Neurobiology of Language and Bilingualism

The paper shows low-frequency neural activity reflects context-dependent parsing of word sequences, tracking sentences rather than individual words.

The paper investigates how conscious and unconscious perception of pitch shifts in auditory feedback during vocalization affects vocal responses and neural activity.

This study investigates how the brain encodes auditory word forms in speech processing, finding distinct neural resets at word boundaries and temporal scaffolding for variable word lengths.

The paper identifies a left-lateralized dorsolateral prefrontal network involved in semantic processing during word retrieval using ECoG data from patients.

This paper reanalyzes N400 data using semantic cloze instead of lexical cloze, finding semantic cloze better predicts N400 amplitude than lexical cloze or LLM-derived probabilities.

The paper models EEG responses to natural speech, showing predictable words are processed faster with earlier and smaller N400-like responses.

The paper re-analyzes fMRI data to identify brain regions and operations involved in semantic composition, finding compositional representations in BA45 and the left middle superior temporal sulcus.

The paper investigates how neural trajectories in latent spaces underpin natural language composition, revealing distinct coding strategies and syntactic relations in human neocortical responses.

The paper investigates how abstract and concrete verbs are processed in the brain, finding that all abstract verb types engage the vATL except mental state verbs, and that different verb types activate distinct ATL clusters.

The paper shows that neural patterns in novice sign language learners correlate with semantic features of newly learned ASL signs, indicating early integration of new vocabulary into existing semantic networks.

The paper investigates how 'what' and 'when' predictions interact in speech processing using MEG, finding that their integration is mediated by a shared cortical network rather than separate hierarchies.

This study uses deep learning models to analyze neural activity during conversation, showing distributed and context-dependent patterns for speech production and comprehension.

The paper introduces a naturalistic neuroimaging dataset with EEG and 7T fMRI recordings from 26 Mandarin speakers listening to single- and multi-talker speech, enabling research on attention and auditory processing in complex environments.

The paper uses MEG data and a machine learning approach to investigate causal connectivity between inferior frontal gyrus and temporal areas during semantic prediction, finding significant feedback effects.

This study investigates how the brain hierarchically represents linguistic predictions during narrative comprehension using NLP and fMRI, finding that sentence-level predictions update at boundaries rather than continuously.

This study links multilingual phonological experience to cortical thickness in auditory brain regions, showing that more diverse language exposure correlates with thinner second transverse temporal gyrus.

The paper visualizes functional and effective connectivity in white matter networks during auditory descriptive naming tasks, showing how phrase order influences neural dynamics.

The paper shows that constructed languages activate the same brain regions as natural languages, suggesting shared cognitive mechanisms regardless of their creation or usage characteristics.

The paper identifies spatial and temporal distributions of semantic, articulatory, and acoustic speech representations in the brain using intracranial data from 15 participants.

This paper shows that pre-onset brain encoding in language processing can be explained by stimulus dependencies rather than neural prediction.

This study uses neural decoding to show that the brain reactivates the syntactic head of a phrase during comprehension, revealing temporal dynamics linked to linguistic composition.

This study identifies a premotor frontal cortex network involved in inhibitory control of speech, showing distinct neural activity for stopping speech compared to speech production.

The paper uses EEG to study neural mechanisms of speech production by decoding auditory speech output under different masking conditions, finding consistent decoding in instantaneous and feedback lags.

The paper introduces a naturalistic neuroimaging dataset with EEG and 7T fMRI recordings from 26 Mandarin speakers listening to single- and multi-talker speech, enabling research on attention and auditory processing in complex environments.

This study simulates aphasia in large language models by disrupting components to explore modularity in language processing and its parallels with human systems.

This study decodes lexical semantic information from natural speech using intracranial EEG in participants during spontaneous conversation, achieving 21% accuracy.

This study investigates whether symmetric semantic information is represented symmetrically in the human brain using fMRI data from movie-evoked responses.

This study investigates how reliable social feedback affects language learning using EEG and pupillometry, finding that social feedback enhances learning and alters neural responses compared to symbolic feedback.