Discover datasets

A high-density 124-channel EEG dataset comprising event-related potentials (ERPs) from 10 healthy participants during a visual object recognition task. Participants viewed 5,184 photographs from six object categories (human body, human face, animal body, animal face, fruit/vegetable, and inanimate objects), with 72 photographs per category, presented for 500 ms each. The dataset is suitable for investigating neural representations of object categories through single-trial EEG classification and representational similarity analysis.

Participants

10

Channels

124 (egi-geodesic)

Citations

93

HED

v8.4.0

Size

3.40 GB

Version

v1.0.3

Updated

Aug 18, 2026

Beetl2021-A is a preprocessed motor imagery EEG dataset derived from the BEETL Competition 2021 (NeurIPS Task 2), comprising 63-channel, 500 Hz recordings from healthy subjects performing a four-class motor imagery task (rest, left hand, right hand, feet) during an online BCI racing game (Cybathlon2020IC). The dataset was designed to benchmark transfer learning and domain adaptation methods for subject-independent, cross-dataset EEG-based brain-computer interfacing.

Participants

3

Channels

63 (10-10)

Citations

2

HED

v8.4.0

Size

2.17 GB

Version

v1.0.6

Updated

Aug 20, 2026

This dataset comprises resting-state transcranial magnetic stimulation (TMS) combined with electroencephalography (EEG) recordings from multiple subjects. The study focuses on identifying site- and stimulation-specific TMS-evoked EEG potentials using quantitative cosine similarity metrics to characterize the electrophysiological responses to TMS across different brain regions.

Participants

20

Channels

30 (10-10)

Size

44.5 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises electroencephalography (EEG) recordings from 50 acute stroke patients (1-30 days post-stroke) performing motor imagery tasks of left- and right-handed hand-grip movements. Recorded using a wireless 29-channel EEG system at 500 Hz, the dataset includes raw and preprocessed data, representing the first open resource addressing left- and right-handed motor imagery in the acute stroke population. The dataset supports brain-computer interface (BCI) algorithm development and clinical rehabilitation applications.

Participants

50

Channels

29 (10-10)

Citations

78

HED

v8.4.0

Size

1.15 GB

Version

v1.0.3

Updated

Aug 18, 2026

This dataset is a mirror of OpenNeuro ds002791, containing EEG recordings and associated metadata. The dataset includes raw EEG data in standard formats (.eeg, .vhdr, .vmrk) along with BIDS-compliant documentation and participant information in TSV format.

Participants

23

Channels

256 (egi-geodesic)

Citations

4

Size

47.1 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises high-density electroencephalography (EEG) recordings acquired during a visual stimulation task from human participants. Data were collected in a single session and organized according to the EEG-BIDS specification, with raw recordings stored in BrainVision format. The dataset provides raw, unfiltered EEG signals suitable for subsequent offline preprocessing and analysis of visual evoked responses.

Participants

31

Channels

64

Citations

1

Size

17.6 GB

Version

v1.0.0

Updated

Aug 19, 2026

EEG dataset containing recordings from multiple subjects. This dataset is mirrored on NEMAR from OpenNeuro (ds002833) and contains raw EEG data in BIDS format.

Participants

20

Channels

257 (egi-geodesic)

Citations

4

Size

39.8 GB

Version

v1.0.0

Updated

Jul 10, 2026

A comprehensive EEG database containing electroencephalographic signals from 87 healthy participants performing motor imagery brain-computer interface tasks. The dataset comprises over 20,800 trials (~70 hours of recording) organized into three datasets (A, B, C) using a standardized Graz protocol for right and left hand motor imagery. In addition to raw EEG signals, the database includes detailed participant demographics, personality profiles, cognitive traits, and BCI performance metrics, enabling research on user-performance relationships, cross-user machine learning algorithms, and profile-informed signal classification.

Participants

87

Channels

27 (10-10)

Citations

38

HED

v8.4.0

Size

15.8 GB

Version

v1.0.4

Updated

Aug 18, 2026

A multi-session EEG dataset acquired from 15 healthy participants performing resting state and graded cognitive tasks (MATB-II at three difficulty levels). The dataset comprises 62-channel EEG recordings at 500 Hz sampling rate designed for passive brain-computer interface applications and mental workload estimation in neuroergonomic contexts. Raw EEG data are provided with standardized event annotations using HED 8.4.0 schema and MOABB-compatible feature extraction pipelines (bandpower analysis and Riemannian covariance methods) for benchmarking purposes.

Participants

15

Citations

61

HED

v8.4.0

Size

1.22 GB

Version

v1.0.0

Updated

Jul 10, 2026

Imported from OpenNeuro ds004362

Participants

109

Channels

64 (10-10)

Citations

99

HED

v8.1.0

Size

11.1 GB

Version

v1.0.0

Updated

Jul 10, 2026