Discover datasets

This dataset is Study O of bigP3BCI, a large open collection of P300-based brain-computer interface EEG recordings. It contains 32-channel EEG from 18 participants with ALS, each recorded over two sessions while using a 9x8 character speller with a supervised checkerboard stimulus paradigm. Target and non-target flashes are annotated with HED tags, and the data are formatted for machine learning and benchmarking.

Participants

18

Channels

32 (10-10)

Citations

2

HED

v8.4.0

Size

3.23 GB

Version

v1.0.4

Updated

Oct 8, 2026

MEG dataset from a logical reasoning study collected by the Cognitive and Computational Neuroscience Laboratory (UPM - UCM). The dataset is organized in BIDS format and mirrored on NEMAR from the OpenNeuro deposit ds003483.

Participants

21

Size

68.3 GB

Version

v1.0.0

Updated

Jun 21, 2026

A longitudinal motor imagery EEG dataset from 18 BCI-naive participants recorded across six sessions (one offline, five online) with 22 EEG channels at 512 Hz. It supports the study of transfer learning for brain-computer interface skill acquisition, comparing unsupervised Generic Recentering and supervised Personally Assisted Recentering for calibration-free training. Participants performed left/right hand motor imagery with continuous visual feedback.

Participants

18

Channels

22 (10-10)

Citations

53

HED

v8.4.0

Size

14.4 GB

Version

v1.0.5

Updated

Oct 8, 2026

EEG dataset from twenty-one participants performing a continuous feedback learning task in which they predicted the final level of an animated rising bar. Cues (gnomes) differed in how predictable the outcome was (highly predictable, somewhat predictable, unpredictable), enabling study of feedback processing under varying outcome uncertainty. Points were awarded according to the accuracy of each guess.

Participants

21

Channels

31 (10-10)

Citations

1

Size

3.48 GB

Version

v1.0.0

Updated

Jun 23, 2026

A preprocessed derivative EEG dataset from BCI Competition 2020 Track 4, containing motor imagery recordings of three right-arm grasping tasks (cylindrical, spherical, lumbrical) from 15 healthy subjects across three sessions. It provides 60-channel EEG at 250 Hz with 450 trials per subject, and is intended for evaluating session-to-session transfer learning in brain-computer interfaces. Data were notch filtered and epoched to the 4 s motor imagery window, and re-hosted in BIDS format via MOABB.

Participants

14

Channels

60 (10-10)

HED

v8.4.0

Size

2.76 GB

Version

v1.0.3

Updated

Aug 18, 2026

The Multimodal Resource for Studying Information Processing in the Developing Brain (MIPDB) provides high-density 128-channel EEG and eye-tracking recordings from a developmental cohort spanning childhood to adulthood. Participants completed a battery of cognitive and perceptual paradigms, including resting state, surround suppression, naturalistic viewing, contrast change detection, sequence learning, and symbol search. This BIDS conversion contains EEG data from 111 participants, with source eye-tracking and behavioural data preserved in sourcedata.

Participants

111

Citations

65

Size

110 GB

Version

v1.0.0

Updated

Jun 17, 2026

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

Raw MEG dataset with T1-weighted anatomical scans and behavioural logfiles from an audiovisual speech memory experiment. Participants completed repeated blocks of encoding (audiovisual synchrony detection on speech movies), a distractor task, and cued retrieval of the auditory speech associated with a speaker's face. The data support analyses of neocortical and hippocampal theta oscillations in audiovisual integration and memory replay.

Participants

30

Citations

7

Size

172 GB

Version

v1.0.0

Updated

Jun 28, 2026

NOD-MEG is a magnetoencephalography dataset of human subjects viewing naturalistic object images drawn from ImageNet. It extends the Natural Object Dataset-fMRI (NOD-fMRI) with MEG and EEG recorded from the same subjects viewing the same stimuli. Together the modalities offer high spatial and high temporal resolution for studying object recognition. The release includes raw BIDS data, preprocessed continuous data, epochs, and detailed trial-level event tables.

Participants

31

Size

215 GB

Version

v1.0.0

Updated

Jun 27, 2026

This dataset contains scalp EEG recordings from 28 participants performing or imagining upper-limb rehabilitation exercises under a multi-paradigm protocol. It is intended to support research on motor-imagery and rehabilitation brain-computer interfaces for restoring upper-limb function. The data are organized in BIDS format under a motor-imagery task.

Participants

28

Channels

59 (10-10)

Citations

3

HED

v8.4.0

Size

47.1 GB

Version

v1.0.5

Updated

Aug 20, 2026