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100 results for "sensorimotor learning" · page 8 of 10 · ranked by relevance
[ in healthy adults. The research demonstrates that personalized whole-brain activity patterns can predict human corticospinal tract activation in real-time, with potential applications for brain stimulation therapies. Data includes EEG recordings collected during TMS-guided brain state-dependent stimulation protocols, where TMS serves as the intervention guided by real-time EEG decoding.
…drone control, adaptive learning, difficulty regulation, visuomotor learning - **Environment**: indoor laboratory - **Online…
This dataset comprises simultaneous EEG and fNIRS recordings from 12 participants performing semantic imagery tasks involving silent naming and sensory-based imagination of animals and tools. Participants engaged in visual, auditory, and tactile perception tasks while neural activity was captured using a 64-channel BioSemi EEG system and a NIRx fNIRS imaging system with integrated optodes. The multimodal neuroimaging data supports research in semantic decoding and brain-computer interface applications.
…Cross-user, cross-session generalization - **Transfer learning**: Generic models with user-specific…
…Few-shot learning, transfer learning - **Sequence modeling**: Character-level prediction with attention…
This dataset comprises stereoelectroencephalography (sEEG) recordings from patients performing a forced two-choice response task, collected in the epilepsy monitoring unit at Oregon Health & Science University. The data extends characterization of movement-related neural oscillations using intracranial electrode recordings, providing insights into canonical motor-related activity patterns across distributed brain regions.
Imported from OpenNeuro ds004745
…Sensitive Period of Native Phoneme Learning. International Journal of Environmental Research and…
This dataset comprises multi-subject, multi-modal neuroimaging recordings (structural MRI, MEG, and EEG) collected during a median nerve stimulation paradigm. Participants received electrical stimuli to the right wrist median nerve and responded by lifting their left index finger as quickly as possible. The dataset supports investigation of somatosensory and motor cortical responses using combined MEG/EEG/MRI methodology.