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.

The comprehension of acoustic and visual speech depends on modality-specific pathways in the brain, which explains why auditory speech abilities and lip reading are not associated in typical adults.

Hidden Markov Modeling to fMRI data reveals how language comprehension arises from the dynamic interplay of large-scale brain networks.

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.

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.

Rhythms of lip movements entrain low-frequency brain oscillations and facilitate audiovisual speech processing.

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

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.

Human electroencephalography reveals that neural speech tracking is enhanced by minimal background noise and that this enhancement is independent of attention and generalizes across noise types and sound-delivery systems.