Article

Linguistic inputs must be syntactically parsable to fully engage the language network

2024-06-22

Abstract excerpt

Human language comprehension is remarkably robust to ill-formed inputs (e.g., word transpositions). This robustness has led some to argue that syntactic parsing is largely an illusion, and that incremental comprehension is more heuristic, shallow, and semantics-based than is often assumed. However, the available data are also consistent with the possibility that humans always perform rule-like symbolic parsing and...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 7586b3c9-0f67-5558-9052-9f078ce23b03
DOI: 10.1101/2024.06.21.599332

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Linguistic inputs must be syntactically parsable to fully engage the language networkDOI 10.1101/2024.06.21.599332Read

The neural architecture of language: Integrative modeling converges on predictive processingSemantic proximity Read

Shared functional specialization in transformer-based language models and the human brainSemantic proximity Read

Robust effects of working memory demand during naturalistic language comprehension in language-selective cortexSemantic proximity Read

Evidence from Formal Logical Reasoning Reveals that the Language of Thought is not Natural LanguageSemantic proximity Read

Reorganization of the neurobiology of language after sentence overlearningSemantic proximity Read

Abstract rule generalization for composing novel meaning recruits the frontoparietal control networkSemantic proximity Read

Neural evidence for the prediction of animacy features during language comprehension: Evidence from MEG and EEG Representational Similarity AnalysisSemantic proximity Read

Language processing in brains and deep neural networks: computational convergence and its limitsSemantic proximity Read

Languages of the brain: fMRI dissection of the amodal networks for language, mathematics, and social knowledgeSemantic proximity Read

Neurocognitive Mechanisms Supporting the Generalization of Concepts Across LanguagesSemantic proximity Read

Temporal Dissociation of Syntactic Disambiguation and Memory Retrieval during Sentence Processing: Naturalistic MEG Evidence from Interpretable ModelsSemantic proximity Read

fMRI reveals language-specific predictive coding during naturalistic sentence comprehensionSemantic proximity Read