Auditory Gamma Entrainment
Imported from OpenNeuro ds003800
- Size
- 364 MB
- Updated
- May 23, 2026
83 results for "neurolinguistics" · page 3 of 9 · ranked by relevance
Imported from OpenNeuro ds003800
MEG-MASC is a high-quality magnetoencephalography dataset comprising raw MEG recordings from 27 English speakers listening to approximately two hours of naturalistic stories from the Manually Annotated Sub-Corpus (MASC). The dataset includes precise temporal annotations of word and phoneme onsets/offsets, organized according to the Brain Imaging Data Structure (BIDS) standard. This benchmark dataset enables large-scale encoding and decoding analyses of neural responses to natural speech processing, with accompanying code for validation analyses including temporal decoding of phonetic features and word frequency effects.
A multiclass electroencephalography dataset of inner speech commands acquired from ten subjects using a 136-channel system. The dataset includes three experimental paradigms: inner speech, pronounced speech, and visualized conditions, with four directional commands (up, down, right, left) totaling 5,640 trials. This resource addresses the scarcity of publicly available EEG datasets for inner speech recognition and supports the development of brain-computer interface technologies and investigation of neural mechanisms underlying inner speech. Ethics approval: Comité Asesor de Ética y Seguridad en el Trabajo Experimental (CEySTE), CCT-CONICET, Santa Fe.
An EEG dataset of imagined speech from 15 healthy participants comparing traditional cue-based and gamified (Pac-Man maze) paradigms for brain-computer interface applications. The dataset comprises 1,800 trials across four Spanish directional commands recorded at 500 Hz from 24 electrodes using the mBrainTrain Smarting system. This derivative dataset enables systematic evaluation of paradigm design effects on imagined speech decoding performance.
This dataset comprises electroencephalography (EEG) recordings investigating the neural correlates of syntactic structure and lexical properties using frequency tagging methodology. Participants were presented with linguistic stimuli while EEG activity was recorded to identify frequency-specific neural responses associated with different linguistic features. The dataset provides raw neurophysiological data suitable for studying the temporal dynamics of language processing at the neural level.