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To curb the diffusion of the novel coronavirus (SARS-CoV-2), governments worldwide have introduced different policies, including lockdowns, social distancing, and mandatory mask wearing. Face mask wearing, especially, has an impact on the formation of first impressions, given that when meeting someone for the first time, individuals rely on the only available piece of information, the newly met person’s aesthetic appearance, in order to make initial estimations of other traits, such as competence, intelligence, or trustworthiness. However, face mask wearing affects the aesthetic appearance of an individual, creating uncertainty which, in turn, has been reported to reduce others’ perceived trustworthiness. In this paper, the influence of face mask wearing on strangers’ perceived trustworthiness and aesthetic appearance is assessed to verify the impact of this policy on impression formation. Participants (N = 71) have been instructed to assess the trustworthiness and the aesthetic appearance of a selection of 96 images depicting individuals of different ages (children, adults, and older adults), gender (men and women), and ethnicity (Asians or Caucasians). Participants were randomly divided into two groups: an experimental group and a control group. Participants in the experimental group (N = 38) rated faces of individuals wearing a face mask, while participants in the control group rated the same faces but in the absence of a face mask. Images were presented in random order. For each face, participants were asked to rate the aesthetic appearance and perceived trustworthiness of the stranger on two different 100-point Likert scales. Results demonstrate that (i) the correlation between perceived trustworthiness and aesthetic appearance is not affected by the presence of a face mask, and (ii) age, but not ethnicity and gender, influences the magnitude of differences in perceived trustworthiness levels during mask wearing. Ministry of Education (MOE) Published version This research was supported from the Ministry of Education, Singapore, under its Academic Research Fund Tier 1 RT10/19. more...

Deep learning (DL) has greatly contributed to bioelectric signal processing, in particular to extract physiological markers. However, the efficacy and applicability of the results proposed in the literature is often constrained to the population represented by the data used to train the models. In this study, we investigate the issues related to applying a DL model on heterogeneous datasets. In particular, by focusing on heart beat detection from electrocardiogram signals (ECG), we show that the performance of a model trained on data from healthy subjects decreases when applied to patients with cardiac conditions and to signals collected with different devices. We then evaluate the use of transfer learning (TL) to adapt the model to the different datasets. In particular, we show that the classification performance is improved, even with datasets with a small sample size. These results suggest that a greater effort should be made towards the generalizability of DL models applied on bioelectric signals, in particular, by retrieving more representative datasets. Published version A.B. was supported by a Post-doctoral Fellowship within MIUR programme framework “Dipartimenti di Eccellenza” (DiPSCO, University of Trento). more...

Social networking sites have determined radical changes in human life, demanding investigations on online socialization mechanisms. The knowledge acquired on in-person sociability could guide researchers to consider both environmental and genetic features as candidates of online socialization. Here, we explored the impact of the quality of adult attachment and the genetic properties of the Serotonin Transporter Gene (5-HTTLPR) on Instagram social behavior. Experiences in Close Relationships-Revised questionnaire was adopted to assess 57 Instagram users’ attachment pattern in close relationships with partners. Genotypes from the 5-HTTLPR/rs25531 region were extracted from the users’ buccal mucosa and analyzed. Users’ Instagram social behavior was examined from four indexes: number of posts, number of followed users (“followings”) and number of followers, and the Social Desirability Index calculated from the followers to followings ratio. Although no interaction between rs25531 and ECR-R dimensions was found, an association between avoidance in close relationships and Instagram number of followings emerged. Post hoc analyses revealed adult avoidance from the partner predicts the Instagram number of followings with good evidence. Moreover, users reporting high avoidance levels displayed fewer followings than users who reported low levels of avoidance. This research provides a window into the psychobiological understanding of online socialization on Instagram. Ministry of Education (MOE) Nanyang Technological University Published version This research was supported by grants from the NAP SUG (M4081597, 2015-2021) and the Singapore Ministry of Education ACR Tier 1 (RG149/16 and RT10/19) to G.E. more...

Human faces convey a range of emotions and psychobiological signals that support social interactions. Multiple factors potentially mediate the facial expressions of emotions across cultures. To further determine the mechanisms underlying human emotion recognition in a complex and ecological environment, we hypothesized that both behavioral and neurophysiological measures would be influenced by stimuli ethnicity (Japanese, Caucasian) in the context of ambiguous emotional expressions (mid-happy, angry). We assessed the neurophysiological and behavioral responses of neurotypical Japanese adults (N = 27, 13 males) involved in a facial expression recognition task. Results uncover an interaction between universal and culturally-driven mechanisms. No differences in behavioral responses are found between male and female participants, male and female faces, and neutral Japanese versus Caucasian faces. However, Caucasian ambiguous emotional expressions which require more energy-consuming processing, as highlighted by neurophysiological results of the Arousal Index, were judged more accurately than Japanese ones. Additionally, a differential Frontal Asymmetry Index in neuronal activation, the signature of an approach versus avoidance response, is found in male participants according to the gender and emotional valence of the stimuli. Ministry of Education (MOE) Nanyang Technological University Published version This research was supported by grants from the Erasmus + International Credit Mobility to A.B., T.G., and G.G. (2016–2017), the JSPS KAKENHI to H.D. (26461769), the NAP SUG (M4081597, 2015–2021) and the Singapore Ministry of Education ACR Tier 1 (RG149/16 and RT10/19) to G.E. more...

Digital collaborative storytelling can be supported by an online learning-management system like Moodle, encouraging prosocial behaviors and shared representations. This study investigated children’s storytelling and collaborative behaviors during an online storytelling activity throughout the 2020 SARS-CoV-2 home confinement in Spain. From 1st to 5th grade of primary school, one-hundred-sixteen students conducted weekly activities of online storytelling as an extracurricular project of a school in Madrid. Facilitators registered participants’ platform use and collaboration. Stories were audio-recorded, transcribed verbatim, and analyzed using the Bears Family Story Analysis System. Three categories related to the SARS-CoV-2 pandemic were added to the story content analysis. The results indicate that primary students worked collaboratively in an online environment, with some methodology adaptations to 1st and 2nd grade. Story lengths tended to be reduced with age, while cohesion and story structure showed stable values in all grades. All stories were balanced in positive and negative contents, especially in characters’ behavior and relationships, while story problems remained at positive solution levels. In addition, the pandemic theme emerged directly or indirectly in only 15% of the stories. The findings indicate the potential of the online collaborative storytelling activities as a distance-education tool in promoting collaboration and social interactions Published version The authors received no funding for this work. more...

This article provides an overview of studies assessing the early vocalisations of children with autism spectrum disorder (ASD), Rett syndrome (RTT), and fragile X syndrome (FXS) using retrospective video analysis (RVA) during the first 2 years of life. Electronic databases were systematically searched and a total of 23 studies were selected. These studies were then categorised according to whether children were later diagnosed with ASD (13 studies), RTT (8 studies), or FXS (2 studies) and then described in terms of (a) participant characteristics, (b) control group characteristics, (c) video footage, (d) behaviours analysed, and (e) main findings. This overview supports the use of RVA in analysing the early development of vocalisations in children later diagnosed with ASD, RTT, or FXS and provides an in-depth analysis of vocalisation presentation, complex vocalisation production, and the rate and/or frequency of vocalisation production across the three disorders. Implications are discussed in terms of extending crude vocal analyses to more precise methods that might provide more powerful means by which to discriminate between disorders during early development. A greater understanding of the early manifestation of these disorders may then lead to improvements in earlier detection. Accepted version more...