The BMI-HDEEG dataset 2
…High-density scalp electroencephalogram dataset during sensorimotor rhythm-based brain-computer interfacing…
- Size
- 29.2 GB
- Updated
- Jun 24, 2026
100 results for "brain connectivity" · page 10 of 10 · ranked by relevance
…High-density scalp electroencephalogram dataset during sensorimotor rhythm-based brain-computer interfacing…
…High-density scalp electroencephalogram dataset during sensorimotor rhythm-based brain-computer interfacing…
…EEG was recorded with a 64-channel BrainVision cap. Resting-state EEG…
This dataset comprises EEG recordings from 15 healthy participants performing self-initiated reach-and-grasp motor tasks using three different recording systems: gel-based laboratory equipment, water-based mobile EEG, and dry-electrode mobile EEG. Data were acquired at 256 Hz from 58 EEG channels plus 6 EOG channels across three sessions with a total of 7,200 trials. Participants executed palmar and lateral grasp actions toward objects while EEG signals were recorded. The study investigates the feasibility of decoding natural reach-and-grasp neural correlates across different EEG acquisition modalities for brain-computer interface applications.
…Surface electroencephalography is a standard and noninvasive way to measure electrical brain…
…EEG-BIDS, an extension to the brain imaging data structure for electroencephalography…
…brain-computer interface, motor imagery, EEG, Riemannian geometry, asynchronous BCI, brain-switch…
This dataset comprises simultaneous EEG and fMRI recordings from 33 healthy human participants during sleep and wakefulness. The study captures coordinated electrophysiological and hemodynamic signals using a 32-channel MR-compatible EEG system synchronized with BOLD fMRI acquisition. The experimental protocol includes anatomical imaging, resting-state sessions before and after a visual-motor adaptation task, and multiple sleep sessions with corresponding sleep stage annotations. EEG signals provide direct measures of electrophysiological activity and sleep stage information, while fMRI captures hemodynamic responses, enabling investigation of the relationship between neural activity during sleep-wake transitions.