Discover datasets

A multimodal neuroimaging dataset combining EEG, eye-tracking, and high-speed video recordings from 31 healthy participants performing a 4-class steady-state visually evoked potential (SSVEP) brain-computer interface task. The dataset comprises 3,024 trials across 63 sessions with 64-channel EEG recordings plus 1 EOG and 1 stimulus channel at 1000 Hz sampling rate, designed to investigate ocular activity patterns and their relationship to BCI performance across multiple paradigms.

Participants

11

Channels

62 (10-10)

Citations

9

HED

v8.4.0

Size

2.06 GB

Version

v1.0.1

Updated

Jul 10, 2026

BigP3BCI Study O is a P300-based brain-computer interface dataset comprising EEG recordings from 18 ALS subjects across 2 sessions each. Participants performed a visual speller task using a 9x8 character grid with supervised/checkerboard stimulus paradigm. The dataset contains 32-channel EEG data sampled at 256 Hz, annotated with target and non-target event labels, and is part of the larger BigP3BCI collection representing one of the most comprehensive public P300 BCI datasets.

Participants

18

Channels

32 (10-10)

HED

v8.4.0

Size

981 MB

Version

v1.0.1

Updated

Jul 10, 2026

BigP3BCI Study D is a P300-based brain-computer interface dataset comprising EEG recordings from 17 healthy subjects performing a 6x6 character grid speller task using dynamic row-column stimulus presentation. 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 using HED 8.4.0 schema. This derivative dataset is part of the larger BigP3BCI collection, the largest public P300 BCI dataset, and is designed for machine learning model development and benchmarking in brain-computer interface research.

Participants

17

Channels

32 (10-10)

HED

v8.4.0

Size

731 MB

Version

v1.0.1

Updated

Jul 10, 2026

BigP3BCI Study G is a P300-based brain-computer interface dataset comprising EEG recordings from 20 healthy subjects performing a 9x8 checkerboard visual speller task. This derivative dataset is Study G of 20 studies in the larger BigP3BCI collection, the largest public P300 BCI dataset with ~267 subjects total. 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

327 MB

Version

v1.0.1

Updated

Jul 10, 2026

BrainForm is a P300 event-related potential (ERP) EEG dataset collected from 22 participants using a gamified brain-computer interface (BCI) designed for scalable data collection with consumer hardware. Participants completed repeated runs of a P300 spelling/selection task within a serious game paradigm, enabling investigation of BCI skill acquisition across sessions and the effects of different visual stimulation textures on perceptual and performance outcomes.

Participants

22

Citations

1

Size

132 MB

Version

v1.0.1

Updated

Jul 10, 2026

A multi-paradigm EEG dataset comprising scalp electroencephalography recordings from 28 participants performing and imagining upper-limb rehabilitation exercises. This dataset is designed to support research on motor imagery and rehabilitation brain-computer interfaces (BCI) for upper-limb motor function recovery and assessment.

Participants

28

Citations

2

Size

3.46 GB

Version

v1.0.1

Updated

Jul 10, 2026

This dataset comprises scalp electroencephalography recordings from 27 stroke patients performing lower-limb motor imagery tasks as part of a longitudinal rehabilitation training protocol. The multi-paradigm design supports research on motor-imagery brain–computer interfaces for gait and lower-limb rehabilitation following stroke, with repeated sessions enabling investigation of learning and neuroplasticity during motor recovery.

Participants

27

Citations

20

Size

5.79 GB

Version

v1.0.1

Updated

Jul 10, 2026

This open-access hybrid brain-computer interface dataset combines simultaneous EEG and near-infrared spectroscopy (NIRS) recordings from 29 healthy subjects performing mental arithmetic and motor imagery tasks. Experiment B focuses on mental arithmetic (serial subtraction) versus rest conditions across six sessions with 20 trials per session. The dataset includes preprocessed EEG data (30 channels, 200 Hz sampling rate) with comprehensive artifact correction and has been validated for single-trial classification using common spatial patterns and linear discriminant analysis.

Participants

29

Channels

30 (10-05)

Citations

94

HED

v8.4.0

Size

1.87 GB

Version

v1.0.1

Updated

Jul 10, 2026

An open access hybrid brain-computer interface dataset combining electroencephalography (EEG) and near-infrared spectroscopy (NIRS) recordings from 29 healthy subjects performing motor imagery and mental arithmetic tasks. The dataset includes preprocessed EEG data (30 channels, 200 Hz sampling rate) and NIRS data with validated classification performance demonstrating enhanced discrimination of mental states through multimodal analysis compared to single modality approaches.

Participants

29

Channels

30 (10-05)

Citations

94

HED

v8.4.0

Size

1.87 GB

Version

v1.0.1

Updated

Jul 10, 2026

An auditory event-related potential dataset from 13 healthy subjects performing an oddball paradigm with two sinusoidal tones (target 1000 Hz, non-target 500 Hz) presented at variable stimulus onset asynchronies (60-600 ms). The dataset comprises 31-channel EEG recordings at 1000 Hz acquired with BrainProducts BrainAmp DC, designed to evaluate Bayesian optimization strategies for automated selection of individually optimal stimulation parameters in brain-computer interface applications.

Participants

13

Channels

31 (10-10)

Citations

2

HED

v8.4.0

Size

3.66 GB

Version

v1.0.1

Updated

Jul 10, 2026