Article

Impact of depression on response to comedy: A dynamic facial coding analysis

Department of Psychology, University of Pittsburgh, Pittsburgh, PA 15260, USA.
Journal of Abnormal Psychology (Impact Factor: 4.86). 11/2007; 116(4):804-9. DOI: 10.1037/0021-843X.116.4.804
Source: PubMed

ABSTRACT Individuals suffering from depression show diminished facial responses to positive stimuli. Recent cognitive research suggests that depressed individuals may appraise emotional stimuli differently than do nondepressed persons. Prior studies do not indicate whether depressed individuals respond differently when they encounter positive stimuli that are difficult to avoid. The authors investigated dynamic responses of individuals varying in both history of major depressive disorder (MDD) and current depressive symptomatology (N = 116) to robust positive stimuli. The Facial Action Coding System (Ekman & Friesen, 1978) was used to measure affect-related responses to a comedy clip. Participants reporting current depressive symptomatology were more likely to evince affect-related shifts in expression following the clip than were those without current symptomatology. This effect of current symptomatology emerged even when the contrast focused only on individuals with a history of MDD. Specifically, persons with current depressive symptomatology were more likely than those without current symptomatology to control their initial smiles with negative affect-related expressions. These findings suggest that integration of emotion science and social cognition may yield important advances for understanding depression.

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    • "Much research using FACS has focused on the occurrence and AU composition of different expressions (Ekman and Rosenberg, 2005). For example, smiles that recruit the orbicularis oculi muscle (i.e., AU 6) are more likely to occur during pleasant circumstances (Ekman et al., 1990, Frank et al., 1993) and smiles that recruit the buccinator muscle (i.e., AU 14) are more likely to occur during active depression (Reed et al., 2007, Girard et al., 2013). A promising subset of research has begun to focus on what can be learned about and from the intensity of expressions. "
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    ABSTRACT: Both the occurrence and intensity of facial expressions are critical to what the face reveals. While much progress has been made towards the automatic detection of facial expression occurrence, controversy exists about how to estimate expression intensity. The most straight-forward approach is to train multiclass or regression models using intensity ground truth. However, collecting intensity ground truth is even more time consuming and expensive than collecting binary ground truth. As a shortcut, some researchers have proposed using the decision values of binary-trained maximum margin classifiers as a proxy for expression intensity. We provide empirical evidence that this heuristic is flawed in practice as well as in theory. Unfortunately, there are no shortcuts when it comes to estimating smile intensity: researchers must take the time to collect and train on intensity ground truth. However, if they do so, high reliability with expert human coders can be achieved. Intensity-trained multiclass and regression models outperformed binary-trained classifier decision values on smile intensity estimation across multiple databases and methods for feature extraction and dimensionality reduction. Multiclass models even outperformed binary-trained classifiers on smile occurrence detection.
    Pattern Recognition Letters 10/2014; DOI:10.1016/j.patrec.2014.10.004 · 1.55 Impact Factor
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    • "As a smile control, AU 24 may occur less often than AU 14 and other smile controls. In a variety of contexts, AU 14 has been the most noticed smile control [27] [61]. Little is known, however, about the relative occurrence of different smile controls. "
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    • "Thus, we were unable to determine whether emotional displays of Whites in our three-person interracial groups were directed toward Black or White group members. Fourth, consistent with our prior work (Reed et al., 2007), this study did not distinguish between smile controls that follow Duchenne smiles and those that follow " social smiles. " Finally, participants observed in this study were young and resided in a relatively diverse metropolitan area in the northeastern United States. "
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