Discover datasets

A classical motor imagery EEG dataset comprising recordings from 7 healthy subjects performing left hand, right hand, and passive rest tasks. The dataset contains 19-channel EEG data sampled at 200 Hz with visual arrow cues guiding motor imagery tasks. This benchmark dataset is designed for evaluating brain-computer interface algorithms and motor imagery classification methods.

Participants

7

Channels

19 (10-20)

Citations

81

HED

v8.4.0

Size

1.20 GB

Version

v1.0.2

Updated

Aug 18, 2026

…CSP, DFT, Bandpower - **Frequency bands**: alpha=[6, 14] Hz; beta=[14, 40…

Participants

14

Channels

15 (other)

Citations

89

HED

v8.4.0

Size

1.37 GB

Version

v1.0.4

Updated

Aug 18, 2026

The MNE-Sample-Data dataset comprises simultaneous MEG and EEG recordings acquired from a single subject using a Neuromag Vectorview system at the Martinos Center for Biomedical Imaging. The experiment involved visual stimulation (checkerboard patterns presented to left and right visual fields) and auditory stimulation (tones to left and right ears), with occasional face stimuli requiring motor responses. Structural MRI data from a 1.5 T Siemens scanner and Freesurfer-derived anatomical derivatives are included, providing a comprehensive reference dataset for MEG/EEG analysis and method development.

Participants

2

Size

1.93 GB

Version

v1.0.0

Updated

Jul 10, 2026

…Covariance/Riemannian, ICA - **Frequency bands**: alpha=[8.0, 13.0] Hz; theta…

Participants

15

Citations

61

HED

v8.4.0

Size

1.22 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset contains resting-state EEG recordings collected using a 128-channel Amps 300 amplifier at the University of Oklahoma, alongside structural MRI scans acquired from the same participants. The data support investigation of whole-brain electrophysiological functional connectivity dynamics during resting-state conditions.

Participants

34

Channels

128 (other)

Size

3.00 GB

Version

v1.0.0

Updated

Aug 19, 2026

The BCIAUT-P300 dataset comprises EEG recordings from 15 individuals with autism spectrum disorder (ASD) participating in a P300-based brain-computer interface (BCI) study focused on joint-attention training in a virtual environment. Data were collected across 7 sessions using 8 EEG channels sampled at 250 Hz, with visual stimuli presented as flashing objects. This multi-session, multi-subject benchmark dataset enables evaluation of P300 detection algorithms and BCI performance in the clinical ASD population.

Participants

15

Channels

8 (10-10)

Citations

67

HED

v8.4.0

Size

9.33 GB

Version

v1.0.2

Updated

Aug 18, 2026

…Riemannian, AR, ICA - **Frequency bands**: alpha=[8.0, 12.0] Hz; mu…

Participants

8

Channels

16 (10-20)

HED

v8.4.0

Size

232 MB

Version

v1.0.2

Updated

Aug 18, 2026

Imported from OpenNeuro ds003343

Participants

20

Channels

16 (10-10)

Citations

1

Size

663 MB

Version

v1.0.0

Updated

Jul 10, 2026

…Feature extraction**: ERSP - **Frequency bands**: alpha=[8.0, 13.0] Hz; beta…

Participants

18

Channels

62 (10-10)

Citations

4

HED

v8.4.0

Size

50.0 GB

Version

v1.0.2

Updated

Aug 18, 2026

64-ch EEG, 95 subjects, 2 sessions, 6 paradigms (13 tasks). BrainAmp 250Hz Easycap 64-ch. DOI:10.1016/j.neuroimage.2022.119666

Participants

95

Channels

64 (10-10)

Citations

28

Size

21.6 GB

Version

v1.0.0

Updated

Jul 10, 2026