Getting to know you: general and specific neural computations for learning about people

Abstract

Learning about other peoples' attributes, e.g. whether an individual is generous or selfish, is central to human social cognition. It is well documented that a network of cortical regions is reliably activated when we engage social processes. However, little is known about the specific computations performed by these regions or whether such processing is specialized for the social domain. We investigated these questions using a task in which participants (N= 26) learned about four peoples' generosity by watching them choose to share money with third party partners, or not. In a non-social control condition, participants learned the win/loss rates of four lotteries. fMRI analysis revealed learning-related general (social + non-social) prediction error signals in the dorsomedial and dorsolateral prefrontal cortices (bilaterally), and in the right lateral parietal cortex. Socially specific (social > non-social) prediction error signals were found in the precuneus. Interestingly, the region that exhibited social prediction errors was a distinct subregion of the area in the precuneus and posterior cingulate cortex that exhibited a commonly reported main effect of higher overall activity for social vs non-social stimuli. These findings elucidate the domain--general and--specific computations underlying learning about other people and demonstrate the increased explanatory power of computational approaches to social cognition.

Keywords: computational neuroscience; fMRI; precuneus; prediction error; trait learning.