Perturbed beam-walking task
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100 results for "neurophysiological biomarkers" · page 9 of 10 · ranked by relevance
[ totaling 5,640 trials. This resource addresses the scarcity of publicly available EEG datasets for inner speech recognition and supports the development of brain-computer interface technologies and investigation of neural mechanisms underlying inner speech. Ethics approval: Comité Asesor de Ética y Seguridad en el Trabajo Experimental (CEySTE), CCT-CONICET, Santa Fe.
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A motor imagery EEG dataset comprising 31 healthy participants performing left and right hand grasping imagery tasks across multiple sessions. The dataset includes 2,520 trials recorded at 1000 Hz using a 64-channel Neuroscan system with standardized electrode montage, designed for brain-computer interface research and motor control applications.
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BigP3BCI Study Q is a P300-based brain-computer interface dataset comprising EEG recordings from 36 ALS subjects across 3 sessions each, using a 6x6 color intensification speller paradigm. The dataset contains 32-channel EEG data sampled at 256 Hz with standardized 10-20 electrode montage, annotated with target and non-target event labels for machine learning applications. This derivative dataset is part of the larger BigP3BCI collection, the largest public P300 BCI dataset with recordings from approximately 267 subjects across 20 studies.
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This dataset contains intracranial electrophysiology recordings and behavioral data from a delayed free recall task with real-time closed-loop brain stimulation during encoding. Participants studied word lists, performed distractor arithmetic tasks, and freely recalled words while an L2 logistic regression classifier trained on encoding neural features guided stimulation delivery to optimize memory performance. Data were collected across multiple clinical sites as part of a collaborative memory research initiative.
This dataset comprises intracranial EEG recordings from five patients undergoing single-pulse electrical stimulation of temporal and limbic circuitry at Mayo Clinic. The study investigates Basis Profile Curve identification and distinct neural responses evoked in human ventral temporal cortex through direct brain stimulation, providing insights into functional connectivity and processing speed within the human connectome.
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