71 results for "neurolinguistics" · page 1 of 8 · ranked by relevance
…the University of Michigan Computational Neurolinguistics Lab (CNL Lab). Events and Linguistic…
This event-related potential (ERP) study investigates semantic and syntactic language processing in deaf readers by examining neural responses to grammatical violations and semantic anomalies. Participants viewed 180 sentences presented in rapid serial visual presentation (RSVP) format while EEG was recorded, with conditions including subject-verb agreement violations, semantic violations, combined violations, word-order violations, and correct control sentences. The research provides insights into the neural mechanisms underlying language comprehension in deaf populations.
…Data were collected in the “spazio EEG” at the Laboratory of Neurolinguistics…
NeuroMorph is a high-temporal resolution magnetoencephalography (MEG) dataset comprising recordings from 24 subjects totaling over 17 hours of data acquired using a KIT/Yokogawa system with 208 magnetometer channels. The dataset is designed to support morpheme-based linguistic analysis and investigation of language and cognitive processes through visual presentation paradigms, providing a resource for studying neural mechanisms of language processing at fine temporal resolution.
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.
This dataset comprises EEG recordings from healthy adults listening to naturalistic speech segments from an audiobook. Brain activity was recorded using a 128-channel ActiveTwo EEG system while subjects listened to passages from "The Old Man and the Sea," with concurrent phoneme and word-level timing annotations. The unfiltered, unreferenced recordings sampled at 512 Hz provide raw neural responses to continuous speech stimuli for investigating cortical entrainment and speech comprehension mechanisms.
This dataset comprises EEG recordings from 10 healthy participants performing a P300 speller task using a 6×6 character matrix. The study compares two stimulus conditions—famous faces and inverting—to evaluate their effects on online P300 classification performance using language models. Data were collected across 2 sessions per subject with 3 runs per session, sampled at 256 Hz from 32 EEG channels.
3M-CPSEED is an EEG dataset comprising recordings from 20 native Chinese speakers performing overt, silently articulated, and imagined speech tasks using Chinese Pinyin phonemes. The dataset captures neural activity across 6 initials (m, f, j, l, k, ch) and 4 finals (a, i, u, ü), with 1600 trials per participant. This resource supports investigation of neural mechanisms underlying speech production.
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.
EEG dataset containing recordings from participants engaged in natural conversation. The dataset includes raw EEG data collected during spontaneous speech interactions, designed to investigate neural correlates of communication and language processing. Data were acquired using standard EEG recording protocols and include multiple channels of continuous EEG activity synchronized with behavioral and linguistic annotations.