Individual Differences in Learning Social and Non-Social Network Structures

TL;DR

This study investigates how individuals learn complex social and non-social network structures, revealing that social traits uniquely influence social network learning, indicating distinct cognitive processes for social versus non-social information.

Contribution

The paper demonstrates that learning social networks is independent from non-social networks and that social traits predict social network learning, providing new insights into individual differences in complex association learning.

Findings

Participants learned both social and non-social networks.

Performance in social and non-social network learning was uncorrelated.

Social traits predicted social network learning but not non-social network learning.

Abstract

Learning about complex associations between pieces of information enables individuals to quickly adjust their expectations and develop mental models. Yet, the degree to which humans can learn higher-order information about complex associations is not well understood; nor is it known whether the learning process differs for social and non-social information. Here, we employ a paradigm in which the order of stimulus presentation forms temporal associations between the stimuli, collectively constituting a complex network structure. We examined individual differences in the ability to learn network topology for which stimuli were social versus non-social. Although participants were able to learn both social and non-social networks, their performance in social network learning was uncorrelated with their performance in non-social network learning. Importantly, social traits, including social orientation and perspective-taking, uniquely predicted the learning of social networks but not the learning of non-social networks. Taken together, our results suggest that the process of learning higher-order structure in social networks is independent from the process of learning higher-order structure in non-social networks. Our study design provides a promising approach to identify neurophysiological drivers of social network versus non-social network learning, extending our knowledge about the impact of individual differences on these learning processes. Implications for how people learn and adapt to new social contexts that require integration into a new social network are discussed.