on006377
InclusionStudy
NIRS
[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on006377-blue…
- Participants
- 115
- Size
- 1.38 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
Discover datasets
100 results for "hybrid neuroimaging" · page 4 of 10 · ranked by relevance
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- nm000177
Multi-session longitudinal motor imagery EEG dataset (Kumar et al. 2024)
EEGA longitudinal motor imagery EEG dataset from 18 brain-computer interface (BCI)-naive subjects acquired across 6 sessions (1 offline + 5 online) to investigate transfer learning and domain adaptation for calibration-free BCI training. Subjects performed cue-based left/right hand motor imagery tasks with visual feedback using 22 EEG channels sampled at 512 Hz. The dataset compares Generic Recentering (unsupervised) and Personally Assisted Recentering (supervised) domain adaptation frameworks, with features extracted as covariance matrices and classified using Riemannian geometry-based methods.
- Participants
- 18
- Channels
- 22 (10-10)
- Citations
- 49
- HED
- v8.4.0
- Size
- 14.4 GB
- Version
- v1.0.3
- Updated
- Aug 18, 2026
- on004796
A Polish Electroencephalography, Alzheimer’s Risk-genes, Lifestyle and Neuroimaging (PEARL-Neuro) Database
EEG FUNC…s Risk-genes, Lifestyle and Neuroimaging (PEARL-Neuro) Database IMPORTANT NOTE: The…
- Participants
- 79
- Citations
- 36
- Size
- 240 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
- nm000220
BEETL Competition 2021 Motor Imagery Dataset A — transfer learning benchmark
EEGBeetl2021-A is a preprocessed motor imagery EEG dataset comprising 63-channel recordings from 3 healthy subjects acquired during an online BCI racing game with four-class motor imagery tasks (rest, left hand, right hand, feet). Sampled at 500 Hz with 1490 total trials, this dataset serves as a benchmark for evaluating transfer learning and domain adaptation methods in brain-computer interfaces, with emphasis on subject independence and cross-dataset generalization.
- Participants
- 3
- Channels
- 63 (10-10)
- Citations
- 2
- HED
- v8.4.0
- Size
- 2.17 GB
- Version
- v1.0.5
- Updated
- Aug 18, 2026
- on007473
High-Density Diffuse Optical Tomography Audiovisual Movie Viewing Dataset
NIRS[. Each subject completed two sessions with 6 runs per session, yielding 200 training and 240 test trials. The dataset features 22 EEG channels plus 3 EOG channels (25 total) sampled at 250 Hz with minimal preprocessing (bandpass filtering 0.05-200 Hz), making it a standard resource for evaluating multi-class motor imagery classification algorithms and cross-session transfer learning approaches.
- Participants
- 9
- Channels
- 22 (10-10)
- Citations
- 90
- HED
- v8.4.0
- Size
- 1.38 GB
- Version
- v1.0.2
- Updated
- Aug 18, 2026
- on007667
Grupos Pre and Post bids
EEGGrupos Pre and Post bids
- Participants
- 55
- Channels
- 19 (10-20)
- Size
- 626 MB
- Version
- v1.0.0
- Updated
- Aug 18, 2026
- nm000115
Zhou2016
EEG- Participants
- 4
- Channels
- 14 (10-10)
- Citations
- 82
- Size
- 152 MB
- Version
- v1.0.0
- Updated
- Jul 10, 2026