Discover datasets

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 62-channel EEG recorded at 500 Hz from 15 healthy participants across two sessions. It combines resting-state recordings with three difficulty levels (easy, medium, difficult) of the MATB-II multitasking paradigm, and was designed for passive brain-computer interface research on cross-session mental workload estimation. The BIDS version is a MOABB-derived conversion of the COG-BCI database, with HED event annotations.

Participants

15

Channels

61 (10-10)

Citations

70

HED

v8.4.0

Size

1.22 GB

Version

v1.0.0

Updated

Jun 2, 2026

This dataset contains 32-channel EEG recordings acquired during a sham neurofeedback experiment in a virtual reality environment. The study examined how feedback valence (positive, negative, or none) modulates alpha-band activity during an attentional task. Each participant completed positive, negative, control, and resting-state (eyes open/eyes closed) conditions.

Participants

36

Channels

29 (10-10)

Size

10.4 GB

Version

v1.0.0

Updated

Jun 29, 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

NeuroMorph is a magnetoencephalography (MEG) dataset with high temporal resolution, designed for morpheme-based linguistic analysis. It contains recordings from 24 participants, totaling over 17 hours of data, acquired with a 208-channel KIT/Yokogawa magnetometer system. The dataset supports research on the neural processing of morphology during language comprehension.

Participants

24

Size

140 GB

Version

v1.0.0

Updated

Jun 26, 2026

EEG dataset from the PROTEUS brain-computer interface (BCI) project in Bordeaux, released for the EEG/EMG Foundation Challenge 2026 (Track 02). It contains recordings from 10 participants across 14 sessions (112 runs) performing three cued mental tasks: kinesthetic motor imagery, mental subtraction and word generation. Runs include resting baselines, calibration runs with sham feedback and online runs with real feedback, using Graz and BrainHero interfaces.

Participants

10

Channels

41 (10-10)

Size

1.48 GB

Version

v1.0.0

Updated

Oct 1, 2026

A cross-session motor imagery EEG dataset from 14 healthy participants who performed cued left- versus right-hand motor imagery on two separate days. Data were recorded with 28 EEG channels at 250 Hz and comprise 60 trials per class per session. The dataset supports research on brain-computer interface decoding and cross-session variability, and it is distributed here in BIDS format with HED event annotations.

Participants

14

Channels

28 (10-10)

HED

v8.4.0

Size

1018 MB

Version

v1.0.0

Updated

Oct 8, 2026

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

Open-access resting-state EEG recordings from 21 neurotypical undergraduate students at the Federal University of Paraíba, Brazil, collected before and after different study methods. Participants were randomly assigned to an active learning group (retrieval practice with feedback), a passive learning group (review of lecture notes), or a control group with no review. The dataset supports research in cognitive neuroscience, educational neuroscience, and the neural correlates of learning and memory.

Participants

21

Channels

31

Size

1.32 GB

Version

v1.0.0

Updated

Jun 29, 2026

EEG recordings from four participants performing motor imagery of the left hand, right hand, and feet, originally reported by Zhou et al. (2016) in a study on automated trial selection for motor imagery brain-computer interfaces. Each participant completed three sessions of two runs, giving 450 trials per subject. Data were recorded from 14 channels at 250 Hz and reformatted into BIDS from a MOABB-generated Zenodo version.

Participants

4

Channels

14 (10-10)

Citations

87

Size

152 MB

Version

v1.0.0

Updated

Mar 3, 2026