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This dataset contains scalp EEG recordings from 22 participants who played BrainForm, a gamified P300 event-related potential brain-computer interface built for scalable data collection with consumer hardware and a minimal setup. Participants completed repeated runs of a P300 spelling/selection task at two task complexities. The data support study of BCI skill acquisition across sessions and of how different visual stimulation textures affect perception and performance.

Participants

22

Channels

8 (10-10)

HED

v8.4.0

Size

237 MB

Version

v1.0.6

Updated

Aug 20, 2026

…oddball | | N170 | N170 | Face perception (faces, cars, scrambled) | | N2pc | N2pc | Visual search…

Participants

40

Channels

30 (10-10)

Citations

162

HED

v8.4.0

Size

17.5 GB

Version

v1.1.1

Updated

Apr 4, 2026

Stereo-EEG recordings from six adult male patients with drug-resistant epilepsy performing a visual awareness task with saccadic report. Near-threshold Gabor gratings were presented while patients reported perception via saccade direction, enabling study of prefrontal cortex involvement in the emergence of visual awareness. The dataset includes per-trial behaviour, defaced T1 MRI, and source data with post-implantation CT and eye-position/behaviour files from patients and 10 healthy controls.

Participants

6

Size

37.9 GB

Version

v1.0.0

Updated

Oct 8, 2026

…The reference images consisted of color photographs of faces. Both the ID…

Participants

27

Channels

256 (biosemi)

Citations

25

HED

v8.0.0

Size

67.6 GB

Version

v1.0.0

Updated

Jun 23, 2026

This dataset contains EEG, physiological, and behavioural recordings collected in 2020 from 44 healthy adults aged 21-40. It includes eyes-closed resting-state recordings and two tasks: a spontaneous deception task (a gambling game with self-reported dice-roll predictions) and a cognitive control task battery. The battery covers processing speed, response selection, response inhibition, and conflict resolution.

Participants

45

Channels

139 (other)

Size

202 GB

Version

v1.0.0

Updated

Jun 24, 2026

The Finer-grained Affective Computing EEG Dataset (FACED) contains 32-channel scalp EEG from 123 healthy participants who watched 28 emotion-eliciting video clips targeting nine emotion categories (four negative, four positive, and neutral). Participants gave self-reported ratings on 12 dimensions, including discrete emotions, valence, arousal, liking, and familiarity. The dataset supports cross-subject affective computing and the development of EEG-based emotion recognition algorithms. This version is converted to BIDS with events annotated by video and emotion labels.

Participants

123

Channels

32 (10-10)

Citations

94

Size

31.4 GB

Version

v1.1.3

Updated

May 29, 2026

This dataset contains EEG recordings collected while participants viewed visual and audiovisual stimuli in virtual reality depicting the Edzna Archaeological Site. It is intended to support research on how immersive, multisensory cultural-heritage environments shape brain activity. The data are organized in BIDS format with HED annotations.

Participants

102

Channels

8 (10-10)

Size

634 MB

Version

v1.0.0

Updated

May 13, 2026

This dataset contains simultaneous EEG and facial EMG recordings examining symmetry perception and associated affective responses. Participants viewed visual patterns and, after stimulus offset, reported whether each pattern was regular (symmetric) or random. It supports investigation of neural and psychophysiological correlates of the processing of visual symmetry.

Participants

24

Channels

64 (other)

Citations

94

Size

2.69 GB

Version

v1.0.0

Updated

Jun 24, 2026

EEG dataset investigating anticipatory neural differences between attention and expectation. The recordings were collected by a research group led by Maria Ruz and are organized in BIDS format. The dataset is mirrored on NEMAR from OpenNeuro (ds004502).

Participants

48

Channels

65 (10-10)

Size

59.4 GB

Version

v1.0.0

Updated

Jun 24, 2026

This dataset contains EEG recordings from 34 participants (one session each) who viewed 242 object images, 121 challenge and 121 control images, selected from comparisons between human behavioural performance and AlexNet. The study examines adaptive recruitment of cortex-wide recurrent processing during visual object recognition. The derivatives folder contains outputs of the decoding analyses, including time-resolved decoding accuracy matrices for object identity (.npz).

Participants

34

Channels

63 (10-10)

Citations

2

Size

61.2 GB

Version

v1.0.0

Updated

Jun 30, 2026