An exploratory study of the effect of age and gender on face scanning during affect recognition in immersive virtual reality.

A person with impaired emotion recognition is not able to correctly identify facial expressions represented by other individuals. The aim of the present study is to assess eyes gaze and facial emotion recognition in a healthy population using dynamic avatars in immersive virtual reality (IVR). For the first time, the viewing of each area of interest of the face in IVR is studied by gender and age. This work in healthy people is conducted to assess the future usefulness of IVR in patients with deficits in the recognition of facial expressions. Seventy-four healthy volunteers participated in the study. The materials used were a laptop computer, a game controller, and a head-mounted display. Dynamic virtual faces randomly representing the six basic emotions plus neutral expression were used as stimuli. After the virtual human represented an emotion, a response panel was displayed with the seven possible options. Besides storing the hits and misses, the software program internally divided the faces into different areas of interest (AOIs) and recorded how long participants looked at each AOI. As regards the overall accuracy of the participants' responses, hits decreased from the youngest to the middle-aged and older adults. Also, all three groups spent the highest percentage of time looking at the eyes, but younger adults had the highest percentage. It is also noteworthy that attention to the face compared to the background decreased with age. Moreover, the hits between women and men were remarkably similar and, in fact, there were no statistically significant differences between them. In general, men paid more attention to the eyes than women, but women paid more attention to the forehead and mouth. In contrast to previous work, our study indicates that there are no differences between men and women in facial emotion recognition. Moreover, in line with previous work, the percentage of face viewing time for younger adults is higher than for older adults. However, contrary to earlier studies, older adults look more at the eyes than at the mouth.Consistent with other studies, the eyes are the AOI with the highest percentage of viewing time. For men the most viewed AOI is the eyes for all emotions in both hits and misses. Women look more at the eyes for all emotions, except for joy, fear, and anger on hits. On misses, they look more into the eyes for almost all emotions except surprise and fear.

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.

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

The negative, mood-congruent cognitive bias described in depression, as well as excessive rumination, have been found to interfere with emotional processing. This study focuses on the assessment of facial recognition of emotions in patients with depression through a new set of dynamic virtual faces (DVFs). The sample consisted of 54 stable patients compared to 54 healthy controls. The experiment consisted in an emotion recognition task using non-immersive virtual reality (VR) with DVFs of six basic emotions and neutral expression. Patients with depression showed a worst performance in facial affect recognition compared to healthy controls. Age of onset was negatively correlated with emotion recognition and no correlation was observed for duration of illness or number of lifetime hospitalizations. There was no correlation for the depression group between emotion recognition and degree of psychopathology, excessive rumination, degree of functioning, or quality of life. Hence, it is important to improve and validate VR tools for emotion recognition to achieve greater methodological homogeneity of studies and to be able to establish more conclusive results.

Behavioral intention of mental health practitioners toward the adoption of virtual humans in affect recognition training.

This paper explores the key factors influencing mental health professionals' behavioral intention to adopt virtual humans as a means of affect recognition training. Therapies targeting social cognition deficits are in high demand given that these deficits are related to a loss of functioning and quality of life in several neuropsychiatric conditions such as schizophrenia, autism spectrum disorders, affective disorders, and acquired brain injury. Therefore, developing new therapies would greatly improve the quality of life of this large cohort of patients. A questionnaire based on the second revision of the Unified Theory of Acceptance and Use of Technology (UTAUT2) questionnaire was used for this study. One hundred and twenty-four mental health professionals responded to the questionnaire after viewing a video presentation of the system. The results confirmed that mental health professionals showed a positive intention to use virtual reality tools to train affect recognition, as they allow manipulation of social interaction with patients. Further studies should be conducted with therapists from other countries to reach more conclusions.

Facial Affect Recognition in Immersive Virtual Reality: Where is the Participant Looking?

