Discover datasets

This dataset (WBCIC-SHU) contains multi-day EEG recordings from 51 healthy, right-handed, BCI-naive subjects performing a motor imagery brain-computer interface paradigm across three sessions per subject. Participants imagined left-hand, right-hand, or (for a subset of 11 subjects) foot movements in response to visual and auditory cues, yielding 39,600 trials in total. The dataset is intended for benchmarking motor imagery classification algorithms such as CSP, FBCSP, EEGNet, deepConvNet, and FBCNet, and was converted to BIDS format using MOABB.

Participants

51

Channels

59 (10-10)

Citations

34

HED

v8.4.0

Size

154 GB

Version

v1.0.5

Updated

Aug 18, 2026

…system as for the EMG recordings. ### Coordinate systems All electrode coordinates (reported…

Participants

16

Size

5.51 GB

Version

v1.0.1

Updated

Jul 10, 2026

…EGI 300 Geodesic EEG System (GES 300) - **Software**: Microsoft Visual Studio 2010…

Participants

11

Channels

14 (10-10)

Citations

39

HED

v8.4.0

Size

277 MB

Version

v1.0.2

Updated

Aug 18, 2026

…coordinates are provided when available. * Recordings done with the Blackrock system are…

Participants

58

Citations

2

Size

107 GB

Version

v1.0.0

Updated

Jul 22, 2026

This dataset comprises electroencephalographic recordings from 21 healthy subjects performing a visual P300-based brain-computer interface task in two environments: a personal computer and a virtual reality headset. The study compares BCI performance and user experience across these modalities using a 6×6 matrix speller paradigm with 16-channel EEG recordings at 512 Hz sampling rate. The experiment was conducted at GIPSA-lab in 2018 and includes both physiological and subjective outcome measures.

Participants

21

Channels

16 (10-10)

Citations

5

HED

v8.4.0

Size

999 MB

Version

v1.0.4

Updated

Aug 18, 2026

…These HPI coordinates have been acquired from the neuronavigation system brainsight (https…

Participants

22

Size

168 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset contains somatosensory MEG recordings converted to BIDS format, including raw MEG data, anatomical MRI scans, and FreeSurfer-derived structural derivatives. The dataset includes forward models and boundary element models computed using MNE-BIDS, providing a complete neuroimaging resource for studying somatosensory processing and demonstrating MEG-MRI integration workflows.

Participants

1

Citations

1

Size

726 MB

Version

v1.0.0

Updated

Jul 10, 2026

…IEEE Transactions on Neural Systems and Rehabilitation Engineering, 25(10), pp.1735…

Participants

29

Channels

30 (10-05)

Citations

94

HED

v8.4.0

Size

6.62 GB

Version

v1.0.3

Updated

Aug 18, 2026

…1916 (1900 gesture prompts + 16 stage boundaries) ### Coordinate System **Single coordinate system…

Participants

100

Size

20.6 GB

Version

v2.0.0

Updated

Jul 10, 2026

TNO (Task-Negative Oscillations) is an EEG dataset containing resting-state and task-based electroencephalography recordings. The dataset includes EEG data collected during cognitive tasks and resting-state conditions, organized in BIDS format with data files in EEGLAB format (.set/.fdt files) and accompanying metadata in BIDS-compatible formats (JSON, TSV). This dataset is designed to investigate neural oscillations and their relationship to task engagement and cognitive processing. The dataset comprises recordings from multiple subjects performing standardized cognitive tasks and resting-state sessions, with complete event annotations and electrode location information.

Participants

21

Channels

32 (10-10)

HED

v8.1.0

Size

7.25 GB

Version

v1.0.0

Updated

Jul 10, 2026