18 results for "cerebral ischemia" · page 1 of 2 · ranked by relevance
Imported from OpenNeuro ds003380
Imported from OpenNeuro ds007315
[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on005776-blue…
Imported from OpenNeuro ds002778
…of Hermes et al., 2015, Cerebral Cortex "Stimulus Dependence of Gamma Oscillations…
This dataset comprises electroencephalography (EEG) recordings from 50 acute stroke patients (1-30 days post-stroke) performing motor imagery tasks of left- and right-handed hand-grip movements. Recorded using a wireless 29-channel EEG system at 500 Hz, the dataset includes raw and preprocessed data, representing the first open resource addressing left- and right-handed motor imagery in the acute stroke population. The dataset supports brain-computer interface (BCI) algorithm development and clinical rehabilitation applications.
…4 disabled (cerebral palsy, multiple sclerosis, late-stage amyotrophic lateral sclerosis, traumatic…
This dataset contains de-identified resting-state EEG recordings from individuals with Parkinson's disease and age-matched healthy controls, collected to investigate whether EEG signals can predict mortality outcomes. Each subject is labeled as either 'living' or 'deceased' in the participants file, with no additional demographic or clinical information provided. The dataset is intended to support research on EEG biomarkers of mortality risk and machine learning classification approaches in Parkinson's disease populations.
…Wolff & Brechmann, Cerebral Cortex, 2023) because of the copyright policy of OpenNeuro…
A derivative EEG dataset containing checkerboard m-sequence-based code-modulated visual evoked potential (c-VEP) recordings from 16 healthy participants across 8 sessions. This dataset is derived from the source dataset by Martínez-Cagigal et al. (2025) (DOI: 10.71569/7c67-v596) and is described in the publication by Fernández-Rodríguez et al. (2023) in Frontiers in Human Neuroscience. The dataset evaluates the influence of spatial frequency in visual stimuli for brain-computer interface applications, with 16-channel EEG data sampled at 256 Hz during a two-class visual stimulation paradigm.