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 English is the dominant language in the study of human cognition and behavior: the
individuals studied by cognitive scientists, as well as most of the scientists themselves, are …

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

Reconstructing visual experiences from human brain activity offers a unique way to
understand how the brain represents the world, and to interpret the connection between …

Considerable progress has recently been made in natural language processing: deep
learning algorithms are increasingly able to generate, summarize, translate and classify …

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 …

Language Models (LMs) can perform new tasks by adapting to a few in-context examples.
For humans, explanations that connect examples to task principles can improve learning …

Abstract reasoning is a key ability for an intelligent system. Large language models (LMs)
achieve above-chance performance on abstract reasoning tasks, but exhibit many …

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 …

Neuroscientists have long characterized the properties and functions of the nervous system,
and are increasingly succeeding in answering how brains perform the tasks they do. But the …