Hybrid EEG-fNIRS MI dataset for ICH from Shi et al 2025
- Participants
- 37
- Channels
- 32 (10-10)
- HED
- v8.4.0
- Size
- 2.59 GB
- Version
- vv1.0.0
- Updated
- Jul 10, 2026
100 results for "brain-computer interface" · page 10 of 10 · ranked by relevance
…relevance vector machines for brain-computer interface applications, achieving mean classification accuracy…
…vector machine approaches for brain-computer interface applications, achieving mean classification accuracy…
…Open access dataset for hybrid brain-computer interfaces (BCIs) using electroencephalography (EEG…
This dataset comprises intracranial EEG recordings and single-unit neuronal activity from the human amygdala of nine epilepsy patients during exposure to dynamic visual stimuli with aversive (fearful faces) and neutral (landscape) content. The recordings enable investigation of amygdalar responses to emotional stimuli across multiple spatial scales, from macroscopic field potentials to microscopic neuronal firing patterns. Data are provided in BIDS format with extended neuronal spike data available in NIX standard.
…A generic non-invasive neuromotor interface for human-computer interaction. Nature, 645…
…Brain–computer interface, P300, Disabled subjects, Fisher's linear discriminant analysis, Bayesian…
Imported from OpenNeuro ds002718
This 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.
Imported from OpenNeuro ds004661