New research shows that AI language models can develop a mathematical “understanding” that differentiates between events that are commonplace, improbable, impossible or just plain nonsense.

Over the fall semester, prestigious national and international organizations recognized Brown faculty for their research, service, scholarship and leadership.

The Brown University cognitive neuroscientist studies how the brain and body interact, with the goal of translating insights into treatments and solutions for patients facing a variety of health challenges.

By working to understand how new AI systems integrate flexible and incremental learning, researchers gained insights about the human brain.

Researchers at the Carney Institute for Brain Science have identified electrical activity in the brain that could predict progression to Alzheimer’s disease.

Graduate students from Brown University and Ben-Gurion University put their brains together in a unique summer practicum to invent and pitch ideas for neurotechnology startups.

A new institute, based at Brown and supported by a $20 million National Science Foundation grant, will convene researchers to guide development of a new generation of AI assistants for use in mental and behavioral health.

With the launch, Brown becomes one of a handful of U.S. universities with an undergraduate curriculum that marries neuroscience with computer science and math.

The lab of Michael Frank has reconciled theories of how humans store and retrieve information in the short-term, a process called working memory, in a new biologically-inspired computational model. The findings have implications for dopamine-related disorders like Parkinson’s disease, attention-deficit/hyperactivity disorder (ADHD) and schizophrenia.