Discover datasets

License

License filtering isn't available while searching — clear the search box to filter by license.

Participants

Features

Has HED annotation
Has viewer
Has data quality Coming soon

The viewer and Zarr filters aren't available while searching — clear the search box to use them.

Channels & montage

Channel density Electrode system

Channel and montage filters apply while browsing — clear the search box to use them.

Reset

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.
nm000199
Learning from label proportions for a visual matrix speller (ERP)

EEG Zarr

EEG recordings from 13 healthy participants performing a copy-spelling task with a visual 6x7 matrix ERP speller. The speller was designed for learning from label proportions (LLP), an unsupervised, calibrationless classification approach for ERP-based brain-computer interfaces. Two stimulus sequences with different target/non-target ratios allowed LLP to reconstruct mean target and non-target responses without labeled data. In the original online study, 84.5% of characters were spelled correctly on average without prior calibration.

Participants

13

Channels

31 (10-10)

Citations

46

HED

v8.4.0

Size

5.15 GB

Version

v1.0.3

Updated

Oct 8, 2026

by David Hübner et al.
nm000272
Romani et al. 2025 — BrainForm: a Serious Game for BCI Training and Data Collection (P300 ERP, University of Trento)

EEG Zarr

This dataset contains scalp EEG recordings from 22 participants who played BrainForm, a gamified P300 event-related potential brain-computer interface built for scalable data collection with consumer hardware and a minimal setup. Participants completed repeated runs of a P300 spelling/selection task at two task complexities. The data support study of BCI skill acquisition across sessions and of how different visual stimulation textures affect perception and performance.

Participants

22

Channels

8 (10-10)

HED

v8.4.0

Size

237 MB

Version

v1.0.6

Updated

Aug 20, 2026

by Michele Romani et al.
on002034
Real-time EEG feedback on alpha power lateralization leads to behavioral improvements in a covert attention task

EEG Zarr

EEG recordings from fourteen healthy participants performing a covert spatial attention task across three sessions. The study tested real-time feedback of alpha power lateralization (α-LI) versus sham feedback in a single-blinded crossover design. It examined whether such neurofeedback leads to behavioral improvements in attention.

Participants

14

Channels

64 (10-10)

Size

10.1 GB

Version

v1.0.0

Updated

Jun 21, 2026

by Christoph Schneider et al. OpenNeuro ds002034
on003195
Placebo Neuroepo multisession

EEG

Resting-state EEG recorded from 25 patients with Parkinson's disease enrolled in a double-blind, randomized, placebo-controlled trial of Neuroepo, an EPO formulation with low sialic acid content. Recordings were acquired before and six months after drug or placebo administration (Neuroepo n=15, placebo n=10). The raw data are shared in EEG-BIDS format to support evaluation of neuroprotective effects and qEEG biomarkers of disease progression.

Participants

10

Channels

19 (10-20)

Citations

2

Size

121 MB

Version

v1.0.0

Updated

May 13, 2026

by Maria Luisa Bringas Vega et al. OpenNeuro ds003195
on003838
EEG, pupillometry, ECG and photoplethysmography, and behavioral data in the digit span task and rest

BEH EEG Zarr

Raw 64-channel EEG, electrocardiography, photoplethysmography, pupillometry and behavioral data from 86 participants during 4 minutes of eyes-closed rest and a digit span serial recall task. Participants memorized or passively listened to auditory digit sequences of 5, 9, or 13 items. The dataset supports work on cognitive load discrimination, event-related and oscillatory dynamics during encoding and maintenance, and links between working memory, central and peripheral physiology.

Participants

86

Channels

63 (10-10)

Citations

65

Size

253 GB

Version

v1.0.0

Updated

Jun 22, 2026

by Yuri G. Pavlov et al. OpenNeuro ds003838
nm000367
Cognitive boundaries and theta phase precession: human microwire LFP during movie-clip encoding, scene recognition and time discrimination (Zheng et al. 2024, DANDI 000940)

iEEG

Microwire local field potentials (200 Hz) recorded from Behnke-Fried hybrid depth electrodes in 16 patients with drug-resistant epilepsy during a cognitive-boundary memory paradigm. Participants encoded 90 silent movie clips containing no, soft, or hard event boundaries, then completed a scene-recognition test and a time-discrimination test. Recording sites include the amygdala, hippocampus, and parahippocampal gyrus, with some participants also covering the dorsal anterior cingulate, pre-SMA, and ventromedial prefrontal cortex. This is an iEEG-BIDS representation of the authors' NWB release on DANDI (000940), supporting analyses of theta phase precession and episodic memory.

Participants

16

Size

2.75 GB

Version

v1.0.0

Updated

Oct 8, 2026

by Jie Zheng et al.
on002680
Go-nogo categorization and detection task

EEG Zarr

EEG recordings from participants performing a rapid go/nogo visual task in which briefly flashed (20 ms) natural photographs had to be either categorized (animal vs. non-animal) or recognized (a previously learned probe image). Data were collected over two recording days, in series of 100 images with equally likely target and non-target trials. The dataset supports research on the timing of visual categorization and recognition processes and on single-trial EEG dynamics.

Participants

14

Channels

31 (10-20)

Size

9.22 GB

Version

v1.0.0

Updated

Jun 21, 2026

by Arnaud Delorme OpenNeuro ds002680
nm000321
Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study Q)

EEG Zarr

This dataset is Study Q of bigP3BCI, an open, machine-learning-ready collection of P300-based brain-computer interface EEG recordings. It contains 32-channel EEG from 36 participants, each recorded over 3 sessions, while they used a 6x6 character speller with color intensification. Target and non-target events are annotated with HED tags. The dataset is a BIDS-formatted derivative of the PhysioNet bigP3BCI release, prepared with MOABB.

Participants

36

Channels

32 (10-10)

Citations

2

HED

v8.4.0

Size

3.70 GB

Version

v1.0.4

Updated

Oct 8, 2026

by Boyla Mainsah et al.
nm000336
Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study R)

EEG Zarr

This dataset is Study R of bigP3BCI, a large open P300-based brain-computer interface collection. It contains 32-channel EEG recorded from 20 participants over two sessions each, using a 9x8 multi-face speller grid with target and non-target flashes. The data are standardized in BIDS and prepared for machine learning and benchmarking of P300 speller decoding.

Participants

20

Channels

32 (10-10)

Citations

2

HED

v8.4.0

Size

6.59 GB

Version

v1.0.4

Updated

Oct 8, 2026

by Boyla Mainsah et al.