Facial emotion recognition in patients with depression compared to healthy controls when using human avatars

Divergent spatiotemporal signatures characterize impaired facial emotional recognition in major depressive disorder: An event-related microstate study

BACKGROUND

Major depressive disorder (MDD) is a chronic affective mental disorder with intricate neuropathological characteristics. Microstate analysis has proved its ability to reveal the relatively stable features in a specific brain process. However, the relationship between event-related microstate networks and affective dysfunctions in patients with MDD is not well known.

METHODS

The 128-channel electroencephalogram (EEG) data from 24 MDD patients and 29 healthy controls (HCs) with facial emotion recognition (FER) tasks were used in this study. The analysis encompassed both event-related microstate parameters and specific microstate network metrics. The microstate parameters included Mean Global Field Power (mGFP), Mean Duration (mDur), Time Coverage (TC), and Segment Count Density (SegD). The network metrics evaluated were the clustering coefficient (CC), path length (Lp), global efficiency (Eg), and local efficiency (Eloc).

RESULTS

Three event-related microstates (MS-P1, MS-N170, and MS-P2) were estimated. Compared with HCs, the MDD patients showed significantly increased mGFP in MS-P1 with the sad emotion and decreased microstate parameters in MS-P2 with happy (mDur and TC) and sad (SegD and TC) emotions. Correlation results showed that MS-P1 with the sad emotion was positively related to clinical outcomes. MS-P2 with happy and sad emotions negatively correlated with clinical scores. Additionally, the microstate networks confirmed that MDD patients had decreased network efficiency of the happy emotion in MS-P1 while increased efficiency in dealing with the negative emotion in MS-P2.

CONCLUSIONS

By analyzing event-related microstates and brain networks, we provided a novel approach to demonstrate the divergent patterns for FER processing and the atypical dynamic coordination and integration of affective mechanisms underlying emotional deficits in MDD.

Child psychological maltreatment, depression, psychological inflexibility and difficulty in identifying feelings, a moderated mediation model

Child psychological maltreatment has a strong relationship with college students' depression. However, the potential mediating and moderating variables between the two need further exploration. This study collected subjective data of college students from two universities in China through a cross-sectional survey, including variables such as child psychological maltreatment, psychological inflexibility, difficulty in identifying feelings, and depression. Through correlation analysis, a mediation model and a moderated mediation model were constructed to explore the interrelationships among the variables.The research results show that there is a significant positive correlation between child psychological maltreatment, psychological inflexibility, difficulty in identifying feelings, and college students' depression. Moreover, psychological inflexibility plays a mediating role between child psychological maltreatment and college students' depression, while difficulty in identifying feelings significantly moderates the relationship between child psychological maltreatment and college students' depression. This study reveals the significant associations among child psychological maltreatment, psychological inflexibility, difficulty in identifying feelings, and college students' depression. These findings remind us to pay attention to the potential mediating role of psychological inflexibility and the moderating role of difficulty in identifying feelings when exploring the relationship between child psychological maltreatment and college students' depression. These results provide a new perspective for understanding the psychological mechanism of depression and offer potential targets for prevention and intervention.

Emotion recognition in individuals with elevated internet addiction scores: An event-related potential study

The current study aims to elucidate the electrophysiological correlates of performance patterns in an emotion recognition task among individuals with higher internet addiction (HIA) scores compared to those with lower internet addiction (LIA) scores. Forty participants, with twenty in the HIA group and twenty in the LIA group, completed an emotion recognition task, involving five facial expressions: anger, fear, disgust, neutral, and sadness. Additionally, cognitive flexibility and working memory were assessed to examine their link to emotion recognition abilities. No significant differences in accuracy or reaction times (RTs) were observed between the groups in the emotion recognition task. However, the HIA group showed reduced P150 amplitudes, but increased N250 amplitudes relative to the LIA group. There was a positive correlation between the RTs and cognitive flexibility, only in the LIA group. Although the groups demonstrated comparable behavioral performance, the stages of stimuli processing differed. The LIA group appeared to process the stimuli more efficiently in the early stage, while the HIA group required greater effort in decoding the stimuli at a later stage. This suggests that the HIA group may rely on over-processing at a later stage due to reduced early processing efficiency, potentially suggesting an early vulnerability marker.

