BNCI 2019-001 Motor Imagery dataset for Spinal Cord Injury patients
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- Aug 18, 2026
97 results for "cortical plasticity" · page 10 of 10 · ranked by relevance
[ recordings collected while participants viewed validated emotional video stimuli. It comprises three components: a large-scale online behavioral survey of 500 participants rating 40 video clips, head digitization data for co-registration, and MEG neural recordings from 23 participants viewing the same stimuli. Emotional states were assessed using Self-Assessment Manikin ratings, discrete emotion categories (PrEmo), and temporal highlight annotations, providing multi-faceted ground truth for affective neuroscience research.
This dataset comprises human electroencephalography recordings from 20 participants performing a visual attention task involving rapid sequences of overlaid oriented gratings. Participants detected target gratings while manipulating both attention (cued by color) and temporal expectation (predictable vs. unpredictable stimulus onset timing). The study dissociates feature-based attention effects from temporal expectation and target-related decision processes, providing insights into the temporal dynamics of selective attention.
This dataset contains magnetoencephalography (MEG) and structural magnetic resonance imaging (MRI) data from adolescent participants with major depressive disorder and healthy controls during a monetary gambling mood induction task and resting state. The study investigates electrophysiological correlates of mood and reward dynamics in human adolescents through pre-registered analyses of task-based and resting-state neuroimaging data.
A synchronized multimodal neuroimaging dataset containing concurrent fMRI and MEG recordings from 12 Mandarin Chinese speakers during naturalistic story listening, supplemented with high-resolution structural imaging, diffusion MRI, and resting-state fMRI. The dataset includes rich linguistic annotations of stimuli encompassing word frequencies, syntactic structures, temporal alignments, and embeddings from multiple pre-trained language models, enabling comprehensive investigation of neural mechanisms underlying language processing.
This dataset contains MEG recordings from a study investigating how the human brain compresses regular binary sound sequences in working memory, testing the language of thought hypothesis. Participants listened to hierarchically structured sequences of two sounds varying in complexity, quantified via minimal description length, while occasional deviant sounds probed their internalized knowledge of sequence structure. The study aimed to characterize how brain activity relates to sequence complexity and predictive processing.
This dataset contains intracranial electrophysiological (iEEG) recordings and behavioral event data from patients performing a paired associates memory task, collected across multiple clinical sites in collaboration with the Computational Memory Lab at the University of Pennsylvania. Participants studied pairs of words, completed a distractor arithmetic task, and performed cued recall to test memory for word pairs. The dataset supports research into the neural basis of associative memory encoding and retrieval using intracranial recordings.