Precision and the Bayesian brain

• Published in: Current biology 2021-09, Vol.31 (17), p.R1026-R1032
• Main Authors: Yon, Daniel, Frith, Chris D.
• Format: Article
• Language: English
• ISSN: 0960-9822; 1879-0445
• DOI: 10.1016/j.cub.2021.07.044

Scientific thinking about the minds of humans and other animals has been transformed by the idea that the brain is Bayesian. A cornerstone of this idea is that agents set the balance between prior knowledge and incoming evidence based on how reliable or ‘precise’ these different sources of information are — lending the most weight to that which is most reliable. This concept of precision has crept into several branches of cognitive science and is a lynchpin of emerging ideas in computational psychiatry — where unusual beliefs or experiences are explained as abnormalities in how the brain estimates precision. But what precisely is precision? In this Primer we explain how precision has found its way into classic and contemporary models of perception, learning, self-awareness, and social interaction. We also chart how ideas around precision are beginning to change in radical ways, meaning we must get more precise about how precision works. In this Primer, Daniel Yon and Chris Frith explain ‘precision’, a key concept in Bayesian models of the mind and brain. The idea of precision is central to current thinking across the cognitive sciences, but in recent years ideas about precision have begun to change. This raises important questions about precisely how precision works.