nm000154
on001787
EEG
- Participants
- 24
- Channels
- 64
- HED
- v8.4.0
- Size
- 5.69 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
Discover datasets
99 results for "multimodal" · page 8 of 10 · ranked by relevance
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- on005811
NOD-EEG
EEG[
- Citations
- 7
- Size
- 24.3 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
- on004517
EEG recordings for semantic decoding of imagined animals and tools during auditory imagery task
EEGThis dataset comprises 64-channel EEG recordings from 7 participants performing an auditory imagery task, in which they imagined sounds associated with animals and tools following visual stimulus cues. The dataset is intended to support research on semantic decoding of imagined auditory content and brain-computer interface applications.
- Participants
- 7
- Channels
- 64 (10-10)
- Size
- 12.7 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
- on005628
Dataset of Visual and Audiovisual Stimuli in Virtual Reality from the Edzna Archaeological Site
EEGImported from OpenNeuro ds005628
- Participants
- 102
- Channels
- 8 (10-10)
- Citations
- 1
- Size
- 633 MB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on003633
ForrestGump-MEG
ANAT MEG[
- HED
- v8.1.0
- Size
- 43.1 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
- nm000151
Motor imagery dataset for three imaginary states of the same upper extremity
EEG Zarr verifiedThis dataset contains EEG recordings from 12 healthy human subjects performing three-class motor imagery tasks involving the same upper extremity: rest, imagined grasping, and imagined elbow flexion. Data were collected across four sessions per subject using a 32-channel EEG system, and the dataset is a BIDS-formatted derivative of the original study on classifying imaginary motor states using time-domain features. The dataset supports research in brain-computer interfaces (BCI) for motor rehabilitation applications.
- Participants
- 12
- Channels
- 32 (egi-geodesic)
- Citations
- 44
- HED
- v8.4.0
- Size
- 52.0 GB
- Version
- v1.0.3
- Updated
- Aug 20, 2026
- on004587
IllusionGameEEG_data
BEH EEG[
- Size
- 219 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on005540
EmoEEG-MC: A Multi-Context Emotional EEG Dataset for Cross-Context Emotion Decoding
BEH EEGEmoEEG-MC is a multi-context emotional EEG dataset comprising 64-channel EEG and peripheral physiological recordings (PPG, GSR) from 60 participants exposed to video-induced and imagery-induced emotional stimuli. Seven emotion categories (joy, inspiration, tenderness, fear, disgust, sadness, neutral) were evoked and validated through subjective reports, enabling investigation of cross-context emotion decoding. The dataset supports research on neural mechanisms of emotion and generalization of affective computing models across contexts.
- Participants
- 60
- Channels
- 64
- Citations
- 3
- Size
- 70.4 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
- on008257
EEG Moments Dataset (EMD)
EEG[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on008257-blue…
- Participants
- 6
- Size
- 210 GB
- Version
- v1.0.0
- Updated
- Sep 8, 2026