ERC_CoG PROMENADE - WP2 - MetaImagery (Metaphor and Mental Imagery)
…Our aim was to test whether the mental representation generated by four…
- Participants
- 39
- Channels
- 58 (10-10)
- Size
- 14.8 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
98 results for "semantic representation" · page 4 of 10 · ranked by relevance
…Our aim was to test whether the mental representation generated by four…
A synchronized multimodal neuroimaging dataset containing concurrent fMRI and MEG recordings from 12 Mandarin Chinese speakers during naturalistic story listening, supplemented with high-resolution structural imaging, diffusion MRI, and resting-state fMRI. The dataset includes rich linguistic annotations of stimuli encompassing word frequencies, syntactic structures, temporal alignments, and embeddings from multiple pre-trained language models, enabling comprehensive investigation of neural mechanisms underlying language processing.
NeuroMorph is a high-temporal resolution MEG dataset designed for morpheme-based linguistic analysis, comprising recordings from 24 subjects totaling over 17 hours of data. Data were collected using a KIT/Yokogawa MEG system to investigate visual language and cognitive processing, with a focus on morphological structure in written language comprehension.
…Parallel processing in speech perception with local and global representations of linguistic…
THINGS-EEG2 is a large-scale EEG dataset comprising recordings from 10 subjects viewing 16,540 distinct training images and 200 test images presented via rapid serial visual presentation at 5 Hz. The dataset includes 63-channel EEG data sampled at 1000 Hz across 4 sessions per subject, with approximately 32,540 training trials and 16,000 test trials, designed to support computational modeling of human visual object recognition. Stimuli are drawn from the THINGS database, and the dataset includes resting-state recordings and behavioral annotations for each trial.
This dataset comprises preprocessed EEG recordings from 6 healthy participants performing imagined speech tasks, specifically discriminating between short and long words ('cooperate' vs 'in'). Data were acquired at 256 Hz using 64 EEG channels and processed with bandpass filtering (8-70 Hz), notch filtering (60 Hz), and artifact removal. The dataset contains 1,200 trials. Classification results (mean accuracy 73.3±8.9%) reported in the original Nguyen et al. 2017 study are provided for reference.
…word generation and word selection * Semantic similarity measures between consecutive words ## Experimental…
This dataset comprises EEG recordings collected using a Visual Attribute-Specific Contextual Trajectory Paradigm, designed to investigate visual attention and perceptual processing of moving stimuli. It provides raw electrophysiological data intended to support research into contextual and attribute-specific visual trajectory processing in humans.
…the dynamic decision process of semantics and preference choices in the human…
This dataset comprises intracranial EEG recordings and behavioral events from a paired-associates memory task incorporating open-loop electrical stimulation at either encoding or retrieval. Participants studied word pairs, performed an arithmetic distractor task, and completed cued recall, with stimulation applied to hippocampal or entorhinal cortex electrodes on a subset of lists. Data were collected across multiple clinical sites in collaboration with the University of Pennsylvania Computational Memory Lab, and represent an open-loop stimulation variant of the PAL1 dataset.