Having Difficulties Reading the Facial Expression of Older Individuals? Blame It on the Facial Muscles, Not the Wrinkles.

Sabrina N Grondhuis,Nicolas M Brunet,Angela Jimmy,Carolina Teague

doi:10.3389/fpsyg.2021.620768

Abstract

Previous studies have found it is more difficult identifying an emotional expression displayed by an older than a younger face. It is unknown whether this is caused by age-related changes such as wrinkles and folds interfering with perception, or by the aging of facial muscles, potentially reducing the ability of older individuals to display an interpretable expression. To discriminate between these two possibilities, participants attempted to identify facial expressions under different conditions. To control for the variables (wrinkles/folds vs facial muscles), we used Generative Adversarial Networks to make faces look older or younger. Based upon behavior data collected from 28 individuals, our model predicts that the odds of correctly identifying the expressed emotion of a face reduced 16.2% when younger faces (condition 1) are artificially aged (condition 3). Replacing the younger faces with natural old-looking faces (Condition 2), however, results in an even stronger effect (odds of correct identification decreased by 50.9%). Counterintuitively, making old faces (Condition 2) look young (Condition 4) results in the largest negative effect (odds of correct identification decreased by 74.8% compared with natural young faces). Taken together, these results suggest that both age-related decline in the facial muscles’ ability to express facial emotions and age-related physical changes in the face, explain why it is difficult to recognize facial expressions from older faces; the effect of the former, however, is much stronger than that of the latter. Facial muscle exercises, therefore, might improve the capacity to convey facial emotional expressions in the elderly.

Highlights

The ability to recognize facial emotional expression is an important social skill
The two most likely explanations are (a) the emotion expressed by weathered faces are harder to interpret because the wrinkles and folds function as distractors, masking the displayed emotion and/or (b) older individuals have more difficulties controlling the many facial muscles involved in emotional expression, which gradually become more inflexible with age
By using an aging filter, the appearance of the face is changed (Condition 3), while the key face features of a given facial expression, such as shape and position of eyes, brows, lids, nostrils, and lips are conserved; an old face with the ability to express facial emotion of that of a young individual. Those key face features involved in emotional expression are conserved when original photos of an older individual (Condition 2) are transformed using a reverse aging filter, so that the face looks a lot younger (Condition 4); in this case, the ability to express facial emotions matches that of an older person

Summary

Introduction

The ability to recognize facial emotional expression is an important social skill. Many studies have focused on characterizing the age-related decrease in ability to distinguish different facial expressions (Calder et al, 2003; Grainger et al, 2017); the ability to convey ones emotional state, through facial expression, has been shown to decline with age (Borod et al, 2004; Hess et al, 2012). The two most likely explanations are (a) the emotion expressed by weathered faces are harder to interpret because the wrinkles and folds function as distractors, masking the displayed emotion and/or (b) older individuals have more difficulties controlling the many facial muscles involved in emotional expression, which gradually become more inflexible with age. To discriminate between these two potential explanations, one would ideally be able to control the variables, i.e., images of young-looking faces, where the emotions are either generated by youthful or aged facial muscles, and images of oldlooking faces where the expression was generated by either youthful or aged facial muscles. Those key face features involved in emotional expression are conserved when original photos of an older individual (Condition 2) are transformed using a reverse aging filter, so that the face looks a lot younger (Condition 4); in this case, the ability to express facial emotions matches that of an older person

Methods

Results

Conclusion