Differences in emotion recognition between nonimmersive versus immersive virtual reality: preliminary findings in schizophrenia and bipolar disorder

Deficits in social cognition may impair emotional processing and facial emotional recognition (FER) in patients with bipolar disorder (BD) and schizophrenia. FER is generally explored using photographs or images of static faces that do not fully capture the complexity of real-life facial stimuli. To overcome this limitation, we developed a set of dynamic virtual faces depicting six basic emotions (i.e. happiness, sadness, anger, fear, disgust, and surprise) and a neutral expression suitable for presentation in immersive and nonimmersive virtual realities. This study presents preliminary findings on the differences in FER accuracy from a frontal view between immersive and nonimmersive virtual realities among patients experiencing a relapse of schizophrenia (n = 10), a manic phase of BD (n = 10), and a group of healthy controls (HCs) (n = 10). As a secondary objective, we compare the FER accuracy across these three groups. Patients with schizophrenia and BD showed similar accuracy in recognizing emotions in immersive and nonimmersive virtual reality settings. However, patients with schizophrenia exhibited lower FER accuracy than HCs in both settings. Individuals with BD showed intermediate accuracy between those with schizophrenia and HCs, although these differences were not statistically significant. Notably, recognition of negative emotions was significantly impaired in both groups of patients.

Reading language of the eyes in female depression

Aberrations in non-verbal social cognition have been reported to coincide with major depressive disorder. Yet little is known about the role of the eyes. To fill this gap, the present study explores whether and, if so, how reading language of the eyes is altered in depression. For this purpose, patients and person-by-person matched typically developing individuals were administered the Emotions in Masked Faces task and Reading the Mind in the Eyes Test, modified, both of which contained a comparable amount of visual information available. For achieving group homogeneity, we set a focus on females as major depressive disorder displays a gender-specific profile. The findings show that facial masks selectively affect inferring emotions: recognition of sadness and anger are more heavily compromised in major depressive disorder as compared with typically developing controls, whereas the recognition of fear, happiness, and neutral expressions remains unhindered. Disgust, the forgotten emotion of psychiatry, is the least recognizable emotion in both groups. On the Reading the Mind in the Eyes Test patients exhibit lower accuracy on positive expressions than their typically developing peers, but do not differ on negative items. In both depressive and typically developing individuals, the ability to recognize emotions behind a mask and performance on the Reading the Mind in the Eyes Test are linked to each other in processing speed, but not recognition accuracy. The outcome provides a blueprint for understanding the complexities of reading language of the eyes within and beyond the COVID-19 pandemic.

The Story behind the Mask: A Narrative Review on Hypomimia in Parkinson's Disease

Facial movements are crucial for social and emotional interaction and well-being. Reduced facial expressions (i.e., hypomimia) is a common feature in patients with Parkinson's disease (PD) and previous studies linked this manifestation to both motor symptoms of the disease and altered emotion recognition and processing. Nevertheless, research on facial motor impairment in PD has been rather scarce and only a limited number of clinical evaluation tools are available, often suffering from poor validation processes and high inter- and intra-rater variability. In recent years, the availability of technology-enhanced quantification methods of facial movements, such as automated video analysis and machine learning application, led to increasing interest in studying hypomimia in PD. In this narrative review, we summarize the current knowledge on pathophysiological hypotheses at the basis of hypomimia in PD, with particular focus on the association between reduced facial expressions and emotional processing and analyze the current evaluation tools and management strategies for this symptom, as well as future research perspectives.

