Social interaction deficits are evident in many psychiatric conditions and specifically in autism spectrum disorder (ASD), but hard to assess objectively. We present a digital tool to automatically quantify biomarkers of social interaction deficits: the simulated interaction task (SIT), which entails a standardized 7-min simulated dialog via video and the automated analysis of facial expressions, gaze behavior, and voice characteristics. In a study with 37 adults with ASD without intellectual disability and 43 healthy controls, we show the potential of the tool as a diagnostic instrument and for better description of ASD-associated social phenotypes. Using machine-learning tools, we detected individuals with ASD with an accuracy of 73%, sensitivity of 67%, and specificity of 79%, based on their facial expressions and vocal characteristics alone. Especially reduced social smiling and facial mimicry as well as a higher voice fundamental frequency and harmony-to-noise-ratio were characteristic for individuals with ASD. The time-effective and cost-effective computer-based analysis outperformed a majority vote and performed equal to clinical expert ratings.npj Digital Medicine (2020) 3:25 ; https://doi.

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Individuals with Autism Spectrum Disorder (ASD) experience a variety of symptoms sometimes including atypicalities in language use. The study explored differences in semantic network organisation of adults with ASD without intellectual impairment. We assessed clusters and switches in verbal fluency tasks ('animals', 'human feature', 'verbs', 'r-words') via curve fitting in combination with corpus-driven analysis of semantic relatedness and evaluated socio-emotional and motor action related content. Compared to participants without ASD (n = 39), participants with ASD (n = 32) tended to produce smaller clusters, longer switches, and fewer words in semantic conditions (no p values survived Bonferroni-correction), whereas relatedness and content were similar. In ASD, semantic networks underlying cluster formation appeared comparably small without affecting strength of associations or content.

Intrusive memories are a hallmark symptom of post-traumatic stress disorder (PTSD) and oxytocin has been implicated in the formation of intrusive memories. This study investigates how oxytocin influences the acquisition and consolidation of trauma-associated memories and whether these effects are influenced by individual neurobiological and genetic differences. In this randomized, double-blind, placebo-controlled study, 220 healthy women received either a single dose of intranasal 24IU oxytocin or a placebo before exposure to a trauma film paradigm that solicits intrusive memories. We used a “general random forest” machine learning approach to examine whether differences in the noradrenergic and hypothalamic-pituitary-adrenal axis activity, polygenic risk for psychiatric disorders, and genetic polymorphism of the oxytocin receptor influence the effect of oxytocin on the acquisition and consolidation of intrusive memories. Oxytocin induced significantly more intrusive memories than placebo did (t(188.33) = 2.12, p = 0.035, Cohen’s d = 0.30, 95% CI 0.16–0.44). As hypothesized, we found that the effect of oxytocin on intrusive memories was influenced by biological covariates, such as salivary cortisol, heart rate variability, and PTSD polygenic risk scores. The five factors that were most relevant to the oxytocin effect on intrusive memories were included in a Poisson regression, which showed that, besides oxytocin administration, higher polygenic loadings for PTSD and major depressive disorder were directly associated with a higher number of reported intrusions after exposure to the trauma film stressor. These results suggest that intranasal oxytocin amplifies the acquisition and consolidation of intrusive memories and that this effect is modulated by neurobiological and genetic factors. Trial registration: NCT03031405.