarking EEG-based eye movement decoding.

Participants

1

Channels

129 (egi-geodesic)

Citations

7

Size

43.6 MB

Version

v1.0.0

Updated

Aug 19, 2026