Recognition thresholds for static and dynamic emotional faces.

Abstract

We investigated the minimum expressive intensity that is required to recognize (above chance) static and dynamic facial expressions of happiness, sadness, anger, disgust, fear, and surprise. To this end, we varied the degree of intensity of emotional expressions unfolding from a neutral face, by means of graphics morphing software. The resulting face stimuli (photographs and short videos) were presented in an expression categorization task for 1 s each, and measures of sensitivity or discrimination (A') were collected to establish thresholds. A number of physical, perceptual, categorical, and affective controls were performed. All six basic emotions were reliably recognized above chance level from low intensities, although recognition thresholds varied for different expressions: 20% of intensity, for happiness; 40%, for sadness, surprise, anger, and disgust; and 50%, for fear. The advantage of happy faces may be due to their greater physical change in facial features (as shown by automated facial expression measurement), also at low levels of intensity, relative to neutral faces. Recognition thresholds and the pattern of confusions across expressions were, nevertheless, equivalent for dynamic and static expressions, although dynamic expressions were recognized more accurately and faster. (PsycINFO Database Record

Recognition of dynamic and static facial expressions of emotion among older adults with major depression

“…36 Problems in the area of coverage of the study and the sample was similar to that found in other studies involving older adults with depression. [11][12][13] Finally, the presence of individuals with comorbid anxiety disorders in the group with depression may have exerted an influence on the results.…”

“…In contrast, despite evidence of the relationship between one's performance on facial emotion recognition tasks and depression, few studies have evaluated this relationship in older adults. [11][12][13] Moreover, all studies on facial emotion recognition in older adults with depression published to date have used tasks with static stimuli only. Therefore, this study is the first to use tasks with dynamic stimuli to evaluate facial emotion recognition in older adults with depression, and the findings may have implications for clinical practice, as the ability of facial emotion recognition is a possible predictor of response to antidepressants in older adults with depression.…”

KDEF-PT: Valence, Emotional Intensity, Familiarity and Attractiveness Ratings of Angry, Neutral, and Happy Faces

“…For example a review by Nelson and Russell (2013) , concluded that happiness is the emotion with the highest percentage of hits (around 90%) across cultures and languages. Indeed, the identification threshold for a happy expression is particularly low, given that this emotion can be recognized even when presented very fast (e.g., Calvo and Lundqvist, 2008 ) and with minimal intensity ( Calvo et al, 2016 ). Moreover, happy faces not only were perceived as the most positive and familiar (e.g., Garrido et al, 2016 ), but also as the most attractive (e.g., Golle et al, 2014 ; Garrido et al, 2016 ).…”

Perceptual and affective mechanisms in facial expression recognition: An integrative review

“…Recio et al (2014) found that the recognition accuracy of all six basic expressions was above 70% (except fear: 62.5%) already at a 60% intensity level. In a recent study (Calvo, Avero, Fernández-Martín, & Recio, 2015), intensity levels were morphed from 20% to 100%. Measures of discrimination (A') established recognition thresholds: 20% of intensity for happiness; 40% for sadness, surprise, anger and disgust; 50-60% for fear, similarly for dynamic and static expressions.…”