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 …

A brain–computer interface that decodes continuous language from non-invasive recordings
would have many scientific and practical applications. Currently, however, non-invasive …

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 …

The neuroscience of perception has recently been revolutionized with an integrative
modeling approach in which computation, brain function, and behavior are linked across …

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 …

The meaning of language is represented in regions of the cerebral cortex collectively known
as the 'semantic system'. However, little of the semantic system has been mapped …

Certain organizational features of brain networks present in the individual are lost when
central tendencies are examined in the group. Here we investigated the detailed network …

How does language inform our downstream thinking? In particular, how do humans make
meaning from language--and how can we leverage a theory of linguistic meaning to build …