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The aesthetic appearance of websites can influence the perception of their usability, reliability, and trustworthiness. A majority of studies investigating the relationship between aesthetic features of web pages and their user perception consider only a limited number of web pages’ visual features and focus exclusively on explicit aesthetic judgments. In this work, we aim to overcome the limitations of previous works by employing multiple visual features, as well as implicit aesthetic appreciation measures estimated by individuals’ neurophysiological activity. Furthermore we aim to study the ability of machine learning models to predict the aesthetic judgments of webpages. We also investigate the differences between the prediction accuracy of explicit and implicit judgments of web pages. Our approach, based on the analysis of physiological signals, uses machine learning and neural network models to estimate users’ implicit aesthetic pleasure. In our experiments, a group of young adults (N = 59, 33 females, Mean age = 21.52 years) assessed the aesthetic appeal of 100 web pages and 50 emotional pictures while we recorded their physiological activity. Our results demonstrate that machine learning models have a higher accuracy at predicting users’ explicit judgments, as compared to implicit judgments.

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.

Faces are pivotal social stimuli that convey a tremendous amount of information and trigger numerous cogni-tive processes and consequent behaviors. Among the numerous factors that mediate face perception, we focused our attention on two particular phenomena and their interaction: the Baby Schema effect (BSE) and the Mere Exposure effect (MEE). Accordingly to the BSE, babies’ features are considered “cuter” than adults’ features and motivate people towards protection and caregiving, while the MEE states that familiarity can increase the like-ability of various stimuli, including faces. To investigate how those two factors interact, we carried out a follow-up study of the work of Venturoso et al. (2019) on a Singaporean sample. Singapore is a multicultural city-state where different ethnicities live alongside each other. Participants (ethnic Chinese and Indian) were shown faces of female adults and babies of different ethnic groups (Caucasian, Indian, Chinese and Arabic). Implicit responses were recorded using pupillometry measures, while explicit attitudes were assessed using a questionnaire. Our results confirm the presence of the BSE in both the explicit and implicit measures; specifically, baby faces elicited greater pupillary variations and were rated as more attractive than adult faces. An interaction effect between age and ethnicity was also observed. On the other hand, differences in pupil diameters and pleasantness scores were found between the ethnic groups on adult faces. The above-mentioned differences did not depend on whether stimuli belonged to the ethnic in-group or out-group of the participants, suggesting that exposure to individu-als of different ethnicities reduces in-group favoritism. Further investigation is needed to better understand the complex interaction between BSE and MEE in our increasingly multifaceted reality Ministry of Education (MOE) Nanyang Technological University Published version This research was supported by the NAP Start-up Grant M4081597 (G.E.) from Nanyang Technological University Singapore, the Singapore Ministry of Education ACR Tier-1 Grant (G.E., P.S.), Singapore Ministry of Education ACR Tier1 (G.E.), Singapore Ministry of Education Social Science Research Thematic Grant (MOE2016-SSRTG-017, P.S.). The founder agencies had no role in the conceptualization, design, data collection, analysis, decision to publish, or preparation of the manuscript.

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).

The influence on the global evaluation of a person based on the perception of a single trait is a phenomenon widely investigated in social psychology. Widely regarded as Halo effect, this phenomenon has been studied for more than 100 years now, and findings such as the relationship between aesthetic perception and other personality traits—such as competence and trustworthiness—have since been uncovered. Trustworthiness plays an especially crucial role in individuals' social interactions. Despite the large body of literature published on the Halo effect, and especially on the relationship between aesthetic appearance and perceived trustworthiness, little is known about the overall generalizability of the effect, as almost all of the studies have been conducted on adult participants from Western countries. Moreover, little is known about the stability of the effect over time, in the event of major destabilization, such as the outbreak of a pandemic. In this work, the cross-cultural generalizability of the Halo effect is investigated before and during the first few months of the COVID-19 pandemic. An analysis of the generalizability and stability over time of the Halo effect is presented. Participants (N = 380, N = 145 Asians, N = 235 Caucasians) have been asked to rate the aesthetic appearance and perceived trustworthiness of a set of human faces of different ages, gender, and ethnicity. Result of our analysis demonstrated that the Halo effect (Aesthetic × trustworthiness) is influenced by the age of presented faces, but not by their gender or ethnicity. Moreover, our results show that the strength of the effect can be affected by external events and that the volatility is higher for adults' than children's faces. Ministry of Education (MOE) Nanyang Technological University Published version GE was supported by NAP SUG 2015, Singapore Ministry of Education ACR Tier 1 (RG149/16 and RT10/19). PS was support by Singapore Ministry of Education Academic Research Fund Tier 1 RG55/15 and Social Science Research Thematic Grant MOE2016-SSRTG-017.

