Large language models (LLMs) have come closest among all models to date to mastering
human language, yet opinions about their linguistic and cognitive capabilities remain split …

Abstract Language behaviour is complex, but neuroscientific evidence disentangles it into
distinct components supported by dedicated brain areas or networks. In this Review, we …

Transformer models such as GPT generate human-like language and are predictive of
human brain responses to language. Here, using functional-MRI-measured brain responses …

Prediction is often regarded as an integral aspect of incremental language comprehension,
but little is known about the cognitive architectures and mechanisms that support it. We …

It has long been argued that only humans could produce and understand language. But
now, for the first time, artificial language models (LMs) achieve this feat. Here we survey the …

The relationship between language and thought is the subject of long-standing debate. One
claim states that language facilitates categorization of objects based on a certain feature (eg …

A comprehensive neural model of language must accommodate four components:
representations, operations, structures and encoding. Recent intracranial research has …

What aspects of computer programs are represented by the human brain during
comprehension? We leverage brain recordings derived from functional magnetic resonance …

The neural correlates of sentence production are typically studied using task paradigms that
differ considerably from the experience of speaking outside of an experimental setting. In …

For bilinguals, speaking in a second language (L2) compared to the native language (L1) is
usually more difficult. In this study we asked whether the difficulty in L2 production reflects …