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BigP3BCI Study S2 is a P300-based brain-computer interface dataset comprising EEG recordings from 24 healthy subjects performing a 9x8 house/tool visual speller paradigm. This derivative dataset, part of the larger bigP3BCI collection, contains standardized EEG data acquired at 256 Hz from 32 channels using g.USBamp hardware. The dataset is designed for machine learning applications and BCI research, with target and non-target event classifications annotated using HED 8.4.0 standards.

Participants

24

Size

1.11 GB

Version

v1.0.1

Updated

Jun 3, 2026

This dataset comprises 64-channel EEG recordings from 62 participants (31 pairs) engaged in a computerized Rock-Paper-Scissors game consisting of 480 competitive trials. The study investigates neural mechanisms underlying competitive decision-making through multivariate decoding approaches, with recordings lasting approximately one hour per session. The dataset supports investigation of brain activity patterns associated with strategic gameplay and interpersonal competition.

Participants

31

Size

78.0 GB

Version

v1.0.0

Updated

Jun 29, 2026

BigP3BCI Study Q is a P300-based brain-computer interface dataset comprising EEG recordings from 36 ALS subjects across 3 sessions each, using a 6x6 color intensification speller paradigm. The dataset contains 32-channel EEG data sampled at 256 Hz with standardized 10-20 electrode montage, annotated with target and non-target event labels for machine learning applications. This derivative dataset is part of the larger BigP3BCI collection, the largest public P300 BCI dataset with recordings from approximately 267 subjects across 20 studies.

Participants

36

Size

1.09 GB

Version

v1.0.1

Updated

Jun 3, 2026

Imported from OpenNeuro ds003194

Participants

15

Size

189 MB

Version

v1.0.0

Updated

May 23, 2026

Participants

10

Citations

81

Size

20.7 MB

Version

v1.0.1

Updated

May 18, 2026