The recognition of facial expression of emotions in others is essential in daily social interactions. The different areas of the face play different roles in decoding each emotion. To find out which ones are more important, the traditional approach has been to use eye-tracking devices with static pictures to capture which parts of the face people are looking at when decoding emotions. However, the ecological validity of this approach is limited because, unlike in real life, there is no movement in the face that can be used to identify the emotion. The use of virtual reality technology opens the door to new experiences in which the users perceive that they are in front of dynamic virtual humans. Therefore, our main aim is to investigate whether the user's immersion in a virtual environment influences the way dynamic virtual faces are visually scanned when decoding emotions. An experiment involving 74 healthy participants was carried out. The results obtained are consistent with previous works. Having confirmed the correct functioning of our solution, it is our intention to study whether emotion recognition deficits in patients with neuropsychiatric disorders are related to the way they visually scan faces.

How Interpersonal Distance Between Avatar and Human Influences Facial Affect Recognition in Immersive Virtual Reality.

Purpose: The purpose of this study was to determine the optimal interpersonal distance (IPD) between humans and affective avatars in facial affect recognition in immersive virtual reality (IVR). The ideal IPD is the one in which the humans show the highest number of hits and the shortest reaction times in recognizing the emotions displayed by avatars. The results should help design future therapies to remedy facial affect recognition deficits. Methods: A group of 39 healthy volunteers participated in an experiment in which participants were shown 65 dynamic faces in IVR and had to identify six basic emotions plus neutral expression presented by the avatars. We decided to limit the experiment to five different distances: D1 (35 cm), D2 (55 cm), D3 (75 cm), D4 (95 cm), and D5 (115 cm), all belonging to the intimate and personal interpersonal spaces. Of the total of 65 faces, 13 faces were presented for each of the included distances. The views were shown at different angles: 50% in frontal view, 25% from the right profile, and 25% from the left profile. The order of appearance of the faces presented to each participant was randomized. Results: The overall success rate in facial emotion identification was 90.33%, being D3 the IPD with the best overall emotional recognition hits, although statistically significant differences could not be found between the IPDs. Consistent with results obtained in previous studies, identification rates for negative emotions were higher with increasing IPD, whereas the recognition task improved for positive emotions when IPD was closer. In addition, the study revealed irregular behavior in the facial detection of the emotion surprise. Conclusions: IVR allows us to reliably assess facial emotion recognition using dynamic avatars as all the IPDs tested showed to be effective. However, no statistically significant differences in facial emotion recognition were found among the different IPDs.

Psychosocial remediation in depressive disorders: A systematic review.

BACKGROUND: Social functioning impairment has been described in several psychiatric illness, including depressive disorders. It is associated with a deterioration in global functioning and quality of life, thus there is a growing interest in psychosocial functioning remediation interventions. This systematic review aims to review all psychotherapeutic, pharmacological and biological social functioning interventions in depressive disorders. METHODS: A systematic search was conducted on PubMed, PsycINFO and Scopus from the first articles to 2019 following the PRISMA guidelines. 72 original papers were extracted from an initial number of 1827, based on the selected eligibility criteria. RESULTS: A growing body of research was observed in the last 10 years, with most studies showing a low level of scientific evidence. The main diagnosis found was major depressive disorder and the principal social cognition domains assessed were emotional processing and attributional style. The type of intervention most found was the pharmacological one, followed by psychotherapeutic interventions classified as "non-specific. The efficacy of treatments showed an improvement in depressive symptoms and positive results for emotional processing and attributional style. LIMITATIONS: Because there is a lack of well-controlled designs and really few interventions focusing on its remediation, and low homogeneity on the assessment of social aspects across, a comparison of results and the extraction of general conclusions is quite difficult. CONCLUSIONS: Although a promising body of literature has been developed in recent years on the improvement of psychosocial functioning in patients with depressive disorders, more studies are needed to clarify relevant aspects in this area.

Facial Affect Recognition by Patients with Schizophrenia Using Human Avatars.

