Computational modelling shows that coupled theta and gamma oscillations in the auditory cortex can decompose speech into its syllabic constituents, and organize the neural spiking at faster timescale into a decodable format.

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.

Analysis of speech acoustics and human brain activity reveals the neural computations by which listeners combine speech input with prior expectations.

In light of the mysteries underlying the biphonic nature of Tuvan throat song, information from multiple modalities is combined to explain how this remarkable phenomenon is achieved biomechanically.

Syntactic structure-building processes can be applied to speech that is task-irrelevant and should be ignored, demonstrating that Selective Attention does not fully eliminate linguistic processing of competing speech.

The neural response to natural speech and music processing is mostly shared between the domains, with additional evidence for selectivity in distributed (i.e. not regional) and frequency-specific neural activity.

The human brain has a spatial code for representing temporal phonetic distinctions in speech.

Incidental experiences can lead to lasting category knowledge, demonstrating that humans forage for information to acquire and consolidate new knowledge even when learning is not strictly necessary for success on an ongoing task.