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nm000296
MIMED2024: Motor Imagery MIMED dataset from Wirawan et al. 2024

EEG

EEG recordings of motor imagery and motor execution for six activities (raising and lowering each hand, standing and sitting) from 30 healthy participants over two sessions. Data were acquired with a 14-channel Emotiv EPOC X headset at 128 Hz. This BIDS re-release, produced via MOABB, exposes a 3-class imagery task (left hand, right hand, trunk) for brain-computer interface research. The distributed imagery files carry no per-repetition activity label, so only folder-level 3-class labels are available.

Participants

30

Channels

14 (10-10)

HED

v8.4.0

Size

41.2 MB

Version

v1.0.0

Updated

Oct 8, 2026

by I Made Agus Wirawan et al.
nm000303
Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study O)

EEG Zarr

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.nm000303-blue…

Participants

18

Channels

32 (10-10)

Citations

2

HED

v8.4.0

Size

3.23 GB

Version

v1.0.4

Updated

Oct 8, 2026

by Boyla Mainsah et al.
nm000146
Motor Imagery dataset from Weibo et al 2014

EEG Zarr

A 60-channel EEG dataset from 10 healthy, BCI-naive participants performing simple limb motor imagery (left hand, right hand, feet) and compound limb motor imagery (both hands, left hand with right foot, right hand with left foot), plus a rest condition. The recordings were used to examine EEG oscillatory patterns (ERD/ERS), cognitive processes, and effective connectivity during motor imagery. This is a preprocessed (bandpass filtered, downsampled to 200 Hz) BIDS version curated through MOABB.

Participants

10

Channels

60 (10-10)

Citations

93

HED

v8.4.0

Size

5.64 GB

Version

v1.0.3

Updated

Oct 8, 2026

by Weibo Yi et al.
nm000313
Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study S2)

EEG Zarr

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.nm000313-blue…

Participants

24

Channels

32 (10-10)

Citations

2

HED

v8.4.0

Size

3.74 GB

Version

v1.0.3

Updated

Aug 18, 2026

by Boyla Mainsah et al.
nm000277
Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study G)

EEG Zarr

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.nm000277-blue…

Participants

20

Channels

16 (10-10)

Citations

2

HED

v8.4.0

Size

1.62 GB

Version

v1.0.3

Updated

Aug 18, 2026

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

EEG Zarr

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.nm000321-blue…

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.
on007216
A multi-session simultaneous EEG-fMRI dataset with online experience sampling

ANAT EEG FMAP FUNC Zarr

A multi-session dataset of simultaneous EEG-fMRI recorded from 24 healthy adults aged 18-35 while they performed a gradual-onset continuous performance task (GradCPT) and a resting-state condition with intermittent multidimensional experience sampling. The same protocol was repeated on two days. Carbon wire loop sensors in the EEG cap support artifact removal. The dataset also includes ECG, behavioral responses, and mental health surveys. It supports study of attentional fluctuations, mind-wandering, and the test-retest reliability of EEG-fMRI relationships.

Participants

24

Channels

31 (10-10)

Citations

1

Size

115 GB

Version

v1.0.0

Updated

Jul 2, 2026

by Aaron Kucyi et al. OpenNeuro ds007216
nm000301
Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study D)

EEG Zarr

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.nm000301-blue…

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.
nm000141
Motor execution dataset from Wairagkar et al 2018

EEG Zarr

EEG recordings from 14 healthy, BCI-naive participants performing asynchronous voluntary index-finger tapping (right, left) and rest, originally reported by Wairagkar et al. (2018). Data were recorded at 1024 Hz from 19 scalp channels and preprocessed with filtering and ICA artifact removal. Trials are segmented around movement onset to study neural correlates of movement intention, and the dataset is distributed in BIDS format via MOABB.

Participants

14

Channels

19 (10-20)

Citations

10

HED

v8.4.0

Size

1.23 GB

Version

v1.0.2

Updated

Aug 18, 2026

by Maitreyee Wairagkar 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

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.nm000351-blue…

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.