PhysioNet 2018 Challenge: Sleep Arousal Detection PSG (Training)
…arousal_rera — respiratory effort-related arousal arousal_spontaneous — spontaneous cortical arousal arousal…
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88 results for "cortical networks" · page 7 of 9 · ranked by relevance
…arousal_rera — respiratory effort-related arousal arousal_spontaneous — spontaneous cortical arousal arousal…
A magnetoencephalography dataset from 13 participants performing audiovisual multisensory tasks, including causality judgment, temporal order judgment, and unimodal localizer conditions. The dataset comprises 1500 trials of audiovisual sequences with simultaneous behavioral recordings and structural MRI, designed to investigate neural mechanisms of multisensory correlation computations using time-resolved encoding models.
This magnetoencephalography (MEG) dataset investigates the differential neural mechanisms underlying selection and maintenance of information during working memory tasks. Data from 22 participants include MEG recordings across two sessions, structural MRI, and detailed behavioral measures from a working memory task and a one-back control task involving visual Gabor stimuli. The dataset supports investigation of how the brain selectively maintains task-relevant information while filtering distractions.
…decoding performance using convolutional neural networks (CNN), which yields potential to attain…
…v7.3.2) to reconstruct cortical surfaces and generate boundary element model…
…dataset The data consists of cortical iEEG recordings in 14 epilepsy patients…
A longitudinal motor imagery EEG dataset from 18 brain-computer interface (BCI)-naive subjects acquired across 6 sessions (1 offline + 5 online) to investigate transfer learning and domain adaptation for calibration-free BCI training. Subjects performed left/right hand motor imagery tasks with visual feedback using 22 EEG channels sampled at 512 Hz. The dataset compares Generic Recentering (unsupervised) and Personally Assisted Recentering (supervised) domain adaptation frameworks, with features extracted as covariance matrices and classified using Riemannian geometry-based methods.
Imported from OpenNeuro ds005515
This dataset comprises neuroimaging data from a logical reasoning study conducted by the Cognitive and Computational Neuroscience Laboratory. The study investigates neural correlates of logical reasoning processes through multimodal brain imaging. Data were collected and organized according to BIDS standards for reproducibility and accessibility. This dataset is a NEMAR mirror of the OpenNeuro dataset ds003483.