Social anxiety and threat-related interpretation of dynamic facial expressions: Sensitivity and response bias

Gutiérrez-García, Aida; Calvo, Manuel G.

doi:10.1016/j.paid.2016.11.025

Cited by 49 publications

(28 citation statements)

References 27 publications

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“…A third promising application is concerned with the use of these stimuli in the investigation of cognitive biases (attentional and interpretative) in psychopathology . For example, it has been shown that individuals with clinical levels of social anxiety are especially prone to detect negatively valenced dynamic expressions at low intensities ( Gutiérrez-García and Calvo, 2016 , 2017 ; Gutiérrez-García et al, 2018 ). A reason for the usefulness of this application to psychopathology research is that dynamic information improves identification of facial affect, particularly for lower intensity and subtle stimuli ( Krumhuber et al, 2013 ), which would increase sensitivity for individuals that are hypervigilant to threat and incongruities in facial expressions.…”

Section: Discussionmentioning

confidence: 99%

Human Observers and Automated Assessment of Dynamic Emotional Facial Expressions: KDEF-dyn Database Validation

et al. 2018

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Most experimental studies of facial expression processing have used static stimuli (photographs), yet facial expressions in daily life are generally dynamic. In its original photographic format, the Karolinska Directed Emotional Faces (KDEF) has been frequently utilized. In the current study, we validate a dynamic version of this database, the KDEF-dyn. To this end, we applied animation between neutral and emotional expressions (happy, sad, angry, fearful, disgusted, and surprised; 1,033-ms unfolding) to 40 KDEF models, with morphing software. Ninety-six human observers categorized the expressions of the resulting 240 video-clip stimuli, and automated face analysis assessed the evidence for 6 expressions and 20 facial action units (AUs) at 31 intensities. Low-level image properties (luminance, signal-to-noise ratio, etc.) and other purely perceptual factors (e.g., size, unfolding speed) were controlled. Human recognition performance (accuracy, efficiency, and confusions) patterns were consistent with prior research using static and other dynamic expressions. Automated assessment of expressions and AUs was sensitive to intensity manipulations. Significant correlations emerged between human observers’ categorization and automated classification. The KDEF-dyn database aims to provide a balance between experimental control and ecological validity for research on emotional facial expression processing. The stimuli and the validation data are available to the scientific community.

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Section: Discussionmentioning

confidence: 99%

Human Observers and Automated Assessment of Dynamic Emotional Facial Expressions: KDEF-dyn Database Validation

et al. 2018

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“…The present study revealed lower accuracy rates for angry-neutral facial emotional changes than those for the neutral-neutral facial emotional changes, suggesting an inferior processing of angry-neutral facial emotional changes. Considering the fact that the angry-neutral facial emotional changes are morphed (ambiguous) negative expressions ( Gutiérrez-García and Calvo, 2017 ), people may be more cautious towards them. However, there are other studies to show that people have better performances (better memory) for emotional faces when compared with neutral faces, which is inconsistent with our finding ( Grady et al, 2007 ).…”

Section: Discussionmentioning

confidence: 99%

“…The following study adopted the modified morphed faces task to examine dynamic facial expressions in individuals with social anxiety ( Heuer et al, 2010 ). Recently, Gutiérrez-García and Calvo (2017) found that HSA participants were biased towards the interpretation of ambiguous expressions (dynamic facial expressions) in response to threat. Although previous behavioral research has investigated the facial emotional change (neutral-angry facial emotional change: a neutral face suddenly changes to an angry face) in individuals with social anxiety, none of the previous studies have directly investigated the angry-neutral facial emotional change (an angry face suddenly changes to a neutral face).…”

Section: Introductionmentioning

confidence: 99%

The Perception of Facial Emotional Change in Social Anxiety: An ERP Study

Zhang

Ran

2018

Front. Psychol.

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Social anxiety is one of the psychological symptoms that most commonly occur in social interaction. Although previous behavioral studies have investigated the neutral-angry facial emotion change in social anxiety, none of the previous studies have, however, directly investigated the angry-neutral facial emotional change. Furthermore, less is known about the neural correlates of the facial emotion changes in individuals with social anxiety. The main goal of the present study was to explore the perception of facial emotional changes in individuals with social anxiety, using high temporal resolution event-related potential techniques. Behaviorally, accuracy in the angry-neutral facial emotional change trail was lower than that in the neutral-neutral case. Neurally, we found that the N170 amplitudes in angry-neutral facial emotional change trial were larger than those in the neutral-neutral case for high social anxiety (HAS) participants, probably reflecting that they might engage in more analytical processing of different facial elements. Interestingly, HSA participants showed smaller P200 left hemisphere amplitudes in the angry-neutral facial emotional change trial when compared with the neutral-neutral case, which suggested that they might have difficulties in processing emotions when they encounter these facial emotional changes. Finally, the late positive potential amplitudes in the neutral-angry and angry-neutral facial emotional change trials were smaller than those in the neutral-neutral case, regardless of the social anxiety. These results suggest that social anxiety influences the facial emotional changes mainly at an earlier stage of processing.

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“…To investigate the sensitivity of the three different facial emotions, we defined all faces used in the experiment except for the neutral faces as emotional (angry, happy, or sad) faces as a previous study [9]. Thus, the correct answer for the emotionally graded faces (from Step 1 to 8) in the angry, happy, or sad category was angry, happy, or sad, respectively.…”

Section: Methodsmentioning

confidence: 99%

“…Especially, participants with high anxiety have shown atypical recognition of negative facial expressions. For instance, high anxiety participants showed a more sensitive recognition of fearful or threatening faces relative to healthy normal participants [5678910]. Moreover, some studies also have demonstrated interpretation bias of facial expressions, in which anxious people are more likely to misclassify neutral or ambiguous emotional faces as threatening faces [1011121314].…”

Section: Introductionmentioning

confidence: 99%

The Influence of Anxiety on the Recognition of Facial Emotion Depends on the Emotion Category and Race of the Target Faces

Kang

Kim

et al. 2019

Exp Neurobiol

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The recognition of emotional facial expressions is critical for our social interactions. While some prior studies have shown that a high anxiety level is associated with more sensitive recognition of emotion, there are also reports supporting that anxiety did not affect or reduce the sensitivity to the recognition of facial emotions. To reconcile these results, here we investigated whether the effect of individual anxiety on the recognition of facial emotions is dependent on the emotion category and the race of the target faces. We found that, first, there was a significant positive correlation between the individual anxiety level and the recognition sensitivity for angry faces but not for sad or happy faces. Second, while the correlation was significant for both low- and high-intensity angry faces during the recognition of the observer's own-race faces, there was significant correlation only for low-intensity angry faces during the recognition of other-race faces. Collectively, our results suggest that the influence of anxiety on the recognition of facial emotions is flexible depending on the characteristics of the target face stimuli including emotion category and race.

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Social anxiety and threat-related interpretation of dynamic facial expressions: Sensitivity and response bias

Cited by 49 publications

References 27 publications

Human Observers and Automated Assessment of Dynamic Emotional Facial Expressions: KDEF-dyn Database Validation

Human Observers and Automated Assessment of Dynamic Emotional Facial Expressions: KDEF-dyn Database Validation

The Perception of Facial Emotional Change in Social Anxiety: An ERP Study

The Influence of Anxiety on the Recognition of Facial Emotion Depends on the Emotion Category and Race of the Target Faces

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