A method for diagnosing depression: Facial expression mimicry is evaluated by facial expression recognition

Abstract

BackgroundConsiderable evidence has shown that facial expression mimicry is impaired in patients with depression. We aimed to evaluate voluntary expression mimicry by facial expression recognition for diagnosing depression. MethodsA total of 168 participants performed voluntary expression mimicry task, posing anger, disgust, fear, happiness, neutrality, sadness, and surprise. 9 healthy raters performed facial expression recognition task through the observer scoring method, and evaluated seven expressions imitated by participants. Emotional scores were calculated to measure any differences between two groups of participants and provided a basis for clinical diagnosis of depression. ResultsCompared with the control group, the depression group had lower accuracy in imitating happiness. Compared with the control group, the depression group imitated a higher neutrality bias for sadness, surprise, happiness and disgust, while sadness and surprise had a lower happiness bias; for imitating happiness, the depression group showed higher anger, disgust, fear, neutrality, and surprise bias; for imitating neutrality, the depression group showed higher sadness bias, and lower happiness bias. Compared with the control group, the raters had a higher reaction time to recognize the happiness imitated by depression group, and it was positively correlated with severity of depression. The severity of depression was also negatively correlated with accuracy in imitating happiness, and positively correlated with neutrality bias of imitating surprise. LimitationsThe ecological effectiveness of static stimulus materials is lower than that of dynamic stimuli. Without synchronized functional imaging, there is no way to link brain activation patterns. ConclusionThe ability of patients with depression to voluntarily imitate facial expressions declines, which is mainly reflected in accuracy, bias and recognizability. Our experiment has discovered deficits in these aspects of patients with depression, which will be used as a method for diagnosising depression.