Programm

Social learning—the ability to acquire relevant knowledge, beliefs, or behaviors in the presence or context of others—is a fundamental human skill. Over the past decade, computational models of learning, with formal quantifications using mathematical equations and latent variables/parameters, have offered remarkable insights into both the behavioral and the neural foundations of this essential process. Today, these models in conjunction with bio-psychological methods help uncover the mechanisms underlying various complex social behaviors, underscoring the richness and versatility of this approach.

This symposium brings together scientists across different career stages from three countries (Austria, Germany, and UK) and three different universities (Universities of Vienna, Würzburg, & Birmingham) who investigate bio-psychological mechanisms of social learning in a variety of social contexts.

Our symposium explores Bayesian inference in a novel social learning task and its connection to autistic traits. (Bianca Schuster). Additionally, we examine the neural mechanisms underlying emotional and reward prediction errors in social transgressions (Lei Zhang). We will discuss how interactive gaze fosters closeness through learning (Julian Gutzeit), and a final presentation will highlight how financial incentives and empathy shape social behavior, integrating fMRI and reinforcement learning models (Anne Saulin).

Together, the presentations in this symposium provide a multidisciplinary perspective on the computational and neural mechanisms of social learning. Collectively, we will discuss and integrate these diverse methodologies and modelling approaches to illustrate how social learning models enhance our understanding of key social-cognitive processes and their role in different social contexts.