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on002338
A multi-modal human neuroimaging dataset for data integration: simultaneous EEG and fMRI acquisition during a motor imagery neurofeedback task: XP2

ANAT EEG FUNC Zarr

This dataset contains simultaneous 64-channel EEG and fMRI recordings from 16 participants performing right-hand motor imagery with bimodal EEG-fMRI neurofeedback (experiment XP2). Participants were randomly assigned to receive either a mono-dimensional or a bi-dimensional feedback display. It includes raw and preprocessed EEG, BOLD fMRI, and EEG and BOLD neurofeedback scores, supporting multi-modal data integration research. It is designed to be combined with the companion XP1 dataset.

Participants

17

Size

25.9 GB

Version

v1.0.0

Updated

Jun 21, 2026

by Giulia Lioi et al. OpenNeuro ds002338
nm000352
IEEG004: A library of human electrocorticographic data and analyses (Kai J. Miller) - calibrated task subset

iEEG

A calibrated task subset of Kai J. Miller's library of human electrocorticographic (ECoG) data, comprising 111 recordings from 24 epilepsy patients with subdural electrode grids. Tasks include finger flexion, hand gestures, motor movement and imagery, and verb generation and noun reading. Data were recorded at 1 kHz and converted to BIDS in BrainVision format with source-documented amplitude calibration.

Participants

24

Size

14.0 GB

Version

v1.0.0

Updated

Oct 8, 2026

by Kai J. Miller
nm000312
Alawieh2025: Motor-imagery BCI dataset with transcutaneous spinal stimulation

EEG

A longitudinal EEG dataset of two-class (left vs. right hand) motor-imagery brain-computer interface training combined with transcutaneous electrical spinal cord stimulation. It includes 27 participants (25 able-bodied and 2 with spinal cord injury), recorded with 32 EEG channels and 3 EOG channels at 512 Hz. The dataset supports study of how spinal stimulation affects sensorimotor activation and BCI skill learning.

Participants

27

Channels

32 (10-10)

HED

v8.4.0

Size

3.53 GB

Version

v1.0.0

Updated

Oct 8, 2026

by Hussein Alawieh et al.
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.
nm000219
BNCI 2020-002 Attention Shift (Covert Spatial Attention) dataset

EEG Zarr

EEG recordings from 18 healthy participants performing a gaze-independent brain-computer interface task based on covert spatial attention shifts. Participants answered yes/no questions by shifting attention to a green or red cross while maintaining central fixation, and N2pc-related ERP responses were classified with canonical correlation analysis. The data were recorded with 30 EEG channels and 2 EOG channels at 250 Hz.

Participants

18

Channels

30 (10-10)

Citations

26

HED

v8.4.0

Size

1.82 GB

Version

v1.0.3

Updated

Oct 8, 2026

by Christoph Reichert et al.
nm000244
P300 dataset BI2014a from a "Brain Invaders" experiment

EEG Zarr

EEG recordings from a visual P300 Brain-Computer Interface videogame, Brain Invaders, collected at GIPSA-lab (Grenoble, France) in 2014. Participants played a game using an oddball paradigm on a grid of 36 symbols while 16 dry electrodes recorded their EEG, with up to three game sessions per participant. The dataset was designed to study the viability of a calibration-less P300-based BCI with dry electrodes.

Participants

64

Channels

16 (10-10)

Citations

19

HED

v8.4.0

Size

3.06 GB

Version

v1.0.4

Updated

Oct 8, 2026

by Louis Korczowski et al.
on007554
Multimodal dataset from the CMx7-MM Experiment

BEH EEG NIRS Zarr

A raw multimodal dataset from 30 healthy right-handed adults performing a hierarchy of cognitive, motor, and combined cognitive-motor tasks across three sessions. It includes EEG, fNIRS, ECG, EMG, Biodex torque/kinematics, push-button responses, and subjective ratings of sleepiness and cognitive load. The data are organized in BIDS and are unprocessed exports from the acquisition systems.

Participants

30

Channels

32 (10-10)

Size

4.21 GB

Version

v1.0.0

Updated

Jun 30, 2026

by Zaineb Ajra et al. OpenNeuro ds007554
nm000167
Motor imagery dataset from Ma et al. 2020

EEG Zarr

EEG recordings from 25 healthy, BCI-naive right-handed participants performing motor imagery of two joints of the same limb (right hand and right elbow). Each participant completed 15 sessions over 3 days, giving 600 trials with 62-channel EEG sampled at 1000 Hz plus EOG. The dataset supports research on decoding fine-grained motor imagery within the same limb for motor rehabilitation and prosthetic control BCIs.

Participants

25

Channels

62 (10-10)

Citations

51

HED

v8.4.0

Size

53.8 GB

Version

v1.0.2

Updated

Aug 18, 2026

by Xuelin Ma et al.
nm000174
Imagined Speech EEG dataset comparing paradigm designs (Aguilera-Rodriguez et al. 2025)

EEG Zarr

An EEG dataset of imagined speech from 15 healthy participants comparing traditional cue-based and gamified (Pac-Man maze) paradigms for brain-computer interface applications. It comprises 1,800 trials of four Spanish directional commands (avanzar, retroceder, derecha, izquierda) recorded at 500 Hz from 24 electrodes. This BIDS derivative, distributed via MOABB and NEMAR, supports evaluation of how paradigm design affects imagined speech decoding.

Participants

15

Channels

24 (10-10)

HED

v8.4.0

Size

1.52 GB

Version

v1.0.3

Updated

Aug 18, 2026

by Edgar Aguilera-Rodriguez et al.
on007509
1hrPVTdataset_allSubjects

EEG Zarr

This dataset contains scalp EEG recordings from healthy adults during one hour of stimulation. Conditions were 40 Hz audiovisual flicker, no flicker (control), or randomized flicker (sham). Participants performed a psychomotor vigilance task throughout the session.

Participants

69

Channels

32 (10-10)

Size

14.8 GB

Version

v1.0.0

Updated

Jun 30, 2026

by Matthew Attokaren et al. OpenNeuro ds007509