Large language models (LLMs), such as OpenAI's GPT-4, Google's Bard or Meta's LLaMa,
have created unprecedented opportunities for analysing and generating language data on a …

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 …

Deep neural networks (DNNs) have had extraordinary successes in classifying
photographic images of objects and are often described as the best models of biological …

The idea that human cognition is, or can be understood as, a form of computation is a useful
conceptual tool for cognitive science. It was a foundational assumption during the birth of …

Many recent studies have shown that representations drawn from neural network language
models are extremely effective at predicting brain responses to natural language. But why …

Models that predict brain responses to stimuli provide one measure of understanding of a
sensory system and have many potential applications in science and engineering. Deep …

Effective communication hinges on a mutual understanding of word meaning in different
contexts. We recorded brain activity using electrocorticography during spontaneous, face-to …

Abstract Language neuroscience currently relies on two major experimental paradigms:
controlled experiments using carefully hand-designed stimuli, and natural stimulus …

The human brain achieves visual object recognition through multiple stages of linear and
nonlinear transformations operating at a millisecond scale. To predict and explain these …

Abstract Large Language Models (LLMs) are recruited in applications that span from clinical
assistance and legal support to question answering and education. Their success in …