Precision and the Bayesian brain

Author: Daniel Yon1, Chris D Frith2
Affiliation: <sup>1</sup> Department of Psychology, Goldsmiths, University of London, Lewisham Way, London SE14 6NW, UK; Department of Psychological Sciences, Birkbeck, University of London, Malet Street, London WC1E 7HX, UK. Electronic address: <sup>2</sup> Institute of Philosophy, University of London, Malet Street, London WC1E 7HU, UK; Wellcome Centre for Human Neuroimaging, University College London, 12 Queen Square, London WC1N 3AR, UK.
Conference/Journal: Curr Biol
Date published: 2021 Sep 13
Other: Volume ID: 31 , Issue ID: 17 , Pages: R1026-R1032 , Special Notes: doi: 10.1016/j.cub.2021.07.044. , Word Count: 155

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.

PMID: 34520708 DOI: 10.1016/j.cub.2021.07.044