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nm000301
Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study D)

EEG Zarr

Study D of the bigP3BCI collection, comprising 32-channel EEG recordings from 17 healthy participants using a P300-based speller with a 6x6 character grid and dynamic row-column stimulus presentation. Data were recorded in a single session per subject with online feedback, and events are labeled as target or non-target flashes. The dataset is a BIDS-formatted derivative of the PhysioNet bigP3BCI release, intended for machine learning and BCI benchmarking.

Participants

17

Channels

32 (10-10)

Citations

2

HED

v8.4.0

Size

2.41 GB

Version

v1.0.3

Updated

Aug 18, 2026

by Boyla Mainsah et al.
on004718
Le Petit Prince Hong Kong: Naturalistic fMRI and EEG dataset from older Cantonese speakers

ANAT EEG FUNC Zarr

…such as time-aligned speech segmentation and prosodic features, along with word…

Participants

52

Channels

64

Size

109 GB

Version

v1.0.0

Updated

Jun 25, 2026

by Mohammad Momenian et al. OpenNeuro ds004718
nm000195
Mixture of LLP and EM for a visual matrix speller (ERP) dataset from

EEG Zarr

EEG recordings from an online brain-computer interface study with twelve healthy participants using a visual matrix P300 speller. Three fully unsupervised decoding methods were compared: learning from label proportions (LLP), expectation-maximization (EM), and their mixture (MIX). Participants copy-spelled a German sentence across three blocks, one per algorithm. The dataset supports research on calibration-free ERP-based BCIs.

Participants

12

Channels

31 (10-10)

Citations

27

HED

v8.4.0

Size

4.81 GB

Version

v1.0.3

Updated

Oct 8, 2026

by David Hübner et al.
nm000207
Kojima et al. 2024 (Dataset B) — Four-class ASME BCI: investigation of the feasibility and comparison of two strategies for multiclassing

EEG Zarr

…within-subject comparison - **Study domain**: auditory BCI - **Feedback type**: none - **Stimulus type…

Participants

15

Channels

64 (10-10)

Citations

5

HED

v8.4.0

Size

23.5 GB

Version

v1.0.5

Updated

Oct 8, 2026

by Simon Kojima et al.
nm000256
The Brain, Body, and Behaviour Dataset (1.0.0) - Experiment 3

BEH EEG Zarr fidelity issue

…correct answers. - “Domain” question type is a general domain knowledge question that…

Participants

29

Channels

64 (10-10)

Size

7.47 GB

Version

v1.0.0

Updated

Jun 3, 2026

by Jens Madsen et al.
on007162
Adaptive recruitment of cortex-wide recurrence for visual object recognition (EEG)

EEG Zarr

…from the decoding analyses, including time-resolved decoding accuracy matrices for object…

Participants

34

Channels

63 (10-10)

Citations

2

Size

61.2 GB

Version

v1.0.0

Updated

Jun 30, 2026

by [Unspecified1] et al. OpenNeuro ds007162
nm000351
Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study P)

EEG Zarr

Study P of the bigP3BCI collection, an open, machine-learning-ready P300-based brain-computer interface dataset. It contains 32-channel EEG recorded at 256 Hz from 19 participants with ALS, each over two sessions, while they used a 9x8 character grid speller with predictive and non-predictive spelling paradigms. Target and non-target flash events are annotated with HED tags, and the data are reformatted from the original PhysioNet release into BIDS.

Participants

19

Channels

32 (10-10)

Citations

2

HED

v8.4.0

Size

4.96 GB

Version

v1.0.4

Updated

Oct 8, 2026

by Boyla Mainsah et al.
on005960
General Info: inst-comp-eeg

EEG Zarr

…the features -blocks of features 1 and blocks of features 2-,and…

Participants

41

Channels

63 (10-10)

Citations

5

Size

57.7 GB

Version

v1.0.0

Updated

Jun 28, 2026

by Pena et al. OpenNeuro ds005960
nm000188
BNCI 2014-009 P300 dataset

EEG Zarr

A P300 brain-computer interface EEG dataset from 10 healthy, BCI-experienced female participants who selected one of 36 characters using two visual spelling interfaces: the P300 Speller (overt attention) and GeoSpell (covert attention). EEG was recorded from 16 scalp electrodes across multiple sessions. The dataset supports analysis of P300 latency jitter and its relationship to BCI classification performance.

Participants

10

Channels

16 (10-10)

Citations

85

HED

v8.4.0

Size

247 MB

Version

v1.0.3

Updated

Oct 8, 2026

by P Aricò et al.
nm000255
The Brain, Body, and Behaviour Dataset (1.0.0) - Experiment 2

BEH EEG Zarr fidelity issue

…correct answers. - “Domain” question type is a general domain knowledge question that…

Participants

31

Channels

64 (10-10)

Size

5.25 GB

Version

v1.0.0

Updated

Jun 3, 2026

by Jens Madsen et al.