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Background Social impairment is a core feature of schizophrenia. It is present throughout the course of the illness from the premorbid stage and resistant to treatments (Green et al, 2008). Given the important role of social deficits in poor outcome, it is imperative to improve social functioning in individuals with schizophrenia (SZ), but currently available pharmacological and psychosocial interventions have not proven to be very effective. However, recent technological advances have enabled the use of virtual reality (VR) to develop novel psychiatric interventions. We have previously reported preliminary feasibility and acceptability findings from a new VR-based social interaction training program that suggests the benefits of simulating and rehearsing social interactions situations in VR (Adery et al, 2018). In the present study, we evaluated predictors and mediators of the clinical outcome of this VR-intervention. Methods 18 outpatients with schizophrenia completed 10 sessions of the social VR training over the course of 5 weeks. At each session, participants were asked to approach and interact with avatars by making appropriate conversations to accomplish social 'missions'. There were 12 different missions varying in difficulty levels and social settings (café, bus stop and shop). Symptoms (BPRS, SAPS, SANS), emotion recognition (BLERT and a novel facial emotion recognition task), social functioning (Social Functioning Scale) and cognitive functioning (IQ, CogState) were examined in relation to the VR game performance at pre- and post-treatment. Multivariate regression models with backward elimination method were used to verify significant predictors of the outcome. Lastly, mediation analyses were evaluated using bootstrapping (n=5000) to specify the relationship between predictors and behavioral changes. Results Negative symptoms, especially alogia, anhedonia and asociality improved significantly by post-assessment. Additionally, attention and emotion recognition improved. Within the VR game, number of incorrect responses declined significantly throughout the training period. In multivariate regression models, baseline and changes in social functioning scores predicted clinical symptom improvement. Furthermore, IQ mediated the relationship between performance change in high-difficulty sessions and improvement in alogia. Alogia improvement mediated the relationship between interpersonal communication changes and VR performance. Discussion Simulation-based social skills VR training game improved clinical symptoms, especially negative symptoms, via changes in social functioning and emotion recognition in schizophrenia. These results suggest that VR-based social skills training may be an effective social intervention method. Although the small sample size limits the scope of our conclusion, the results of the present study illustrate the potential power of technology-based psychiatric interventions. [ABSTRACT FROM AUTHOR]

Background Emotional functioning deficits are a core symptom of schizophrenia contributing to interpersonal difficulties. Emotion perception and expression mediate social interactions by allowing a shared representation of emotional experiences between individuals. Emotion recognition has been consistently found impaired in individuals with schizophrenia. Spontaneous facial mimicry, a process by which individuals automatically imitate each other's facial expressions during interactions, has previously been shown to facilitate emotion recognition. However, studies assessing automatic facial mimicry in schizophrenia have yielded mixed results. Moreover, to our knowledge, spontaneous facial mimicry and emotion recognition have not been assessed simultaneously in individuals with schizophrenia. The primary aim of this study was to test whether automatic facial mimicry deficits underlie emotion recognition impairments in schizophrenia. Methods 21 Individuals with schizophrenia (SZ) and 23 demographically matched controls (CO) completed a novel dynamic emotion recognition task (Emotion Recognition and Rating Application Task, ERRATA) while facial electromyographic (EMG) activity was recorded. ERRATA was designed to display faces of a diverse set of avatars with varying emotional expression at different levels of intensity. Each trial of the ERRATA task consisted of the presentation of an avatar face with neutral expression for 2.5 seconds, after which the avatar's facial expression changed to express an emotion for 2 seconds. Participants were asked to identify the avatar's emotion by selecting from a list of 7 words, and to provide a confidence rating. The BIOPAC MP150 system was used to record EMG in corrugator supercilli and zygomaticus major throughout the ERRATA. To investigate the relationship between functional EMG (fEMG) data, the task performance of the participant and the emotion displayed by the avatar, machine-learning method was implemented. Specifically, fEMG features were used to predict the emotions presented by the avatar, as well as participants' choices. Results SZ performed significantly worse than CO on the ERRATA task. SZ emotion recognition impairment was correlated to negative, but not positive symptoms. When fEMG data were used to predict the emotions displayed by the avatars, the machine-learning models for CO and SZ achieved similar results, which suggests that spontaneous facial mimicry was unimpaired in SZ. However, when we used fEMG data to predict the participants' selected emotions, the models for CO statistically outperformed the SZ models. In CO, fEMG and emotion recognition performance were closely associated but not in SZ. Discussion Although spontaneous facial mimicry was intact in SZ, their ability to identify emotions of others was impaired. These results indicate that whilst the automatic process underlying shared emotional experiences during social encounters is unaffected in schizophrenia, the conscious, explicit process of identifying emotion seems impaired. This finding suggests that emotion recognition deficits in SZ might involve a higher-order mechanism that allows for cross-indexing of unconscious internal states to conceptual categories of emotion. [ABSTRACT FROM AUTHOR]