on005672
PerceiveImagine
EEG
[
- Size
- 4.23 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
Discover datasets
100 results for "visuomotor learning" · page 9 of 10 · ranked by relevance
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- nm000277
Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study G)
EEG[
- HED
- v8.4.0
- Size
- 1.62 GB
- Version
- v1.0.3
- Updated
- Aug 18, 2026
- on002550
Differential brain mechanisms of selection and maintenance of information during working memory (MEG data)
ANAT MEGThis magnetoencephalography (MEG) dataset investigates the differential neural mechanisms underlying selection and maintenance of information during working memory tasks. Data from 22 participants include MEG recordings across two sessions, structural MRI, and detailed behavioral measures from a working memory task and a one-back control task involving visual Gabor stimuli. The dataset supports investigation of how the brain selectively maintains task-relevant information while filtering distractions.
- Participants
- 22
- Size
- 168 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- nm000340
Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study J)
EEG[
- HED
- v8.4.0
- Size
- 1.49 GB
- Version
- v1.0.3
- Updated
- Aug 18, 2026
- on007554
Multimodal dataset from the CMx7-MM Experiment
BEH EEG NIRSThis dataset comprises raw multimodal recordings from 30 healthy right-handed adults performing a hierarchy of cognitive, motor, and combined cognitive-motor tasks across three sessions. Data include EEG, fNIRS, ECG, EMG, torque/kinematic, behavioral (push-button), and subjective (sleepiness, cognitive load) measures, organized according to the BIDS standard. The dataset supports research into neurophysiological correlates of cognitive-motor interactions and dual-task performance.
- Participants
- 30
- Channels
- 32 (10-10)
- Citations
- 1
- Size
- 4.21 GB
- Version
- v1.0.0
- Updated
- Aug 18, 2026
- on003190
Assesment of the visual stimuli properties in P300 paradigm
EEGThis dataset comprises 382 electroencephalographic recordings from 19 participants performing a P300 visual oddball paradigm with systematically varied stimulus properties. Participants completed three experimental sessions, each containing seven recordings with different numbers of visual stimuli (4-9) and flash types (standard flash or cartoon face overlay). EEG data were acquired from eight scalp electrodes at 256 Hz sampling rate, with detailed event markers encoding experimental phases and stimulus presentations.
- Participants
- 19
- Channels
- 9 (10-10)
- Citations
- 3
- Size
- 1.27 GB
- Version
- v1.0.0
- Updated
- Jul 22, 2026
- nm000351
Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study P)
EEG[
- HED
- v8.4.0
- Size
- 4.96 GB
- Version
- v1.0.3
- Updated
- Aug 18, 2026
- on005489
Free Recall with Open-Loop Stimulation at Encoding
BEH iEEGThis dataset contains intracranial EEG recordings and behavioral events from a delayed free recall task with open-loop electrical stimulation delivered during word encoding. Data were collected across multiple clinical sites in collaboration with the Computational Memory Lab at the University of Pennsylvania. Stimulation was applied to single electrodes in the hippocampus or entorhinal cortex during alternating two-word blocks in a subset of study lists, enabling investigation of stimulation effects on memory encoding.
- Participants
- 38
- Size
- 64.9 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
- nm000326
Mainsah et al. 2025 — bigP3BCI: An Open, Diverse and Machine Learning Ready P300-based Brain-Computer Interface Dataset (Study C)
EEG[
- HED
- v8.4.0
- Size
- 4.11 GB
- Version
- v1.0.3
- Updated
- Aug 18, 2026
- on007353
HAD-MEEG
ANAT EEG MEGHAD-MEEG is a magnetoencephalography (MEG) and electroencephalography (EEG) dataset recorded from 30 participants viewing 21,600 video clips spanning 180 categories of human action, extending the previously released Human Action Dataset (HAD) fMRI resource. It was collected in the same participants and with the same stimuli as HAD-fMRI to enable combined spatiotemporal investigation of neural mechanisms underlying human action recognition. The dataset leverages the millisecond-level temporal resolution of M/EEG to complement the spatial precision of fMRI.
- Participants
- 32
- Channels
- 62 (10-10)
- Citations
- 5
- Size
- 221 GB
- Version
- v1.0.0
- Updated
- Aug 18, 2026