Discover datasets

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

A cross-session motor imagery EEG dataset from 10 healthy participants who performed cued left- versus right-hand motor imagery across two sessions. Recordings used 28 EEG channels sampled at 250 Hz with a Neuroscan SynAmps2 amplifier, with roughly 180 trials per session. In session 2, test trials included online feedback. The data were re-released in BIDS format via MOABB for brain-computer interface research.

Participants

10

Channels

28 (10-10)

HED

v8.4.0

Size

1.01 GB

Version

v1.0.0

Updated

Oct 8, 2026

Stereo-EEG recordings from six patients with medically refractory epilepsy performing a scene recognition memory task with concurrent EyeLink eye tracking. The dataset accompanies a study of how the human hippocampus rapidly coordinates effective learning, and is a lossless iEEG-BIDS re-packaging of the authors' public Zenodo release. It includes electrode MNI coordinates, behavioural arrays, eye-tracking files and the authors' analysis code in sourcedata.

Participants

6

Size

41.7 GB

Version

v1.0.0

Updated

Oct 8, 2026

EEG recordings from 12 healthy participants performing three-class motor imagery of the same upper extremity: rest, hand grasping, and elbow flexion. Each participant completed 4 sessions of 20 trials per class, recorded with a 32-channel EGI HydroCel net at 1000 Hz. The dataset supports research on brain-computer interface classification of imagined movements within one limb, for example for rehabilitation and motor control.

Participants

12

Channels

32 (egi-geodesic)

Citations

45

HED

v8.4.0

Size

52.0 GB

Version

v1.0.3

Updated

Aug 20, 2026

EEG recordings from 20 healthy participants performing a discrete center-out reaching task in four directions (up, down, left, right) at two speeds (slow, fast) and two distances (near, far). The data were recorded with 67 channels, including EOG, and preprocessed with eye artifact correction (SGEYESUB) and ICA. The dataset supports research on low-frequency EEG encoding of reaching kinematics and on brain-computer interfaces.

Participants

20

Channels

67 (10-05)

Citations

4

HED

v8.4.0

Size

15.4 GB

Version

v1.0.2

Updated

Aug 18, 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

A multimodal EEG dataset of motor imagery (MI) recorded from 31 healthy participants over up to three sessions each. Participants imagined left- and right-hand grasping in response to visual cues while 64-channel EEG plus EOG were recorded at 1000 Hz. This is a MOABB-derived version of the Eye-BCI dataset, which also includes eye-tracking and high-speed video for ocular activity analysis across BCI paradigms.

Participants

31

Channels

66 (10-10)

Citations

13

HED

v8.4.0

Size

4.65 GB

Version

v1.0.0

Updated

Jun 3, 2026

FACE-DEC is an OPM-MEG (optically pumped magnetometer magnetoencephalography) dataset for studying face perception through multivariate decoding and representational similarity analysis. The release includes analysis code for preprocessing (face_1_prep), decoding (face_2_dec), RSA (face_3_rsa), statistics (face_4_stat), and Bayesian model selection (face_6_bayes.m), with a main entry script (face_0_main). Individual facial point clouds and structural MRIs were not collected because optical scanning equipment was unavailable, so all analyses were performed at the whole-brain sensor level. Data collection was approved by the Institutional Review Board of Peking University.

Participants

21

Size

27.6 GB

Version

v1.0.0

Updated

Jun 26, 2026

An open access dataset for hybrid brain-computer interface research combining EEG and near-infrared spectroscopy (NIRS). This portion (Experiment A) contains recordings from 29 healthy participants performing left versus right hand kinesthetic motor imagery over multiple sessions. The data include 30 EEG channels plus EOG, are preprocessed, and are annotated with HED tags. They support single-trial classification and multimodal BCI validation.

Participants

29

Channels

30 (10-05)

Citations

95

HED

v8.4.0

Size

6.50 GB

Version

v1.0.3

Updated

Aug 18, 2026

EEG recordings from fourteen healthy participants performing a covert spatial attention task across three sessions. The study tested real-time feedback of alpha power lateralization (α-LI) versus sham feedback in a single-blinded crossover design. It examined whether such neurofeedback leads to behavioral improvements in attention.

Participants

14

Channels

64 (10-10)

Size

10.1 GB

Version

v1.0.0

Updated

Jun 21, 2026