This study examines different ways of measuring the onset of symptoms in autism spectrum disorder (ASD). The present findings suggest that declining developmental skills, consistent with a regressive onset pattern, are common in children with ASD and may be more the rule than the exception. The results question the accuracy of widely used methods of measuring symptom onset and argue against their widespread use.

Many high-profile societal problems involve an individual or group repeatedly attacking another – from child-parent disputes, sexual violence against women, civil unrest, violent conflicts and acts of terror, to current cyber-attacks on national infrastructure and ultrafast cyber-trades attacking stockholders. There is an urgent need to quantify the likely severity and timing of such future acts, shed light on likely perpetrators, and identify intervention strategies. Here we present a combined analysis of multiple datasets across all these domains which account for >100,000 events, and show that a simple mathematical law can benchmark them all. We derive this benchmark and interpret it, using a minimal mechanistic model grounded by state-of-the-art fieldwork. Our findings provide quantitative predictions concerning future attacks; a tool to help detect common perpetrators and abnormal behaviors; insight into the trajectory of a ‘lone wolf'; identification of a critical threshold for spreading a message or idea among perpetrators; an intervention strategy to erode the most lethal clusters; and more broadly, a quantitative starting point for cross-disciplinary theorizing about human aggression at the individual and group level, in both real and online worlds.

Infants at risk for Autism Spectrum Disorders (ASD) may have difficulty integrating smiles into initiating joint attention (IJA) bids. A specific IJA pattern, anticipatory smiling, may communicate preexisting positive affect when an infant smiles at an object and then turns the smile toward the social partner. We compared the development of anticipatory smiling at 8, 10, and 12 months in infant siblings of children with ASD (high-risk siblings) and without ASD (low-risk siblings). High-risk siblings produced less anticipatory smiling than low-risk siblings, suggesting early differences in communicating preexisting positive affect. While early anticipatory smiling distinguished the risk groups, IJA not accompanied by smiling best predicted later severity of ASD-related behavioral characteristics among high-risk siblings. High-risk infants appear to show lower levels of motivation to share positive affect with others. However, facility with initiating joint attention in the absence of a clear index of positive affective motivation appears to be central to the prediction of ASD symptoms.

Although the distinction between positive and negative facial expressions is assumed to be clear and robust, recent research with intense real-life faces has shown that viewers are unable to reliably differentiate the valence of such expressions (Aviezer, Trope, & Todorov, 2012). Yet, the fact that viewers fail to distinguish these expressions does not in itself testify that the faces are physically identical. In experiment 1, the muscular activity of victorious and defeated faces was analyzed. Higher numbers of individually coded facial actions—particularly smiling and mouth opening—were more common among winners than losers, indicating an objective difference in facial activity. In experiment 2, we asked whether supplying participants with valid or invalid information about objective facial activity and valence would alter their ratings. Notwithstanding these manipulations, valence ratings were virtually identical in all groups and participants failed to differentiate between positive and negative faces. While objective differences between intense positive and negative faces are detectable, human viewers do not utilize these differences in determining valence. These results suggest a surprising dissociation between information present in expressions and information used by perceivers.

 36-month-old children with elevated ADHD symptoms had the most screen time. Higher screen time was associated with lower receptive/expressive language scores. Screen time was associated with behavioral phenotype, not family history of ASD/ADHD. Screen time reduction strategies and behavioral management support may benefit families of young children.