People with schizophrenia have difficulty recognizing the emotions in the facial expressions of others, which affects their social interaction and functioning in the community. Static stimuli such as photographs have been used traditionally to examine deficiencies in the recognition of emotions in patients with schizophrenia, which has been criticized by some authors for lacking the dynamism that real facial stimuli have. With the aim of overcoming these drawbacks, in recent years, the creation and validation of virtual humans has been developed. This work presents the results of a study that evaluated facial recognition of emotions through a new set of dynamic virtual humans previously designed by the research team, in patients diagnosed of schizophrenia. The study included 56 stable patients, compared with 56 healthy controls. Our results showed that patients with schizophrenia present a deficit in facial affect recognition, compared to healthy controls (average hit rate 71.6% for patients vs 90.0% for controls). Facial expressions with greater dynamism (compared to less dynamic ones), as well as those presented from frontal view (compared to profile view) were better recognized in both groups. Regarding clinical and sociodemographic variables, the number of hospitalizations throughout life did not correlate with recognition rates. There was also no correlation between functioning or quality of life and recognition. A trend showed a reduction in the emotional recognition rate as a result of increases in Positive and Negative Syndrome Scale (PANSS), being statistically significant for negative PANSS. Patients presented a learning effect during the progression of the task, slightly greater in comparison to the control group. This finding is relevant when designing training interventions for people with schizophrenia. Maintaining the attention of patients and getting them to improve in the proposed tasks is a challenge for today's psychiatry.

Validation of dynamic virtual faces for facial affect recognition.

The ability to recognise facial emotions is essential for successful social interaction. The most common stimuli used when evaluating this ability are photographs. Although these stimuli have proved to be valid, they do not offer the level of realism that virtual humans have achieved. The objective of the present paper is the validation of a new set of dynamic virtual faces (DVFs) that mimic the six basic emotions plus the neutral expression. The faces are prepared to be observed with low and high dynamism, and from front and side views. For this purpose, 204 healthy participants, stratified by gender, age and education level, were recruited for assessing their facial affect recognition with the set of DVFs. The accuracy in responses was compared with the already validated Penn Emotion Recognition Test (ER-40). The results showed that DVFs were as valid as standardised natural faces for accurately recreating human-like facial expressions. The overall accuracy in the identification of emotions was higher for the DVFs (88.25%) than for the ER-40 faces (82.60%). The percentage of hits of each DVF emotion was high, especially for neutral expression and happiness emotion. No statistically significant differences were discovered regarding gender. Nor were significant differences found between younger adults and adults over 60 years. Moreover, there is an increase of hits for avatar faces showing a greater dynamism, as well as front views of the DVFs compared to their profile presentations. DVFs are as valid as standardised natural faces for accurately recreating human-like facial expressions of emotions.

[Cytomegalovirus colitis in an immunocompetent elderly patient]. / Colitis por citomegalovirus en paciente anciano inmunocompetente.

Gastrointestinal tract involvement due to cytomegalovirus infection is a condition that usually occurs in immunocompromised patients, but is uncommon in immunocompetent patients. In a review of 33 cases, the median age was 68 years, and the accompanying symptoms were diarrhoea (76%), abdominal pain (52%), and haematochezia, or melena (27%). The case is presented of ctyomegalovirus colitis in an 85 year-old man with no previously identified immunocompromised states.

Social cognition remediation interventions: A systematic mapping review.

BACKGROUND: Impairments in social cognition have been described in several psychiatric and neurological disorders. Given the importance of the relationship between social cognition and functioning and quality of life in these disorders, there is a growing interest in social cognition remediation interventions. The aim of this study was to carry out a systematic mapping review to describe the state of the art in social cognition training and remediation interventions. METHODS: Publications from 2006 to 2016 on social cognition interventions were reviewed in four databases: Scopus, PsycINFO, PubMed and Embase. From the initial result set of 3229 publications, a final total of 241 publications were selected. RESULTS: The study revealed an increasing interest in social cognition remediation interventions, especially in the fields of psychiatry and psychology, with a gradual growth in the number of publications. These were frequently published in high impact factor journals and underpinned by robust scientific evidence. Most studies were conducted on schizophrenia, followed by autism spectrum disorders. Theory of mind and emotional processing were the focus of most interventions, whilst a limited number of studies addressed attributional bias and social perception. Targeted interventions in social cognition were the most frequent practice in the selected papers, followed by non-specific treatment interventions and broad-based interventions. CONCLUSIONS: Research in social cognition remediation interventions is growing. Further studies are needed on attributional bias and social perception remediation programs, while the comparative efficacy of different interventions also remains unclear.

