on004447
The BMI-HDEEG dataset 3
EEG
…High-density scalp electroencephalogram dataset during sensorimotor rhythm-based brain-computer interfacing…
- Participants
- 22
- Size
- 20.7 GB
- Version
- v1.0.0
- Updated
- Jun 24, 2026
Discover datasets
100 results for "task-based neurophysiology" · page 7 of 10 · ranked by relevance
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- on004444
The BMI-HDEEG dataset 1
EEG…High-density scalp electroencephalogram dataset during sensorimotor rhythm-based brain-computer interfacing…
- Participants
- 30
- Size
- 48.4 GB
- Version
- v1.0.0
- Updated
- Jun 24, 2026
- on002338
A multi-modal human neuroimaging dataset for data integration: simultaneous EEG and fMRI acquisition during a motor imagery neurofeedback task: XP2
ANAT EEG FUNCThis dataset comprises simultaneous 64-channel EEG and 3T fMRI recordings from 16 subjects performing motor imagery and neurofeedback tasks. Participants were randomly assigned to receive either mono-dimensional or bi-dimensional neurofeedback displays during five experimental runs with alternating rest and task blocks. The dataset includes raw EEG data in Brain Vision format, preprocessed EEG data, BOLD fMRI acquisitions, computed neurofeedback scores from both modalities (EEG and fMRI), and event timing files, providing a comprehensive resource for multimodal neuroimaging data integration studies.
- Participants
- 17
- Size
- 25.9 GB
- Version
- v1.0.0
- Updated
- Jun 21, 2026
- on004446
The BMI-HDEEG dataset 2
EEG…High-density scalp electroencephalogram dataset during sensorimotor rhythm-based brain-computer interfacing…
- Participants
- 30
- Size
- 29.2 GB
- Version
- v1.0.0
- Updated
- Jun 24, 2026
- on004448
The BMI-HDEEG dataset 4
EEG…High-density scalp electroencephalogram dataset during sensorimotor rhythm-based brain-computer interfacing…
- Participants
- 56
- Size
- 38.2 GB
- Version
- v1.0.0
- Updated
- Jun 24, 2026
- on006386
PhysioMotion_Artifact
EEGPhysioMotion_Artifact is an electrophysiological dataset organized in BIDS format containing EEG recordings with associated physiological motion artifacts. The dataset serves as a resource for studying and developing artifact detection and correction methods in EEG analysis, with potential applications in motor imagery and brain-computer interface research.
- Participants
- 30
- Citations
- 1
- Size
- 36.2 GB
- Version
- v1.0.0
- Updated
- Jun 28, 2026
- on004844
T22
EEG…Predicting and influencing trust-based decisions about control authority hand-off and…
- Participants
- 17
- Size
- 22.3 GB
- Version
- v1.0.0
- Updated
- Jun 25, 2026
- nm000343
Hinss et al. 2021 — Open multi-session and multi-task EEG cognitive Dataset for passive brain-computer Interface Applications
EEGThis dataset comprises multi-session, multi-task EEG recordings from 15 healthy participants performing resting state and graded difficulty levels of the MATB-II task. Acquired at 500 Hz using 62 active electrodes, the dataset includes 90 trials per participant across two sessions and is designed to support passive brain-computer interface applications and mental workload estimation in neuroergonomic contexts. The dataset is in raw, unpreprocessed state and has been formatted according to BIDS standards for accessibility and reproducibility.
- Participants
- 15
- Citations
- 61
- Size
- 1.22 GB
- Version
- v1.0.1
- Updated
- Jun 3, 2026
- on004262
Continuous Feedback Processing
BEH EEG…Points were awarded based on the distance between their guess and the…
- Participants
- 21
- Size
- 3.47 GB
- Version
- v1.0.0
- Updated
- Jun 23, 2026
- on005931
Visuomotor_task
iEEGThis dataset comprises intracranial electroencephalography (iEEG) recordings from ten epilepsy patients performing a visuomotor task (Speed Match) during interictal periods. The dataset includes continuous iEEG data across five sessions per subject, with detailed channel information and trial timing annotations. This resource provides a unique opportunity to investigate neural correlates of visuomotor processing in patients with implanted electrodes for seizure localization.
- Participants
- 8
- Size
- 817 MB
- Version
- v1.0.0
- Updated
- Jun 28, 2026