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This dataset comprises intracranial EEG recordings collected using the CorTec BrainInterchange implantable device and the BCI2000 software platform, developed as part of an ecosystem of technology and protocols for adaptive neuromodulation research in humans. The data support research into closed-loop neuromodulation approaches and adaptive brain-computer interface systems. Recordings were obtained under IACUC-approved protocols in collaboration with Mayo Clinic and academic partners.

Participants

3

Size

19.3 GB

Version

v1.0.0

Updated

Aug 19, 2026

BigP3BCI Study C is a P300-based brain-computer interface dataset comprising EEG recordings from 19 healthy subjects performing a visual speller task using a 6x6 checkerboard paradigm. The dataset contains single-session recordings with 32-channel EEG data sampled at 256 Hz, annotated with target and non-target event labels. This derivative dataset is part of the larger BigP3BCI collection, the largest public P300 BCI dataset, and is formatted according to BIDS standards with HED event annotations for machine learning applications.

Participants

19

Channels

32 (10-10)

HED

v8.4.0

Size

4.11 GB

Version

v1.0.3

Updated

Aug 18, 2026

Imported from OpenNeuro ds003194

Participants

15

Channels

19 (10-20)

Size

189 MB

Version

v1.0.0

Updated

Jul 10, 2026

BigP3BCI Study J is a P300-based brain-computer interface dataset comprising EEG recordings from 20 healthy subjects performing a 9x8 character grid speller task. 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 16-channel EEG with a g.USBamp amplifier and include target and non-target event classifications suitable for machine learning applications.

Participants

20

Channels

16 (10-10)

HED

v8.4.0

Size

1.49 GB

Version

v1.0.3

Updated

Aug 18, 2026

This dataset contains EEG recordings from 20 healthy participants performing a 7-day longitudinal motor imagery brain-computer interface (BCI) task without feedback. Each subject completed 7 sessions of 6 runs, imagining left hand, right hand, feet, and rest movements, yielding 33,600 trials in total. The dataset was converted to BIDS format from the original study by Zhou et al. (2021) examining the relationship between relative power and motor imagery decoding performance across time and subjects.

Participants

20

Channels

41 (other)

Citations

15

HED

v8.4.0

Size

93.1 GB

Version

v1.0.3

Updated

Aug 20, 2026

Participants

15

Channels

64 (10-10)

Size

585 MB

Version

v1.0.0

Updated

Jul 10, 2026

BigP3BCI Study B is a derivative EEG dataset containing P300 brain-computer interface recordings from 19 ALS patients across 8 sessions each, using a 6x6 checkerboard visual speller paradigm. The dataset comprises 16-channel EEG data sampled at 256 Hz, annotated with target and non-target event classifications using HED 8.4.0 schema. This dataset is a subset of the larger BigP3BCI collection, the largest public P300 BCI dataset with recordings from approximately 267 subjects across multiple studies.

Participants

19

Channels

16 (10-10)

HED

v8.4.0

Size

4.28 GB

Version

v1.0.2

Updated

Aug 18, 2026

This dataset contains neuroimaging recordings from 29 participants investigating human brain responses to nociceptive stimulation. The study examines neural activity patterns during concomitant stimulation of Aδ and C nociceptors, contributing to understanding of pain processing mechanisms in the human brain.

Participants

29

Channels

64 (10-10)

Size

24.0 GB

Version

v1.0.0

Updated

Jul 10, 2026