Multimodal EEG and fNIRS Biosignal Acquisition during Motor Imagery Tasks in Patients with Orthopedic Impairment
Imported from OpenNeuro ds004022
- Participants
- 7
- Channels
- 18
- Citations
- 2
- Size
- 635 MB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
100 results for "electrical stimulation mapping" · page 7 of 10 · ranked by relevance
Imported from OpenNeuro ds004022
…M., Carlson T.A. (2024). Mapping the Dynamics of Visual Feature Coding…
A multimodal EEG dataset comprising motor imagery and motor execution data from 25 healthy subjects performing 11 intuitive upper-limb movement tasks (6 reaching, 3 grasping, 2 wrist twisting) across 3 sessions. The dataset includes 71-channel EEG recordings (60 EEG, 4 EOG, 7 EMG channels) sampled at 1000 Hz with synchronized behavioral annotations, designed for brain-computer interface research and motor control applications. This is a BIDS-formatted derivative dataset converted from the original Jeong et al. 2020 publication using MOABB (Mother of All BCI Benchmarks).
…type=gray arrow on black background, direction_mapping=downward=feet, leftward=left…
…excluded all electrode contacts where electrical stimulation evoked motor or language responses…
…because the per-block paradigm mapping > is not explicitly enumerated in Langer…
This dataset comprises intracranial EEG (iEEG) recordings collected by the Hamilton Lab at the University of Texas at Austin, compiled as a teaching resource for the WIRED ICM course in Paris, 2024. It includes evoked responses to naturalistic auditory stimuli, such as movie trailers and TIMIT speech corpus sentences, alongside illustrative examples of seizure activity and vagus nerve stimulator (VNS) artifact. The dataset is intended to demonstrate typical and atypical intracranial recording phenomena in patients with epilepsy.
…Culver; Functional brain mapping using whole-head very high-density diffuse optical…
This dataset contains electroencephalogram (EEG), galvanic skin response (GSR), and electrocardiogram (ECG) recordings from 19 healthy adult participants during a calibration session of an affective brain-computer music interface system. Participants listened to 40-second synthetic music clips designed to induce specific affective states defined by valence and arousal dimensions across 5 runs of 18 trials each. The synthetic music was generated in real-time based on target emotional states and could be modified online to induce target emotional states. The dataset includes self-reported affective state ratings and auxiliary variables, serving as calibration data for the brain-computer music interface system. This dataset is part of a three-dataset collection that includes offline training and online real-time control sessions.
…Each word is assigned a unique key to enable mapping fixated words…