Auditory single word recognition in MEG
…Neurobiology of Language Niso, G., Gorgolewski, K. J., Bock, E., Brooks, T…
- Participants
- 19
- Citations
- 1
- Size
- 11.6 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
95 results for "language models" · page 3 of 10 · ranked by relevance
…Neurobiology of Language Niso, G., Gorgolewski, K. J., Bock, E., Brooks, T…
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 BIDS-reformatted derivative is based on the original data described in Pressel et al. 2016 and supports brain-computer interface research and motor imagery classification studies.
…However, previous evidence supports two seemingly contradictory models of how a predictive…
…Connectionist Temporal Classification (CTC) **Language model**: 6-gram modified Kneser-Ney (trained…
This dataset comprises EEG recordings from 24 participants across two related studies (2019 and 2021) investigating phoneme discrimination during concurrent transcranial magnetic stimulation (TMS) of motor and speech-related cortical regions. Participants listened to speech sounds—including single phonemes, phoneme pairs, and phoneme triplets (real and pseudowords)—and responded via button press, enabling exploration of articulation and coarticulation effects on neural speech decoding. The dataset supports research into cortical mechanisms underlying speech perception and motor cortex involvement in phoneme processing.
…This is a naturalistic auditory language-comprehension paradigm designed to study how…
…associated with subject specific head models. See the corresponding publication for more…
This dataset comprises preprocessed EEG recordings from 8 healthy subjects performing imagined speech tasks involving three vowel phonemes (a, i, u). Participants received auditory and visual cues to imagine speaking each vowel, with 64-channel EEG data acquired at 256 Hz. The dataset includes 2,400 trials generating 7,200 overlapping 2-second epochs (8 subjects × 300 trials × 3 overlapping epochs per trial) analyzed using Riemannian manifold-based feature extraction and relevance vector machine classification for brain-computer interface applications, achieving approximately 49% mean accuracy across a 10-fold cross-validation scheme.
…acoustic encoding and higher-level language or cognitive processing, namely the extraction…
[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on003104-blue…