EEG recordings for semantic decoding of imagined animals and tools during auditory imagery task
…Using data from cue presentations results in grossly overestimating semantic BCI performance…
- Size
- 12.7 GB
- Updated
- Jun 24, 2026
27 results for "semantic conditioning" · page 2 of 3 · ranked by relevance
…Using data from cue presentations results in grossly overestimating semantic BCI performance…
This dataset comprises neuroimaging data from a logical reasoning study conducted by the Cognitive and Computational Neuroscience Laboratory. The study investigates neural correlates of logical reasoning processes through multimodal brain imaging. Data were collected and organized according to BIDS standards for reproducibility and accessibility. This dataset is a NEMAR mirror of the OpenNeuro dataset ds003483.
This dataset comprises intracranial electrophysiological recordings and behavioral data from a paired associates memory task with open-loop electrical brain stimulation applied during encoding or retrieval phases. Participants studied word pairs, performed a distractor task, and completed cued recall, with stimulation delivered to hippocampal and entorhinal cortex electrodes on randomly assigned lists. The dataset enables investigation of how targeted electrical stimulation affects memory encoding and retrieval processes.
…Using data from cue presentations results in grossly overestimating semantic BCI performance…
…the dynamic decision process of semantics and preference choices in the human…
This dataset contains neural recordings investigating the brain's representation of consciously perceived versus unconsciously processed visual information. The study examines how neural activity differs when identical visual stimuli are either consciously seen or remain outside conscious awareness, providing insights into the neural correlates of consciousness and visual perception.
…The picture and word could be phonologically related, semantically related, or unrelated…
This derivative dataset contains processed MEG data from a study investigating the neural mechanisms of model-based aversive learning in humans. The research examines how task state representations are preferentially reactivated during aversive learning, providing insights into the computational and neural basis of threat-related decision-making and learning processes.
…word generation and word selection * Semantic similarity measures between consecutive words ## Experimental…
…The word lists in this paradigm follow a specific semantic construction. Each…