on005810
NOD-MEG
ANAT MEG Zarr
…these neural mechanisms of object recognition across these rich and daily natural…
- Participants
- 31
- Size
- 215 GB
- Version
- v1.0.0
- Updated
- Jun 27, 2026
Discover datasets
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- nm000338
Lee et al. 2019 (Motor Imagery) — EEG dataset and OpenBMI toolbox for three BCI paradigms: an investigation into BCI illiteracy
EEG ZarrA motor imagery EEG dataset from 54 healthy participants performing binary left/right hand grasping imagery across two sessions on different days. Recordings were made with 62 EEG channels plus 4 EMG channels at 1000 Hz. The data belong to a larger multi-paradigm BCI collection (MI, ERP, SSVEP) used to investigate BCI illiteracy and variation in decoding performance across subjects and sessions.
- Participants
- 54
- Channels
- 62 (10-05)
- Citations
- 99
- HED
- v8.4.0
- Size
- 121 GB
- Version
- v1.0.5
- Updated
- Aug 18, 2026
- on005811
NOD-EEG
EEG Zarr…these neural mechanisms of object recognition across these rich and daily natural…
- Participants
- 19
- Channels
- 62 (10-10)
- Citations
- 5
- Size
- 24.3 GB
- Version
- v1.0.0
- Updated
- Jun 28, 2026
- on002720
A dataset recorded during development of a tempo-based brain-computer music interface
EEGEEG recordings from 19 healthy participants using a music-based brain-computer interface that lets users dynamically modulate music tempo through intentional control. Participants kinaesthetically imagined squeezing a ball with the right hand to increase tempo, or relaxed to decrease it. The paradigm comprised 9 runs, beginning with a calibration run of 30 trials in pairs of increase and decrease tempo trials.
- Participants
- 18
- Channels
- 19 (10-20)
- Size
- 2.39 GB
- Version
- v1.0.0
- Updated
- Jun 21, 2026
- nm000379
Rapid coordination of effective learning by the human hippocampus: intracranial EEG during scene recognition with eye tracking
iEEG…Center, Chicago) performing a scene recognition memory task with concurrent EyeLink eye…
- Participants
- 6
- Size
- 41.7 GB
- Version
- v1.0.0
- Updated
- Oct 8, 2026
- nm000250
Dreyer et al. 2023 — A large EEG database with users' profile information for motor imagery brain-computer interface research
EEG ZarrA large EEG database from 87 healthy participants recorded during a single-day motor imagery brain-computer interface (BCI) experiment. The data are organized into three datasets (A, B, C) that share one Graz-protocol task, left- versus right-hand motor imagery, with 240 trials per participant (over 20,800 trials in total). It also provides demographic, personality and cognitive-trait information, which supports studies of how user profiles relate to BCI performance and cross-user classification algorithms.
- Participants
- 87
- Channels
- 27 (10-10)
- Citations
- 44
- HED
- v8.4.0
- Size
- 15.8 GB
- Version
- v1.0.5
- Updated
- Oct 6, 2026
- nm000319
Kueper2024: Unilateral vs bilateral movement-execution EEG dataset
EEG…Avoidance of specific calibration sessions in motor intention recognition for exoskeleton-supported…
- Participants
- 8
- Channels
- 64 (10-10)
- HED
- v8.4.0
- Size
- 1.49 GB
- Version
- v1.0.0
- Updated
- Oct 8, 2026
- nm000113
2020 BCI competition, track 3
EEG ZarrEEG recordings from 15 participants performing imagined speech of five commands ("Hello", "Help me", "Stop", "Thank you", "Yes"), released for the 2020 BCI Competition Track 3. The data are split into training, validation and test runs to support machine-learning decoding of imagined speech for brain-computer interfaces. The dataset was converted from the original MATLAB files to BIDS-compliant EDF with trial annotations.
- Participants
- 15
- Channels
- 64 (10-10)
- Size
- 585 MB
- Version
- v1.0.0
- Updated
- Mar 14, 2026
- on005876
Song Familiarity
BEH EEG Zarr[ — Open Access Dataset for EEG+NIRS Single-Trial Classification
EEG ZarrAn 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