39 results for "acute stroke" · page 2 of 4 · ranked by relevance
Imported from OpenNeuro ds003380
This dataset comprises intracranial EEG (iEEG) recordings from 23 patients undergoing stereo-EEG presurgical evaluation for drug-resistant epilepsy, capturing 41 instances of high-frequency cortical stimulation that evoked negative motor responses. Each recording includes pre- and post-stimulation epochs used for connectivity analysis, along with detailed stimulation parameters. The dataset supports research into the cortical networks underlying negative motor phenomena elicited by direct electrical stimulation.
VEPCON is a multimodal neuroimaging dataset comprising high-density EEG, structural MRI, and diffusion-weighted imaging from 20 participants performing visual discrimination tasks (face vs. scrambled faces, coherent vs. incoherent motion). The dataset includes preprocessed EEG single trials, individual brain parcellations at five spatial resolutions, structural connectomes derived from diffusion data, and EEG source imaging solutions based on individual anatomy. This resource supports multimodal methods development, structure-function relationship studies, and optimization of source imaging and graph analysis techniques.
…A comprehensive battery of behavioural and self-report measures captured acute and…
This dataset comprises raw 64-channel EEG, ECG, PPG, and behavioral data collected from 30 healthy young adults during resting-state and verbal working memory tasks. Participants completed a digit-span serial recall task under four stimulus presentation modes (simultaneous, fast, fast+delay, and slow sequential), enabling investigation of neural and physiological correlates of encoding, maintenance, and retrieval. The dataset supports research on working memory load classification and the relationship between oscillatory brain activity, autonomic signals, and behavioral performance.
…brain-computer interface, motor imagery, mental tasks, EEG, CNS tissue damage, stroke…
A code-modulated visual evoked potential (cVEP) brain-computer interface dataset from 30 healthy participants performing an offline BCI task with a calculator grid stimulus. This derivative dataset demonstrates a calibration-free approach that progressively reduces training data requirements, ultimately achieving zero-training performance through neural encoding models while maintaining classification accuracy comparable to traditional event-related potential methods.
A high-density 124-channel EEG dataset comprising event-related potentials (ERPs) from 10 healthy participants during a visual object recognition task. Participants viewed 5,184 photographs from six object categories (human body, human face, animal body, animal face, fruit/vegetable, and inanimate objects), with 72 photographs per category, presented for 500 ms each. The dataset is suitable for investigating neural representations of object categories through single-trial EEG classification and representational similarity analysis.
…six patients recorded intraoperatively using electrocorticography (acute ECoG), six patients with long…