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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.
nm000182
Multicenter iEEG dataset for classification of graphoelements and artifactual signals (MAYO)

iEEG Zarr

Nejedly2020 multicenter iEEG graphoelement clips (MAYO) This BIDS dataset is converted from…

Participants

24

Size

8.69 GB

Version

v1.0.2

Updated

Jun 29, 2026

by Petr Nejedly et al.
nm000183
Multicenter iEEG dataset for classification of graphoelements and artifactual signals (FNUSA)

iEEG Zarr

Nejedly2020 multicenter iEEG graphoelement clips (FNUSA) This BIDS dataset is converted from…

Participants

14

Size

10.8 GB

Version

v1.0.2

Updated

Jun 29, 2026

by Petr Nejedly et al.
nm000373
Intracranial entrainment reveals statistical learning across levels of abstraction (Sherman et al., 2023): raw iEEG from 8 neurosurgical patients

iEEG

…patients with electrodes implanted for seizure monitoring, recorded while they viewed rapid…

Participants

8

Size

17.5 GB

Version

v1.0.0

Updated

Oct 8, 2026

by Brynn Sherman et al.
nm000346
Castillos et al. 2023, m-sequence c-VEP, 100% amplitude depth: Burst c-VEP Based BCI: Optimizing stimulus design for enhanced classification with minimal calibration data and improved user experience

EEG Zarr

EEG dataset of a 4-class code-modulated visual evoked potential (c-VEP) reactive brain-computer interface study with 12 healthy participants. This subset contains the m-sequence c-VEP condition at 100% amplitude depth, recorded with a 32-channel BrainProducts LiveAmp system at 500 Hz. The study compared burst and m-sequence codes at two amplitude depths, assessing classification accuracy with minimal calibration data and user experience.

Participants

12

Channels

32 (10-10)

Citations

18

HED

v8.4.0

Size

352 MB

Version

v1.0.3

Updated

Oct 8, 2026

by Kalou Cabrera Castillos et al.
nm000369
Sensorimotor alpha and beta ECoG during movement imagery (Stolk et al. 2019, shared participants S4-S6)

iEEG

…No seizures occurred during task administration. - This release: S4 (right hemisphere, 112…

Participants

3

Size

663 MB

Version

v1.0.0

Updated

Oct 8, 2026

by Arjen Stolk et al.
on006923
Dataset of Electroencephalograms of Juvenile Offenders

EEG Zarr

Resting-state EEG recordings from 140 Colombian young people: 74 juvenile offenders and 66 non-offender controls. Data were acquired with a 128-channel Biosemi ActiveTwo system. The dataset provides epoched and preprocessed EEG, along with spectral band-power features (delta, theta, alpha, beta) for eyes-open and eyes-closed epochs. It is intended to support the study of neurocognition in juvenile delinquency.

Participants

140

Channels

128 (other)

Size

8.13 GB

Version

v1.0.0

Updated

Jun 29, 2026

by Aura Polo et al. OpenNeuro ds006923
nm000184
BCI Competition 2020 Track 5 — ERP during walking (scalp, ear-EEG, and IMU)

EEG Zarr

EEG recordings from 15 healthy participants performing a visual P300 oddball task while walking on a treadmill at 1.6 m/s, released as BCI Competition 2020 Track 5. The dataset combines 46-channel scalp EEG, 14-channel ear-EEG, 4 EOG channels, and 6 inertial measurement unit channels sampled at 100 Hz. It is intended for evaluating brain-computer interface performance under ambulatory conditions, with trials divided temporally into training, validation, and test sets.

Participants

15

Channels

46 (10-10)

HED

v8.4.0

Size

224 MB

Version

v1.0.4

Updated

Oct 8, 2026

by Ji-Hoon Jeong et al.
on003498
interictal iEEG during slow-wave sleep with HFO markings

iEEG Zarr fidelity issue

…Resection of high frequency oscillations predicts seizure outcome in the individual patient…

Participants

20

Citations

97

Size

44.7 GB

Version

v1.0.0

Updated

Jun 21, 2026

by Fedele T et al. OpenNeuro ds003498
nm000257
Imagined speech EEG dataset — short words condition (Nguyen et al. 2017)

EEG Zarr

Preprocessed 64-channel EEG recordings from 6 healthy participants performing imagined speech of three short words (out, in, up), cued by auditory and visual stimuli. The dataset contains 1800 trials of a single session, analyzed in the source study with Riemannian manifold covariance features and relevance vector machines for brain-computer interface applications. It is re-hosted in BIDS format from the MOABB benchmark collection.

Participants

6

Channels

60 (10-10)

Citations

99

HED

v8.4.0

Size

1.90 GB

Version

v1.0.3

Updated

Aug 18, 2026

by Chuong H. Nguyen et al.