100 results for "lexical processing" · page 3 of 10 · ranked by relevance
…The primary goal is to advance our understanding of language processing in…
This dataset contains EEG/ERP data from an experiment examining sensitivity to semantic and syntactic violations in deaf readers. Participants read sentences presented word-by-word (RSVP) that contained subject-verb agreement violations, semantic violations, combined violations, word-order violations, or correct control sentences, while EEG was recorded. The study aims to characterize how deaf readers process linguistic anomalies at the neural level.
This dataset comprises behavioral events and intracranial electrophysiological recordings from a categorized free recall task conducted across multiple clinical sites. Participants studied semantically organized word lists (12 items from 3 categories with paired exemplars), performed a distractor task, and freely recalled the words. The dataset includes monopolar and bipolar iEEG recordings with electrode localization information, supporting investigations of memory encoding and retrieval processes.
[. 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.
…the word occurs in | | `is_lexical` | 1 = open-class/content word, 0…
…Participants were exposed to emotionally relevant lexical prompts and were allowed either…
[ recordings and behavioral event data from patients performing a paired associates memory task, collected across multiple clinical sites in collaboration with the Computational Memory Lab at the University of Pennsylvania. Participants studied pairs of words, completed a distractor arithmetic task, and performed cued recall to test memory for word pairs. The dataset supports research into the neural basis of associative memory encoding and retrieval using intracranial recordings.
This dataset contains preprocessed EEG recordings from 6 healthy participants performing imagined speech tasks with three short word conditions (out, in, up). Data were acquired at 256 Hz using 64 channels and analyzed using Riemannian manifold methods and relevance vector machines for brain-computer interface applications. The motor imagery paradigm employed auditory and visual cueing, yielding 5,400 trials suitable for BCI research and benchmarking.