on003801
Neural Tracking to go
EEG
Imported from OpenNeuro ds003801
- Participants
- 20
- Channels
- 24 (10-10)
- Size
- 1.15 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
Discover datasets
100 results for "multi-class motor imagery" · page 9 of 10 · ranked by relevance
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- on004444
The BMI-HDEEG dataset 1
EEG[
- Size
- 48.4 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on004446
The BMI-HDEEG dataset 2
EEG[
- Size
- 29.2 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on004448
The BMI-HDEEG dataset 4
EEG[
- Size
- 38.2 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- nm000232
THINGS-EEG2: A large and rich EEG dataset for modeling human visual object recognition
EEGTHINGS-EEG2 is a large-scale EEG dataset comprising recordings from 10 subjects viewing 16,540 distinct training images and 200 test images presented via rapid serial visual presentation at 5 Hz. The dataset includes 63-channel EEG data sampled at 1000 Hz across 4 sessions per subject, with approximately 32,540 training trials and 16,000 test trials, designed to support computational modeling of human visual object recognition. Stimuli are drawn from the THINGS database, and the dataset includes resting-state recordings and behavioral annotations for each trial.
- Participants
- 10
- Channels
- 63 (10-10)
- Size
- 198 GB
- Version
- v1.1.0
- Updated
- Jul 10, 2026
- nm000178
BNCI 2020-001 Reach-and-Grasp Electrode Comparison EEG dataset
EEG…self-initiated reach-and-grasp motor imagery tasks using three different recording…
- Participants
- 45
- Channels
- 58 (10-05)
- HED
- v8.4.0
- Size
- 2.08 GB
- Version
- v1.0.1
- Updated
- Jul 10, 2026
- on005795
MULTI-CLARID (Multimodal Category Learning and Resting-state Imaging Data)
ANAT EEG FUNCMULTI-CLARID is a multimodal neuroimaging dataset combining simultaneous fMRI and EEG recordings from participants performing an auditory category learning task and resting-state fMRI. The dataset includes 64-channel EEG (63 head channels plus ECG) with physiological monitoring (EOG, facial EMG, skin conductance), structural MRI (T1-weighted and PD-weighted UTE), and behavioral measures. This resource enables investigation of neural mechanisms underlying category learning and brain functional connectivity. Data were acquired at the Combinatorial NeuroImaging (CNI) core facility of the Leibniz Institute for Neurobiology (LIN) Magdeburg.
- Participants
- 34
- Channels
- 72 (10-10)
- Size
- 6.43 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on002158
Disentangling the origins of confidence in speeded perceptual judgments through multimodal imaging
ANAT EEG FMAP FUNCThis multimodal neuroimaging dataset investigates the neural mechanisms of metacognition—the ability to assess decision confidence—by isolating postdecisional from decisional contributions. Healthy volunteers performed perceptual judgments and observed decisions while reporting confidence, with concurrent electroencephalography and functional magnetic resonance imaging recordings. The study reveals dissociable neural correlates of confidence in prefrontal regions and proposes a computational model explaining how decision commitment enhances metacognitive performance.
- Participants
- 20
- Size
- 423 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on005540
EmoEEG-MC: A Multi-Context Emotional EEG Dataset for Cross-Context Emotion Decoding
BEH EEG…Missing 2 imagery trials (Trials 20 and 21). - **sub57**: Missing 4 imagery…
- Participants
- 60
- Channels
- 64
- Size
- 70.4 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on007162
Adaptive recruitment of cortex-wide recurrence for visual object recognition (EEG)
EEGThis EEG dataset contains neural recordings from 34 participants performing a visual object recognition task using a curated stimulus set of 242 images (121 challenge and 121 control images). Participants viewed sequences of 14 images presented for 200 ms each with 100 ms interstimulus intervals and performed a detection task. The dataset includes time-resolved decoding analyses examining adaptive recruitment of cortical recurrence mechanisms during visual object recognition.
- Participants
- 34
- Channels
- 63 (10-10)
- Size
- 59.6 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026