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.

A study by cognitive scientists at Brown University’s Carney Institute for Brain Science deciphered how the human brain represents the complex social connections among acquaintances, friends, and friends of friends.

As part of a class taught by Brown neuroscientist David Badre, undergraduates embrace the rare opportunity to conduct experiments and engage in research with state-of-the-art MRI technology.

A collaboration between professors Michael Frank and Ellie Pavlick is yielding important results about similarities between how ChatGPT-like AI and the human brain accomplish certain complex tasks, opening the door for transformative research at the intersection of computational neuroscience and computer science.

Dopaminergic therapy and deep brain stimulation can improve the motor symptoms of Parkinson’s disease (PD). But both treatments can make patients more impulsive. In a new study, Carney researchers combined experimental testing with computational modeling to uncover two different routes the two treatments take to modify decision-making.

How does dopamine help us make important decisions? What kinds of learning scenarios best enable us to become proficient at something? And why does overthinking sometimes hinder learning? Professor Michael Frank’s lab has published scholarship that responds to these questions.