Emotion identification across adulthood using the Dynamic FACES database of emotional expressions in younger, middle aged, and older adults.

Facial stimuli are widely used in behavioural and brain science research to investigate emotional facial processing. However, some studies have demonstrated that dynamic expressions elicit stronger emotional responses compared to static images. To address the need for more ecologically valid and powerful facial emotional stimuli, we created Dynamic FACES, a database of morphed videos (n = 1026) from younger, middle-aged, and older adults displaying naturalistic emotional facial expressions (neutrality, sadness, disgust, fear, anger, happiness). To assess adult age differences in emotion identification of dynamic stimuli and to provide normative ratings for this modified set of stimuli, healthy adults (n = 1822, age range 18-86 years) categorised for each video the emotional expression displayed, rated the expression distinctiveness, estimated the age of the face model, and rated the naturalness of the expression. We found few age differences in emotion identification when using dynamic stimuli. Only for angry faces did older adults show lower levels of identification accuracy than younger adults. Further, older adults outperformed middle-aged adults' in identification of sadness. The use of dynamic facial emotional stimuli has previously been limited, but Dynamic FACES provides a large database of high-resolution naturalistic, dynamic expressions across adulthood. Information on using Dynamic FACES for research purposes can be found at http://faces.mpib-berlin.mpg.de .

Duke Scholars

Author Gregory Russell Samanez-Larkin Psychology & Neuroscience