Linguistic features are encoded more strongly during language comprehension than when comprehension is absent, and high word entropy (less constraining context) enhances the encoding of lower-level acoustic and linguistic features while low word entropy suppresses it.

Large-scale replication study with brain potentials challenges the view that people routinely predict the phonological form of a predictable word during language comprehension.

The brain’s projection of linguistic knowledge onto speech is reflected by the automatic, reflexive neural tracking of phrases, while the distribution of phrasal-rate tracking and connectivity, particularly the involvement of inferior frontal cortex, is subject to task demands.

Structural representations of sentences generated by deep language models correlate with human listeners' behaviours and neural activity, providing a quantifiable framework to uncover the neural dynamics underpinning incremental speech comprehension.

Computer code comprehension shares neural resources with formal logical inference in the fronto-parietal network.

The domain-general executive brain regions support the use of a novel cognitive tool even when it is structurally similar to natural language.

Innovative MRI mapping of the auditory pathway reveals that peripheral auditory structure significantly impacts the development of the central auditory-language network in children with profound sensorineural hearing loss, emphasizing the need for early speech input and tailored interventions.

The prediction of specific words is associated with distinct spatial and temporal patterns of neural activity within the left inferior and medial temporal regions before the predicted word is presented.

Blind people re-purpose the brain's visual areas for tracking speech rhythm.

G9a regulates chromatin-bound b-catenin enabling cell-intrinsic control of WNT signaling-mediated cell fate decisions.