on000247
MEG-BIDS OMEGA RestingState_sample
ANAT MEG Zarr
…Imaging Data Structure, http://bids.neuroimaging.io) (Niso et al. 2018) - Niso…
- Participants
- 6
- Size
- 10.5 GB
- Version
- v1.0.0
- Updated
- Jun 20, 2026
Discover datasets
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- nm000220
BEETL Competition 2021 Motor Imagery Dataset A — transfer learning benchmark
EEG ZarrBeetl2021-A is a preprocessed four-class motor imagery EEG dataset (rest, left hand, right hand, feet) from Task 2 of the BEETL Competition at NeurIPS 2021. It contains 63-channel recordings at 500 Hz from healthy participants playing an online BCI racing game (Cybathlon2020IC), with 1490 trials of 4 s each in a single session. It serves as a benchmark for transfer learning and domain adaptation across heterogeneous EEG datasets and subjects, and is re-hosted in BIDS format via the MOABB pipeline.
- Participants
- 3
- Channels
- 63 (10-10)
- HED
- v8.4.0
- Size
- 2.17 GB
- Version
- v1.0.6
- Updated
- Aug 20, 2026
- nm000177
Multi-session longitudinal motor imagery EEG dataset (Kumar et al. 2024)
EEGA 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
- on003887
Capacity for movement is an organisational principle in object representations: EEG data from Experiment 2
EEG Zarr…Recent neuroimaging evidence has shown that goal-directed movement is an important…
- Participants
- 24
- Citations
- 3
- Size
- 80.7 GB
- Version
- v1.0.0
- Updated
- Jun 22, 2026
- on003645
Face processing MEEG dataset with HED annotation
ANAT BEH EEG MEG ZarrA multi-modal face processing dataset combining simultaneously recorded MEG and EEG with structural MRI from 18 participants. Participants viewed famous, unfamiliar, and scrambled faces and made a symmetry judgment by button press. The data are a curated repackaging of the MEEG portion of ds000117, with reorganized event logs, Hierarchical Event Descriptor (HED) annotations, and EEGLAB-format EEG.
- Participants
- 19
- Citations
- 80
- HED
- v8.1.0
- Size
- 106 GB
- Version
- v1.0.0
- Updated
- Mar 9, 2026
- on003885
Capacity for movement is an organisational principle in object representations: EEG data from Experiment 1
EEG Zarr…Recent neuroimaging evidence has shown that goal-directed movement is an important…
- Participants
- 24
- Citations
- 18
- Size
- 82.2 GB
- Version
- v1.0.0
- Updated
- Jun 22, 2026
- nm000178
BNCI 2020-001 Reach-and-Grasp Electrode Comparison EEG dataset
EEG ZarrEEG recordings from healthy participants performing self-initiated palmar and lateral reach-and-grasp actions, acquired simultaneously across three recording systems: gel-based laboratory EEG, water-based mobile EEG, and dry-electrode mobile EEG. The dataset supports investigation of the feasibility of decoding natural reach-and-grasp movement-related cortical potentials across EEG acquisition modalities for brain-computer interface applications. It is distributed in BIDS format as part of the MOABB benchmark collection.
- Participants
- 45
- Channels
- 58 (10-05)
- Citations
- 50
- HED
- v8.4.0
- Size
- 8.67 GB
- Version
- v1.0.4
- Updated
- Oct 8, 2026
- on002718
Face processing EEG dataset for EEGLAB
ANAT EEG Zarr…subject, multi-modal (sMRI+EEG) neuroimaging dataset on face processing. Original data…
- Participants
- 18
- Channels
- 70 (other)
- Citations
- 84
- Size
- 4.31 GB
- Version
- v1.0.0
- Updated
- May 25, 2026
- nm000158
Liu, Lv et al. 2023 — EEG datasets of stroke patients (motor imagery)
EEG ZarrEEG motor imagery dataset recorded from 50 acute stroke patients (1-30 days post-stroke) using a wireless portable semi-dry saline EEG system. Patients imagined left- or right-hand grasping during video-guided trials (40 per subject). It is presented as the first open dataset addressing left- and right-handed motor imagery in acute stroke, supporting BCI algorithm development and rehabilitation applications. Raw and preprocessed data and patient clinical characteristics are provided.
- Participants
- 50
- Channels
- 29 (10-10)
- Citations
- 88
- HED
- v8.4.0
- Size
- 1.15 GB
- Version
- v1.0.3
- Updated
- Aug 18, 2026
- on006720
Alpha power indexes working memory load for durations
ANAT MEG Zarr[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on006720-blue…
- Participants
- 24
- Citations
- 1
- Size
- 136 GB
- Version
- v1.0.0
- Updated
- Jun 29, 2026