The Halo Effect is a widely studied phenomenon that interests multiple disciplines. The relationship between Aesthetics Appearance and perceived Trustworthiness has especially gathered the attention of social scientists. While experimental works compared the strength of the Halo Effect in different situations (e.g. different genders’ faces), little is known about the stability of the Halo. During the COVID-19 pandemic, we have been urged to distance ourselves from others. Similar suggestions may alter the relationship between Aesthetic Appearance and Perceived Trustworthiness. Moreover, previous works reported that individuals’ attachment styles affected their emotional responses to the pandemic. Individuals’ attachment styles may influence the magnitude of change of the Halo. Here we investigate how priming (Social Distancing or Contact with others) affects the strength of the Halo Effect, with respect to individuals’ attachment styles. Participants (N = 298) rated the Aesthetics and Perceived Trustworthiness of strangers’ faces (N = 96) presented twice, before and after the presentation of a prime. Results revealed that individuals’ attachment styles affect the strength of the Halo. However, we found no evidence supporting the fact that different attachment styles lead to differences in the magnitude of changes after priming. Results help shed light on how attachment styles influence individuals’ impression formation. Ministry of Education (MOE) Published version This research was supported by grants from the NAP SUG to GE (M4081597, 2015-2021). Ministry of Education, Singapore, under its Academic Research Fund Tier 1 (RT10/19 and RG55/18). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Oxytocin is a primary neuropeptide which coordinates affiliative behavior. Previous researchers pointed to the association between genetic vulnerability on Oxytocin Receptor Gene (OXTR) and environmental factors (e.g., social relationships) to comprehend social behavior. Although an extensive knowledge of in-person social interactions has been obtained, little is known about online sociability. A gene-environment perspective is adopted to examine how OXTR and adult attachment moderate Instagram behavior. The genetic factors within the regions OXTR/rs53576 (A/A homozygotes vs G-carriers) and OXTR/rs2254298 (G/G homozygotes vs A-carriers) were assessed. The Experience in Close Relationships-Revised (ECR-R) questionnaire was used to collect participants' (N = 57, 16 males) attachment with a partner. The number of posts, followed people (“followings”) and followers were obtained from Instagram, and the Social Desirability Index (SDI) was calculated as the ratio of followers to followings. Interaction effects between OXTR groups and ECR-R scores on the number of posts and SDI were hypothesized. Results showed an effect of rs53576 on the number of Instagram followings. Specifically, people with A/A OXTR/rs53576 genotype had more followings than G-carriers independent of the anxiety or avoidance felt towards their partner. These preliminary results offer insights into future investigations on social media behavior., Gene*Environment; Adult attachment; Close relationship; Oxytocin Receptor Gene; rs53576; rs2254298; Online behavior; Social media; Social network; Instagram

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.

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.

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.

Despite technological advancements in functional Near Infra-Red Spectroscopy (fNIRS) and a rise in the application of the fNIRS in neuroscience experimental designs, the processing of fNIRS data remains characterized by a high number of heterogeneous approaches, implicating the scientific reproducibility and interpretability of the results. For example, a manual inspection is still necessary to assess the quality and subsequent retention of collected fNIRS signals for analysis. Machine Learning (ML) approaches are well-positioned to provide a unique contribution to fNIRS data processing by automating and standardizing methodological approaches for quality control, where ML models can produce objective and reproducible results. However, any successful ML application is grounded in a high-quality dataset of labeled training data, and unfortunately, no such dataset is currently available for fNIRS signals. In this work, we introduce fNIRS-QC, a platform designed for the crowd-sourced creation of a quality control fNIRS dataset. In particular, we (a) composed a dataset of 4385 fNIRS signals, (b) created a web interface to allow multiple users to manually label the signal quality of 510 10 s fNIRS segments. Finally, (c) a subset of the labeled dataset is used to develop a proof-of-concept ML model to automatically assess the quality of fNIRS signals. The developed ML models can serve as a more objective and efficient quality control check that minimizes error from manual inspection and the need for expertise with signal quality control.

Women who abuse illicit drugs often engage in atypical parenting behaviors that interfere with the natural development of mother-infant interaction and attachment. Maternal caregiving deficits leave pronounced adverse consequences in the wake of drug abuse relapse, which often occurs and in early infancy. These are times when the child requires optimal parental care. The contemporary literature documents long-term implications of illicit drug-abuse in parenting on infants. However, factors that drive and sustain the influence of drug abuse on parent-infant outcomes remain elusive. This review adopts a biopsychosocial approach to synthesizing the existing state of knowledge on this issue. Mother-infant interaction is a dynamic socio-relational process that occurs at multiple levels of organization. As such, a biopsychosocial perspective enables us to uncover: (i) roles of specific physiological mechanisms and biological characteristics of atypical parenting in mothers who abuse drugs, (ii) the influence of drugs on maternal psychological state (i.e., beliefs regarding parenting practices, emotional regulation), and (iii) social relationships (i.e., relationships with spouse and other drug abusers) and contextual cues (i.e., triggers) that moderate non-optimal maternal caregiving. A comprehensive review of these key domains provides a nuanced understanding of how these several sources interdependently shape atypical parent-infant interaction amongst drug abusing mothers. Systematic elucidation of major factors underlying drug-abused maternal behaviors facilitates the development of targeted and more effective interventions. Published version

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

Little is known about the physiological response of parents of children with Autism Spectrum Disorder (ASD) to crying of children who have already received the diagnosis of ASD. This study aimed to compare cardiac dynamics via Inter-Beat Interval (IBI) and self-reported emotional states of parents of children with ASD and of parents with typically developing (TD) children while listening to crying of children with ASD (ASD cry) and of typically developing children (TD cry). Analyses revealed higher IBI in parents of children with ASD than IBI in parents of TD children while listening to both cry groups; however no differences on self-reported emotional states were observed. Parents of children with ASD were calmer (higher IBI) than parents of TD children while listening to crying. However, ASD cry did not elicit different IBI compared to TD cry. ASD cry and TD cry were differentiated based on parents’ self-responses about what they felt during the listening of crying, their physiological responses showed no differences. These results highlight the similarities and differences between self-reported emotional states and physiological responses of parents of children with ASD, and also point to the importance of monitoring parents’ physiological responses in addition to their subjective responses. Accepted version