on004703
sEEG Passive listening to natural speech
ANAT iEEG Zarr fidelity issue
…of training set for commercial machine learning applications. These data may not…
- Participants
- 10
- Size
- 13.2 GB
- Version
- v1.0.0
- Updated
- Jun 25, 2026
Discover datasets
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- on006673
ball_squeeze_Carlton_2025
NIRSA high-density functional near-infrared spectroscopy (fNIRS) dataset recorded during a ball-squeezing motor task at Boston University. The recordings were used to develop and optimize surface-based image reconstruction methods for high-density fNIRS. The dataset is mirrored on NEMAR from OpenNeuro (ds006673).
- Participants
- 17
- Size
- 20.7 GB
- Version
- v1.0.0
- Updated
- Jun 18, 2026
- nm000287
Muse Sleep-Onset EEG — EEG/EMG Foundation Challenge 2026, Track 03
EEG Zarr…of the EEG/EMG Foundation Challenge 2026. The task is to predict…
- Participants
- 203
- Channels
- 4 (10-10)
- Size
- 1.08 GB
- Version
- v1.0.0
- Updated
- Sep 24, 2026
- nm000232
THINGS-EEG2: A large and rich EEG dataset for modeling human visual object recognition
EEG ZarrTHINGS-EEG2 is an EEG dataset from 10 participants who viewed 16,540 training images and 200 repeated test images from the THINGS database, using rapid serial visual presentation at 5 Hz. Each participant completed four sessions, recorded with a 63-channel BrainVision actiCHamp system at 1000 Hz, plus resting-state recordings. The dataset supports modeling of human visual object recognition and encoding models of neural responses.
- Participants
- 10
- Channels
- 63 (10-10)
- Citations
- 88
- Size
- 241 GB
- Version
- v1.1.1
- Updated
- Oct 15, 2026
- on003519
EEG: Visual Working Memory + Cabergoline Challenge
EEG[
- Citations
- 1
- Size
- 8.96 GB
- Version
- v1.0.0
- Updated
- Jun 22, 2026
- nm000173
Motor Imagery ataset from Ofner et al 2017
EEG ZarrEEG recordings from fifteen healthy participants who executed and imagined six sustained upper limb movements (elbow flexion/extension, forearm supination/pronation, hand open/close) plus a rest condition, in two separate sessions. The dataset supports decoding of single upper limb movements from the time-domain of low-frequency EEG. It is relevant to non-invasive control of motor neuroprostheses and robotic arms. This BIDS version was generated from the original BNCI Horizon 2020 data using MOABB.
- Participants
- 15
- Channels
- 61 (10-05)
- Citations
- 93
- HED
- v8.4.0
- Size
- 34.0 GB
- Version
- v1.0.3
- Updated
- Aug 18, 2026
- on005207
Surrey cEEGrid sleep data set
EEG Zarr…The data set was previously described in the paper 'Machine-learning-derived…
- Participants
- 20
- Channels
- 6 (other)
- Citations
- 92
- Size
- 69.1 GB
- Version
- v1.0.0
- Updated
- Jun 26, 2026
- on006377
InclusionStudy
NIRSThis dataset contains functional near-infrared spectroscopy (fNIRS) recordings collected to quantify how hair and skin characteristics affect fNIRS signal quality. It was collected to support more inclusive fNIRS research and device design. The data are organized in BIDS format and mirrored from OpenNeuro.
- Participants
- 115
- Size
- 1.38 GB
- Version
- v1.0.0
- Updated
- Jun 18, 2026
- nm000272
Romani et al. 2025 — BrainForm: a Serious Game for BCI Training and Data Collection (P300 ERP, University of Trento)
EEG Zarr…Focus:** BCI training, human factors, machine learning on ERP data ## Participants This…
- Participants
- 22
- Channels
- 8 (10-10)
- HED
- v8.4.0
- Size
- 237 MB
- Version
- v1.0.6
- Updated
- Aug 20, 2026
- nm000167
Motor imagery dataset from Ma et al. 2020
EEG ZarrEEG recordings from 25 healthy, BCI-naive right-handed participants performing motor imagery of two joints of the same limb (right hand and right elbow). Each participant completed 15 sessions over 3 days, giving 600 trials with 62-channel EEG sampled at 1000 Hz plus EOG. The dataset supports research on decoding fine-grained motor imagery within the same limb for motor rehabilitation and prosthetic control BCIs.
- Participants
- 25
- Channels
- 62 (10-10)
- Citations
- 51
- HED
- v8.4.0
- Size
- 53.8 GB
- Version
- v1.0.2
- Updated
- Aug 18, 2026