Discover datasets

THINGS-EEG2 is a large EEG dataset from 10 participants who viewed 16,540 training images and 200 repeatedly presented test images from the THINGS database. Images were shown in rapid serial visual presentation at 5 Hz while 63-channel EEG was recorded at 1000 Hz across four sessions per subject. The dataset supports modeling of human visual object recognition and includes resting-state recordings, the authors' preprocessed epochs, and stimulus images.

Participants

10

Channels

63 (10-10)

Citations

88

Size

241 GB

Version

v1.1.0

Updated

Jul 5, 2026

…noise, and then a Morlet wavelet transformation (wavenumber = 5) is applied to…

Participants

18

Size

34.7 GB

Version

v1.0.0

Updated

Jun 27, 2026

Raw 128-channel EEG data from 20 observers viewing object images in a rapid presentation paradigm, together with representational dissimilarity matrices. The dataset supports time-resolved neural decoding analyses that separate objects' contextual associations from their perceptual and conceptual attributes. One participant was excluded because of a technical recording error, leaving 19 usable participants.

Participants

19

Citations

2

Size

18.9 GB

Version

v1.0.0

Updated

Jun 17, 2026

…noise, and then a Morlet wavelet transformation (wavenumber = 5) is applied to…

Participants

9

Size

12.2 GB

Version

v1.0.0

Updated

Jun 27, 2026

…P300 latency jitter, brain-computer interface, covert attention, wavelet analysis, single epoch…

Participants

10

Channels

16 (10-10)

Citations

85

HED

v8.4.0

Size

247 MB

Version

v1.0.3

Updated

Oct 8, 2026

EEG dataset investigating whether images of stylized (cartoon-like) faces with exaggerated visual features improve event-related potential (ERP) correlates of emotion relative to ordinary human faces. The stylized faces elicit an enhanced N170 component associated with facial recognition encoding. The findings suggest that consistent stimulus transformations could improve affect detection from EEG in affective brain-computer interface design.

Participants

26

Channels

28 (10-10)

Citations

1

Size

2.46 GB

Version

v1.0.0

Updated

Jun 24, 2026

…phase-locking value and relative entropy in delta 0.5-4, theta…

Participants

148

Size

3.90 GB

Version

v1.0.0

Updated

Oct 13, 2026

ODE is an EEG dataset formatted according to BIDS with HED annotations, contributed by Johnson, Gordon, Touryan, and King. The available documentation describes it only as a placeholder dataset, so no further details on content or purpose are provided.

Participants

1

Channels

64 (10-10)

HED

v8.1.0

Size

79.2 MB

Version

v1.0.0

Updated

May 13, 2026

…120 Hz line noise; Morlet wavelet power; retrieval epochs from 4 s…

Participants

7

Size

3.98 GB

Version

v1.0.0

Updated

Oct 8, 2026

Preprocessed 64-channel EEG recordings from 6 healthy participants performing imagined speech of three short words (out, in, up), cued by auditory and visual stimuli. The dataset contains 1800 trials of a single session, analyzed in the source study with Riemannian manifold covariance features and relevance vector machines for brain-computer interface applications. It is re-hosted in BIDS format from the MOABB benchmark collection.

Participants

6

Channels

60 (10-10)

Citations

99

HED

v8.4.0

Size

1.90 GB

Version

v1.0.3

Updated

Aug 18, 2026