Investigating the Role of Working Memory on Emotion Recognition Accuracy in Emerging Adults

Abstract

Emotion recognition involves interpreting nonverbal cues like facial expressions and tone of voice. Vocal emotion recognition is more challenging and matures later than facial recognition. However, research often uses static facial expressions and dynamic vocal expressions, leading to biased comparisons. The disparity between vocal and facial emotion recognition may stem from the need for advanced cognitive skills to interpret dynamic expressions that unfold over time. The current online study explored potential cognitive predictors involved in four emotion recognition tasks in a sample of 260 emerging adults (60.4% female; age M = 22.24 years, SD = 7.50 years). Including four emotion recognition tasks (i.e., static voice, static face, dynamic voice, and dynamic face) in the current study enabled direct comparisons between facial and vocal modalities, addressing the temporal inconsistencies found in previous research. Additionally, tasks such as the backwards digit span and N-back were used to assess whether different facets of working memory predicted emotion recognition accuracy. It was hypothesized that emotion recognition accuracy would be higher for facial compared to vocal stimuli, with the lowest accuracy expected in the dynamic vocal condition. Additionally, it was hypothesized that working memory would be a predictor of emotion recognition accuracy for dynamic stimuli. Results of the study show that emotion recognition accuracy was higher for facial compared to vocal stimuli, and that emotion recognition accuracy was higher for static compared to dynamic stimuli. The impact of modality on emotion recognition accuracy depended on whether the stimuli were static or dynamic. Dynamic facial expressions were recognized more accurately than vocal prosody, whereas static vocalizations and static facial images were recognized with similar accuracy. Although working memory did not predict overall emotion recognition accuracy, the results changed when the challenging dynamic vocal condition was excluded. Without this condition, visual working memory was associated with higher emotion recognition accuracy. Furthermore, attentional control also predicted greater accuracy, contributing uniquely beyond the influence of visual working memory. These findings provide insight into the cognitive processes involved in emotion recognition and have implications for understanding the varying developmental trajectories of facial compared to vocal emotion recognition.