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 …

To understand the architecture of human language, it is critical to examine diverse
languages; however, most cognitive neuroscience research has focused on only a handful …

Deep learning algorithms trained to predict masked words from large amount of text have
recently been shown to generate activations similar to those of the human brain. However …

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 …

From sequences of speech sounds, or letters, humans can extract rich and nuanced
meaning through language. This capacity is essential for human communication. Yet …

Abstract Syntax, the structure of sentences, enables humans to express an infinite range of
meanings through finite means. The neurobiology of syntax has been intensely studied but …

Theories of human cognition prominently feature'Broca's area', which causally contributes to
a myriad of mental functions. However, Broca's area is not a monolithic, multipurpose unit–it …

Two analytic traditions characterize fMRI language research. One relies on averaging
activations across individuals. This approach has limitations: because of inter-individual …

Much research in cognitive neuroscience supports prediction as a canonical computation of
cognition across domains. Is such predictive coding implemented by feedback from higher …