100 results for "verbal memory" · page 7 of 10 · ranked by relevance
…Examining Perceptual Grouping on Stages of Processing in Visual Working Memory: An…
This dataset comprises 64-channel EEG recordings and behavioral ratings from 4 participants (P105, P141, P142, P146; anonymized as sub-001 to sub-004 in BIDS format) who evaluated 210 short English-language texts (70 Haiku, 70 Senryu, and 70 control texts) on five subjective dimensions: Aesthetic Appeal, Vivid Imagery, Being Moved, Originality, and Creativity. IMPORTANT: These 4 participants were EXCLUDED from primary analyses due to segmented EEG recordings acquired in multiple sessions and subsequently concatenated during preprocessing, which introduced potential artifacts. This is a companion dataset to Poetry Assessment EEG Dataset 1 (47 participants with validated continuous recordings used in primary analyses). Poetry Assessment EEG Dataset 2 is included for completeness and transparency, enabling users to apply their own quality control pipelines if desired. The dataset includes resting-state EEG (trigger codes: 65285, 65286 for pre-experiment; 65287, 65288 for post-experiment), trial-by-trial behavioral ratings, and psychometric responses (PANAS, Openness, Curiosity, VVIQ, AVIQ, MAAS, AReA), enabling investigation of neural correlates of aesthetic and creative cognition during poetic language processing. All preprocessing steps, event markers, and metadata structures were applied identically across both Poetry Assessment EEG datasets.
Visual working memory in control & sub-acute mild TBI. Mind wandering probes…
An open-access EEG dataset containing recordings from 15 healthy Spanish-speaking subjects performing imagined speech tasks. The dataset comprises 11 imagery classes (5 Spanish vowels and 6 directional commands) acquired using 6-channel EEG at 1024 Hz with preprocessed data (bandpass filtered 2-45 Hz). This resource supports brain-computer interface research and motor imagery classification studies.
…Motor control processes moderate visual working memory gating. The Journal of Neuroscience…
Brain Treebank is a large-scale intracranial EEG dataset comprising 43 hours of iEEG recordings from 10 epilepsy patients watching naturalistic Hollywood movies, with 1,688 electrodes sampled at 2048 Hz. The dataset includes time-aligned linguistic annotations with word-level transcripts and Universal Dependencies syntax trees, providing a unique resource for studying neural language processing during naturalistic stimulation.
…Participants were instructed to verbally report the perceived pain intensity of each…
A large-scale multi-laboratory replication study (N=356 participants across 9 UK institutions) investigating probabilistic prediction in language comprehension using event-related potentials. Participants read sentences word-by-word while EEG was recorded, with critical manipulations of indefinite articles (a/an) preceding expected or unexpected nouns. The study challenges strong prediction accounts by demonstrating reliable N400 effects on target nouns but not on preceding articles, contrary to the original DeLong et al. (2005) findings.
This event-related potentials (ERP) study investigates cognitive conflict during moral judgment of accidental harm using EEG recordings from 31 participants. Participants performed a combined semantic and moral judgment task, evaluating scenarios involving intentional or accidental harm while making congruency judgments about target words. The orthogonal manipulation of agent intention and semantic congruency across four conditions enables examination of how moral and semantic processing interact in the brain.
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.