Digital Technology for Internet Access by Patients With Early-Stage Schizophrenia in Spain: Multicenter Research Study.

BACKGROUND: Digital technology and social networks are part of everyday life in the current internet age, especially among young people. To date, few studies have been published worldwide on the pattern of use of digital technology devices and applications in patients with early-stage schizophrenia and even fewer comparing them with healthy participants (not using data from general population surveys) from the same demographic areas. In Spain, no such study has been carried out. OBJECTIVE: The aim of this study was to analyze how patients with early-stage schizophrenia use internet and social networks compared with healthy participants matched by age and gender and also to examine which devices are utilized to access internet resources. METHODS: A cross-sectional, multicentric study was carried out through a semistructured interview asking about the use of digital technology devices and internet. The sample comprised 90 patients and 90 healthy participants. The semistructured interview was conducted on 30 outpatients and 30 healthy subjects in each of the 3 different cities (Madrid, Alicante, and Cuenca). Student t test was used for continuous variables and chi-square test for categorical variables. In the case of ordinal variables, nonparametric Mann-Whitney U and Kruskal-Wallis H tests for independent samples were performed to compare groups. RESULTS: The results indicated that a large proportion of patients with early-stage schizophrenia have access to different digital devices and use them frequently. In addition, both groups coincide in the order of preference and the purpose for which they use the devices. However, a lower frequency of use of most digital technology devices was detected in patients compared with healthy participants. In the case of some devices, this was due to the impossibility of access and not a lack of interest. CONCLUSIONS: To our knowledge, this is the first study to analyze patterns of internet access and use of digital technology devices and applications in Spanish patients with early-stage schizophrenia compared with healthy participants from the same demographic areas. The results on significant access and use of digital technology and internet shown in this cross-sectional study will allow enhanced and more efficient treatment strategies to be planned, utilizing digital technology devices, for patients with early-stage schizophrenia.

Pharmacological interventions in social cognition deficits: A systematic mapping review.

Social cognition is an important research field in psychiatry due to its relevance in the functioning and quality of life of patients. The objective of this work is to conduct a systematic mapping review of pharmacological strategies for improving social cognition deficits. Publications from 2006 to 2016 were reviewed in Scopus, PsycINFO, PubMed, and Embase. From the initial 1059 publications obtained, a final number of 110 were selected. The results show an increasing interest in pharmacological approaches in different medical fields (especially psychiatry, pharmacology, and endocrinology, with schizophrenia and autism as the most studied disorders), as can be observed in the progressive increase in the number of publications, the high degree of scientific evidence, and the high impact factor of publications. However, it is also observed that most studies were conducted with oxytocin, psychostimulants, and antipsychotics (mainly risperidone and olanzapine), with few studies using other drugs. In the different social cognition domains, the majority of publications were focused on emotional processing or theory of mind, with few studies in other domains. Thus, this systematic mapping review shows that, even though there are increasing research activities, there are some important gaps to cover in future investigation.

Human-Avatar Symbiosis for the Treatment of Auditory Verbal Hallucinations in Schizophrenia through Virtual/Augmented Reality and Brain-Computer Interfaces.

This perspective paper faces the future of alternative treatments that take advantage of a social and cognitive approach with regards to pharmacological therapy of auditory verbal hallucinations (AVH) in patients with schizophrenia. AVH are the perception of voices in the absence of auditory stimulation and represents a severe mental health symptom. Virtual/augmented reality (VR/AR) and brain computer interfaces (BCI) are technologies that are growing more and more in different medical and psychological applications. Our position is that their combined use in computer-based therapies offers still unforeseen possibilities for the treatment of physical and mental disabilities. This is why, the paper expects that researchers and clinicians undergo a pathway toward human-avatar symbiosis for AVH by taking full advantage of new technologies. This outlook supposes to address challenging issues in the understanding of non-pharmacological treatment of schizophrenia-related disorders and the exploitation of VR/AR and BCI to achieve a real human-avatar symbiosis.