Autism and schizophrenia share a history of diagnostic conflation that was not definitively resolved until the publication of the DSM-III in 1980. Though now recognized as heterogeneous disorders with distinct developmental trajectories and dissociative features, much of the early nosological confusion stemmed from apparent overlap in certain areas of social dysfunction. In more recent years, separate but substantial literatures have accumulated for autism and schizophrenia demonstrating that abnormalities in social cognition directly contribute to the characteristic social deficits of both disorders. The current paper argues that direct comparison of social cognitive impairment can highlight shared and divergent mechanisms underlying pathways to social dysfunction, a process that can provide significant clinical benefit by informing the development of tailored treatment efforts. Thus, while the history of diagnostic conflation between autism and schizophrenia may have originated in similarities in social dysfunction, the goal of direct comparisons is not to conflate them once again but rather to reveal distinctions that illuminate disorder-specific mechanisms and pathways that contribute to social cognitive impairment.

OBJECTIVE: We examined the clinical significance of moderate and severe selective eating (SE).Two levels of SE were examined in relation to concurrent psychiatric symptoms and as a risk factor for the emergence of later psychiatric symptoms. Findings are intended to guide health care providers to recognize when SE is a problem worthy of intervention.METHODS: A population cohort sample of 917 children aged 24 to 71 months and designated caregivers were recruited via primary care practices at a major medical center in the Southeast as part of an epidemiologic study of preschool anxiety. Caregivers were administered structured diagnostic interviews (the Preschool Age Psychiatric Assessment) regarding the child's eating and related selfregulatory capacities, psychiatric symptoms, functioning, and home environment variables. A subset of 188 dyads were assessed a second time ∼24.7 months from the initial assessment.RESULTS: Both moderate and severe levels of SE were associated with psychopathological symptoms (anxiety, depression, attention-deficit/hyperactivity disorder) both concurrently and prospectively. However, the severity of psychopathological symptoms worsened as SE became more severe. Impairment in family functioning was reported at both levels of SE, as was sensory sensitivity in domains outside of food and the experience of food aversion.

Evidence suggests that differences in motor function are an early feature of autism spectrum disorder (ASD). One aspect of motor ability that develops during childhood is postural control, reflected in the ability to maintain a steady head and body position without excessive sway. Observational studies have documented differences in postural control in older children with ASD. The present study used computer vision analysis to assess midline head postural control, as reflected in the rate of spontaneous head movements during states of active attention, in 104 toddlers between 16–31 months of age (Mean = 22 months), 22 of whom were diagnosed with ASD. Time-series data revealed robust group differences in the rate of head movements while the toddlers watched movies depicting social and nonsocial stimuli. Toddlers with ASD exhibited a significantly higher rate of head movement as compared to non-ASD toddlers, suggesting difficulties in maintaining midline position of the head while engaging attentional systems. The use of digital phenotyping approaches, such as computer vision analysis, to quantify variation in early motor behaviors will allow for more precise, objective, and quantitative characterization of early motor signatures and potentially provide new automated methods for early autism risk identification.

To demonstrate the capability of computer vision analysis to detect atypical orienting and attention behaviors in toddlers with autism spectrum disorder. One hundered and four toddlers of 16-31 months old (mean = 22) participated in this study. Twenty-two of the toddlers had autism spectrum disorder and 82 had typical development or developmental delay. Toddlers watched video stimuli on a tablet while the built-in camera recorded their head movement. Computer vision analysis measured participants' attention and orienting in response to name calls. Reliability of the computer vision analysis algorithm was tested against a human rater. Differences in behavior were analyzed between the autism spectrum disorder group and the comparison group. Reliability between computer vision analysis and human coding for orienting to name was excellent (intra-class coefficient 0.84, 95% confidence interval 0.67-0.91). Only 8% of toddlers with autism spectrum disorder oriented to name calling on >1 trial, compared to 63% of toddlers in the comparison group (p = 0.002). Mean latency to orient was significantly longer for toddlers with autism spectrum disorder (2.02 vs 1.06 s, p = 0.04). Sensitivity for autism spectrum disorder of atypical orienting was 96% and specificity was 38%. Older toddlers with autism spectrum disorder showed less attention to the videos overall (p = 0.03). Automated coding offers a reliable, quantitative method for detecting atypical social orienting and reduced sustained attention in toddlers with autism spectrum disorder.