Design of an Emotional Facial Recognition Task in a 3D Environment

The recognition of emotional facial expressions is a key skill for social adaptation. Previous studies have shown that clinical and subclinical populations, such as those diagnosed with schizophrenia or autism spectrum disorder, have a significant deficit in the recognition of emotional facial expressions. These studies suggest that this may be the cause of their social dysfunction. Given the importance of this type of recognition in social functioning, the present study aims to design a tool to measure the recognition of emotional facial expressions using Unreal Engine 4 software to develop computer graphics in a 3D environment. Additionally, we tested it in a small pilot study with a sample of 37 university students, aged between 18 and 40, to compare the results with a more classical emotional facial recognition task. We also administered the SEES Scale and a set of custom-formulated questions to both groups to assess potential differences in activation levels between the two modalities (3D environment vs. classical format). The results of this initial pilot study suggest that students who completed the task in the classical format exhibited a greater lack of activation compared to those who completed the task in the 3D environment. Regarding the recognition of emotional facial expressions, both tasks were similar in two of the seven emotions evaluated. We believe that this study represents the beginning of a new line of research that could have important clinical implications.