93 results for "somatosensory cortex" · page 3 of 10 · ranked by relevance
Imported from OpenNeuro ds003380
NOD-EEG provides electroencephalography (EEG) recordings collected from the same subjects and using the same naturalistic ImageNet stimuli as the previously published NOD-fMRI dataset, extending the Natural Object Dataset (NOD) to include temporal dynamics of visual object recognition. Combined with companion MEG data, this multimodal resource enables investigation of neural mechanisms underlying object recognition across naturalistic scenes with both high spatial and high temporal resolution. The dataset includes raw and preprocessed EEG time series and epoched data, along with detailed trial-level event metadata.
…DLPFC; dorsolateral pre-frontal cortex, OFC; orbitofrontal cortex, PPC; posterior parietal cortex…
This dataset contains whole-brain EEG recordings from participants experiencing tactile stimulation and viewing videos of touch to investigate overlapping neural representations between firsthand and vicarious touch. Using time-resolved multivariate pattern analysis, the study examines whether observed touch evokes similar neural patterns as direct tactile experience. The dataset includes 64-channel EEG data collected at 2048 Hz from 12 experimental runs comprising 1728 trials across tactile and visual conditions.
…the prefrontal cortex (PFC), sensory motor cortices, and posterior parietal cortex (PPC…
…dataset focus on the prefrontal cortex activity in fourteen types of highly…
Imported from OpenNeuro ds004022
[ research. The dataset was reorganized into BIDS format from an original OpenNeuro dataset to support reproducible MEG analysis workflows across multiple research sites.
This dataset contains electroencephalography (EEG) recordings collected during reactive balance perturbations to investigate cortical contributions to feedback-driven sensorimotor control. The data support analyses of how specific cortical regions contribute to reactive postural responses following balance disturbances. It is intended to inform understanding of the neural mechanisms underlying balance control and their potential relevance to rehabilitation research.