Facial-expression affective attributes and their configural correlates: components and categories

Area of Science:

• Psychology
• Cognitive Science
• Neuroscience

Background:

• Facial expressions are crucial for social communication.
• Understanding how humans perceive and interpret emotions from faces is a fundamental question in psychology.
• Previous models proposed either categorical or dimensional perception of emotions.

Purpose of the Study:

• To investigate the perception of facial expressions of emotion.
• To explore the relationship between the configural properties of facial expressions and their subjective attribution.
• To test whether a componential or categorical-gestalt model better explains emotion perception.

Main Methods:

• Generated morphed facial expression stimuli between prototypes of seven emotions (happiness, sadness, fear, anger, surprise, disgust, neutral).
• Quantified topographical properties using the Facial Expression Measurement (FACEM) scheme.
• Used multidimensional scaling on perceived dissimilarities from a sorting procedure to analyze the facial-expression space.

Main Results:

• Four dimensions were identified in the facial-expression space, opposing positive and negative emotions.
• Three dimensions were interpreted as affective attributes distinguishing clusters: Surprise-Fear, Anger, and Disgust.
• Significant relationships were found between affective attributes and objective facial measures (configural properties).

Conclusions:

• Findings support a componential model where facial expression components convey separable affective values.
• Configural information is integral to decoding affective attributes of facial expressions.
• Configural measures may serve as a basis for both dimensional and categorical perception of emotional faces.