Differences in facial emotion recognition between bipolar disorder and other clinical populations: A systematic review and meta-analysis

Facial emotion (or expression) recognition (FER) is a domain of affective cognition impaired across various psychiatric conditions, including bipolar disorder (BD). We conducted a systematic review and meta-analysis searching for eligible articles published from inception to April 26, 2023, in PubMed/MEDLINE, Scopus, EMBASE, and PsycINFO to examine whether and to what extent FER would differ between people with BD and those with other mental disorders. Thirty-three studies comparing 1506 BD patients with 1973 clinical controls were included in the present systematic review, and twenty-six of them were analyzed in random-effects meta-analyses exploring the discrepancies in discriminating or identifying emotional stimuli at a general and specific level. Individuals with BD were more accurate in identifying each type of emotion during a FER task compared to individuals diagnosed with schizophrenia (SCZ) (SMD = 0.27; p-value = 0.006), with specific differences in the perception of anger (SMD = 0.46; p-value = 1.19e-06), fear (SMD = 0.38; p-value = 8.2e-04), and sadness (SMD = 0.33; p-value = 0.026). In contrast, BD patients were less accurate than individuals with major depressive disorder (MDD) in identifying each type of emotion (SMD = -0.24; p-value = 0.014), but these differences were more specific for sad emotional stimuli (SMD = -0.31; p-value = 0.009). No significant differences were observed when BD was compared with children and adolescents diagnosed with attention-deficit/hyperactivity disorder. FER emerges as a potential integrative instrument for guiding diagnosis by enabling discrimination between BD and SCZ or MDD. Enhancing the standardization of adopted tasks could further enhance the accuracy of this tool, leveraging FER potential as a therapeutic target.

Recognition of masked and unmasked facial expressions in males and females and relations with mental wellness

Background

While the effects of mask wearing/facial occlusion are known to impair facial expression recognition, little is known about the role of mental wellness on facial expression recognition, as well as the influence of sex on misattribution errors (i.e., confusions between emotions). In this large study, we aimed to address the relation between facial expression recognition and loneliness, perceived stress, anxiety, and depression symptoms in male and female adults.

Methods

We assessed the influence of mask-wearing on facial expression recognition [i.e., accuracy and response time (RT)] via an online study in N = 469 adult males and females across Canada.

Results

Expectedly, recognition was impaired under masked conditions (i.e., lower accuracy, longer RTs, more misattribution errors). Females were faster and more accurate than males, with less misattribution errors. A novel finding was that people with higher perceived stress were less accurate at identifying masked fearful faces. Perceived stress influenced the relation between sex and RT to masked happy faces; males with high stress scores were slower to recognize masked happy faces, the opposite was true for females. Finally, this study was among the first to show that higher loneliness predicted shorter RT to unmasked faces.

Impact

Our results show that facial expression recognition is impaired by mask-wearing, and that sex and mental health features are important predictors of performance. Such insight could be detrimental in certain sectors of the population (e.g., health care or education), and inform policies being adopted in future pandemics.

Effect of Action Units, Viewpoint and Immersion on Emotion Recognition Using Dynamic Virtual Faces

Facial affect recognition is a critical skill in human interactions that is often impaired in psychiatric disorders. To address this challenge, tests have been developed to measure and train this skill. Recently, virtual human (VH) and virtual reality (VR) technologies have emerged as novel tools for this purpose. This study investigates the unique contributions of different factors in the communication and perception of emotions conveyed by VHs. Specifically, it examines the effects of the use of action units (AUs) in virtual faces, the positioning of the VH (frontal or mid-profile), and the level of immersion in the VR environment (desktop screen versus immersive VR). Thirty-six healthy subjects participated in each condition. Dynamic virtual faces (DVFs), VHs with facial animations, were used to represent the six basic emotions and the neutral expression. The results highlight the important role of the accurate implementation of AUs in virtual faces for emotion recognition. Furthermore, it is observed that frontal views outperform mid-profile views in both test conditions, while immersive VR shows a slight improvement in emotion recognition. This study provides novel insights into the influence of these factors on emotion perception and advances the understanding and application of these technologies for effective facial emotion recognition training.