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Abstract Homophily, the tendency for individuals to preferentially interact with others similar to themselves is typically documented via self-report and, for children, adult report. Few studies have investigated homophily directly using objective measures of social movement. We quantified homophily in children with developmental disabilities (DD) and typical development (TD) using objective measures of position/orientation in preschool inclusion classrooms, designed to promote interaction between these groups of children. Objective measurements were collected using ultra-wideband radio-frequency tracking to determine social approach and social contact, measures of social movement and interaction. Observations of 77 preschoolers (47 with DD, and 30 TD) were conducted in eight inclusion classrooms on a total of 26 days. We compared DD and TD groups with respect to how children approached and shared time in social contact with peers using mixed-effects models. Children in concordant dyads (DD-DD and TD-TD) both moved toward each other at higher velocities and spent greater time in social contact than discordant dyads (DD-TD), evidencing homophily. DD-DD dyads spent less time in social contact than TD-TD dyads but were comparable to TD-TD dyads in their social approach velocities. Children’s preference for similar peers appears to be a pervasive feature of their naturalistic interactions. 

Tuberous Sclerosis Complex (TSC), is a neurocutaneous disorder, associated with a high prevalence of autism spectrum disorder (ASD; ∼50% of individuals). As TSC is a leading cause of syndromic ASD, understanding language development in this population would not only be important for individuals with TSC but may also have implications for those with other causes of syndromic and idiopathic ASD. In this mini review, we consider what is known about language development in this population and how speech and language in TSC are related to ASD. Although up to 70% of individuals with TSC report language difficulties, much of the limited research to date on language in TSC has been based on summary scores from standardized assessments. Missing is a detailed understanding of the mechanisms driving speech and language in TSC and how they relate to ASD. Here, we review recent work suggesting that canonical babbling and volubility—two precursors of language development that predict the emergence of speech and are delayed in infants with idiopathic ASD—are also delayed in infants with TSC. We then look to the broader literature on language development to identify other early precursors of language development that tend to be delayed in children with autism as a guide for future research on speech and language in TSC. We argue that vocal turn-taking, shared attention, and fast mapping are three such skills that can provide important information about how speech and language develop in TSC and where potential delays come from. The overall goal of this line of research is to not only illuminate the trajectory of language in TSC with and without ASD, but to ultimately find strategies for earlier recognition and treatment of the pervasive language difficulties in this population. 

Automated detection of facial action units in infants is challenging. Infant faces have different proportions, less texture, fewer wrinkles and furrows, and unique facial actions relative to adults. For these and related reasons, action unit (AU) detectors that are trained on adult faces may generalize poorly to infant faces. To train and test AU detectors for infant faces, we trained convolutional neural networks (CNN) in adult video databases and fine-tuned these networks in two large, manually annotated, infant video databases that differ in context, head pose, illumination, video resolution, and infant age. AUs were those central to expression of positive and negative emotion. AU detectors trained in infants greatly outperformed ones trained previously in adults. Training AU detectors across infant databases afforded greater robustness to between-database differences than did training database specific AU detectors and outperformed previous state-of-the-art in infant AU detection. The resulting AU detection system, which we refer to as Infant AFAR (Automated Facial Action Recognition), is available to the research community for further testing and applications in infant emotion, social interaction, and related topics.

 

Current models of COVID-19 transmission predict infection from reported or assumed interactions. Here we leverage high-resolution observations of interaction to simulate infectious processes. Ultra-Wide Radio Frequency Identification (RFID) systems were employed to track the real-time physical movements and directional orientation of children and their teachers in 4 preschool classes over a total of 34 observations. An agent-based transmission model combined observed interaction patterns (individual distance and orientation) with CDC-published risk guidelines to estimate the transmission impact of an infected patient zero attending class on the proportion of overall infections, the average transmission rate, and the time lag to the appearance of symptomatic individuals. These metrics highlighted the prophylactic role of decreased classroom density and teacher vaccinations. Reduction of classroom density to half capacity was associated with an 18.2% drop in overall infection proportion while teacher vaccination receipt was associated with a 25.3% drop. Simulation results of classroom transmission dynamics may inform public policy in the face of COVID-19 and similar infectious threats.

 

Although still‐face effects are well‐studied, little is known about the degree to which the Face‐to‐Face/Still‐Face (FFSF) is associated with the production of intense affective displays. Duchenne smiling expresses more intense positive affect than non‐Duchenne smiling, while Duchenne cry‐faces express more intense negative affect than non‐Duchenne cry‐faces. Forty 4‐month‐old infants and their mothers completed the FFSF, and key affect‐indexing facial Action Units (AUs) were coded by expert Facial Action Coding System coders for the first 30 s of each FFSF episode. Computer vision software, automated facial affect recognition (AFAR), identified AUs for the entire 2‐min episodes. Expert coding and AFAR produced similar infant and mother Duchenne and non‐Duchenne FFSF effects, highlighting the convergent validity of automated measurement. Substantive AFAR analyses indicated that both infant Duchenne and non‐Duchenne smiling declined from the FF to the SF, but only Duchenne smiling increased from the SF to the RE. In similar fashion, the magnitude of mother Duchenne smiling changes over the FFSF were 2–4 times greater than non‐Duchenne smiling changes. Duchenne expressions appear to be a sensitive index of intense infant and mother affective valence that are accessible to automated measurement and may be a target for future FFSF research.

 

Classroom engagement plays a crucial role in preschoolers' development, yet the correlates of engagement, especially among children with autism spectrum disorder (ASD) and developmental delays (DD), remains unknown. This study examines levels of engagement with classroom social partners and tasks among children in three groups ASD, DD, and typical development (TD). Here, we asked whether children's vocal interactions (vocalizations to and from peers and teachers) were associated with their classroom engagement with social partners (peers and teachers) and with tasks, and whether the association between classroom engagement and vocal interactions differed between children in the ASD group and their peers in the DD and TD groups. Automated measures of vocalizations and location quantified children's vocal interactions with peers and teachers over the course of the school year. Automated location and vocalization data were used to capture both (1) children's vocal output to specific peers and teachers, and (2) the vocal input they received from those peers and teachers. Participants were 72 3–5‐year‐olds (M_age = 48.6 months, SD = 7.0, 43% girls) and their teachers. Children in the ASD group displayed lower engagement with peers, teachers, and tasks than children in the TD group; they also showed lower engagement with peers than children in the DD group. Overall, children's own vocalizations were positively associated with engagement with social partners. Thus, although children in the ASD group tend to have lower engagement scores than children in the TD group, active participation in vocal interactions appears to support their classroom engagement with teachers and peers.

 

Infants vary in their ability to follow others’ gazes, but it is unclear how these individual differences emerge. We tested whether social motivation levels in early infancy predict later gaze following skills. We longitudinally tracked infants’ (N = 82) gazes and pupil dilation while they observed videos of a woman looking into the camera simulating eye contact (i.e., mutual gaze) and then gazing toward one of two objects, at 2, 4, 6, 8, and 14 months of age. To improve measurement validity, we used confirmatory factor analysis to combine multiple observed measures to index the underlying constructs of social motivation and gaze following. Infants’ social motivation—indexed by their speed of social orienting, duration of mutual gaze, and degree of pupil dilation during mutual gaze—was developmentally stable and positively predicted the development of gaze following—indexed by their proportion of time looking to the target object, first object look difference scores, and first face‐to‐object saccade difference scores—from 6 to 14 months of age. These findings suggest that infants’ social motivation likely plays a role in the development of gaze following and highlight the use of a multi‐measure approach to improve measurement sensitivity and validity in infancy research.