Abstract

The immediate detection and correct processing of affective facial expressions are one of the most important competences in social interaction and thus a main subject in emotion and affect research. Generally, studies in these research domains, use pictures of adults who display affective facial expressions as experimental stimuli. However, for studies investigating developmental psychology and attachment behaviour it is necessary to use age-matched stimuli, where it is children that display affective expressions. PSYCAFE represents a newly developed picture-set of children’s faces. It includes reference portraits of girls and boys aged 4 to 6 years averaged digitally from different individual pictures, that were categorized to six basic affects (fear, disgust, happiness, sadness, anger and surprise) plus a neutral facial expression by cluster analysis. This procedure led to deindividualized and affect prototypical portraits. Individual affect expressive portraits of adults from an already validated picture-set (KDEF) were used in a similar way to create affect prototypical images also of adults. The stimulus set has been validated on human observers and entail emotion recognition accuracy rates and scores for intensity, authenticity and likeability ratings of the specific affect displayed. Moreover, the stimuli have also been characterized by the iMotions Facial Expression Analysis Module, providing additional data on probability values representing the likelihood that the stimuli depict the expected affect. Finally, the validation data from human observers and iMotions are compared to data on facial mimicry of healthy adults in response to these portraits, measured by facial EMG (m. zygomaticus major and m. corrugator supercilii).

Highlights

  • It is a crucial ability of human interaction to detect and to understand affective signals, to represent them verbally and to display them in direct social contact

  • In order to obtain a differentiated assignment of the individual portraits to the respective clusters and to detect even small differences between the single clusters, the 23-cluster solution was chosen for further analysis

  • The digitally deindividualized portraits of the PSYCAFE picture-set were created from 149 individual pictures of real children in play

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Summary

Introduction

It is a crucial ability of human interaction to detect and to understand affective signals, to represent them verbally and to display them in direct social contact. Survival and development of attachment are based on the affect-related regulation of the needs of the child by the primary caregiver. This process is stimulated by the baby schema [4]. It is vital to create picture-sets of affect expressive faces for different age groups This allows to investigate affect recognition and processing without the confounding effect of the own-age-bias [7] or to perform studies on attachment related and developmental issues such as early parent-child-interaction and affect regulation (e.g. dependent from different psychic or affective disorders)

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