Fig. 6: Computational models explain expectancy ratings and in- and outgroup closeness ratings in the East Asian sample.
From: Learning reduces ingroup bias more with perceived losses than gains across cultures
a Expectations of money being given/taken varied over the course of the experiment (solid black line) and our learning model explained these expectations (shaded area). b Trial-by-trial ingroup closeness ratings (solid red line) and corresponding model estimates (shaded area) in the Gain and Loss frame. c Trial-by-trial outgroup closeness ratings (solid blue line) and corresponding model estimates (shaded area) in the Gain and Loss frame. The model estimates illustrate the best-fitting Learning/Closeness model. All panels show averages of participants (N = 50/49 in the Gain/Loss frame). The shaded area represents \(\pm\) s.e.m. around the mean model predictions.
