Zhou2016
- Participants
- 4
- Channels
- 14 (10-10)
- Citations
- 79
- Size
- 152 MB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
100 results for "Somatosensory Processing" · page 5 of 10 · ranked by relevance
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.
…a multitask EEG dataset for exploring auditory temporal processing with Morse code…
This dataset comprises electroencephalographic (EEG) recordings collected during the presentation of stylized facial stimuli to investigate emotion detection and event-related potentials (ERPs). The study demonstrates that artificially enhanced faces with exaggerated visual features elicit enhanced N170 components compared to standard facial images, suggesting optimized stimulus design can improve neural correlates of emotion recognition. These findings have implications for affective brain-computer interface (BCI) development and emotion detection accuracy from EEG signals. Participant information has been anonymized.
…Effect of obesity on arithmetic processing in preteens with high and low…
…Rotation-tolerant representations elucidate the time course of high-level object processing…
Imported from OpenNeuro ds003801
…varying selective attention and the processing of sensory stimuli with distinct features…
…150 grasping + 100 twisting) Signal Processing ----------------- Classifiers: CSP+RLDA Feature extraction: CSP…
An auditory event-related potential dataset from 13 healthy subjects performing an oddball paradigm with two sinusoidal tones (target 1000 Hz, non-target 500 Hz) presented at variable stimulus onset asynchronies (60-600 ms). The dataset comprises 31-channel EEG recordings at 1000 Hz acquired with BrainProducts BrainAmp DC, designed to evaluate Bayesian optimization strategies for automated selection of individually optimal stimulation parameters in brain-computer interface applications.