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This dataset comprises EEG recordings from 8 healthy subjects performing a P300-based brain-computer interface task using a 6x6 checkerboard visual stimulus paradigm. Recorded at 256 Hz with 16 channels using g.USBamp hardware, the data includes target and non-target event classifications for speller application development. This derivative dataset is part of the BigP3BCI study, the largest public P300 BCI dataset containing recordings from approximately 267 subjects across multiple stimulus paradigms.

Participants

8

Channels

16 (10-10)

HED

v8.4.0

Size

518 MB

Version

v1.0.2

Updated

Aug 18, 2026

BigP3BCI Study R is a P300-based brain-computer interface dataset comprising EEG recordings from 20 subjects performing a 9x8 multi-face character grid speller task across two sessions. This derivative dataset is part of the larger BigP3BCI collection, the largest public P300 BCI dataset with ~267 subjects across 20 studies. The data were acquired at 256 Hz using 32-channel EEG with a g.USBamp amplifier and are formatted according to BIDS standards with HED event annotations for standardized analysis and machine learning applications.

Participants

20

Channels

32 (10-10)

HED

v8.4.0

Size

6.59 GB

Version

v1.0.3

Updated

Aug 18, 2026