No abstract

Improved characterization of quantitative traits and dimensionally distributed complex behaviors during toddlerhood may improve early identification of autism spectrum disorder and related neurodevelopmental disorders. Parents of 205 community-ascertained toddlers (age: mean = 20.2, SD = 2.6 months) completed the Repetitive Behavior Scales for Early Childhood (RBS-EC) and the Video-Referenced Rating of Reciprocal Social Behavior (vrRSB), with longitudinal follow-up of behavioral assessments and/or another round of parent-report questionnaires. Criterion validity was examined both concurrently and longitudinally using the Infant Toddler Social Emotional Assessment (ITSEA) as a criterion anchor. Reciprocal social behavior as measured by the vrRSB was significantly associated with social competence as measured by the ITSEA, longitudinally and concurrently. Reciprocal social behavior was not associated with the externalizing subscale on the ITSEA, providing evidence of discriminant validity. Higher-order repetitive behaviors (restricted interests; rituals and routines) as measured by RBS-EC subscales were associated with the dysregulation and internalizing subscales of the ITSEA, longitudinally and concurrently. All RBS-EC subscales (excepting repetitive motor) were associated concurrently and longitudinally with the dysregulation subscale of the ITSEA. We report evidence of criterion-oriented and discriminant validity for the constructs/domains captured by the RBS-EC and vrRSB. These instruments may be particularly useful in characterizing dimensional variability across the typical-to-atypical continuum.

The development of selective visual attention is critical for effectively engaging with an ever-changing world. Its optimal deployment depends upon interactions between neural, motor, and sensory systems across multiple timescales and neurocognitive loci. Previous work illustrates the spatio-temporal dynamics of these processes in adults, but less is known about this emergent phenomenon early in life. Using data (n = 190; 421 visits) collected between 3 and 35 months of age, we examined the spatio-temporal complexity of young children’s gaze patterns as they viewed stimuli varying in semantic salience. Specifically, we used detrended fluctuation analysis (DFA) to quantify the extent to which infants’ gaze patterns exhibited scale invariant patterns of nested variability, an organizational feature thought to reflect self-organized and optimally flexible system dynamics that are not overly rigid or random. Results indicated that gaze patterns of even the youngest infants exhibited fractal organization that increased with age. Further, fractal organization was greater when children (a) viewed social stimuli compared to stimuli with degraded social information and (b) when they spontaneously gazed at faces. These findings suggest that selective attention is well-organized in infancy, particularly toward social information, and indicate noteworthy growth in these processes across the first years of life.

These findings demonstrate that BPGD better predicted putative antecedents of adverse psychological outcomes-specifically, RRBs and RSBs-than gestation duration alone. These findings provide insight to the link between preterm birth and suboptimal behavioral/psychological outcomes and suggest that high birth weight, which may reflect a more optimal intrauterine environment, may serve as a protective factor irrespective of gestation duration.

Background: To advance early identification efforts, we must detect and characterize neurodevelopmental sequelae of risk among population-based samples early in development. However, variability across the typical-to-atypical continuum and heterogeneity within and across early emerging psychiatric/neurodevelopmental disorders represent fundamental challenges to overcome. Identifying multidimensionally determined profiles of risk, agnostic to DSM categories, via data-driven computational approaches represents an avenue to improve early identification of risk. Methods: Factor mixture modeling (FMM) was used to identify subgroups and characterize phenotypic risk profiles, derived from multiple parent-report measures of typical and atypical behaviors common to autism spectrum disorder, in a community-based sample of 17-to 25-month-old toddlers (n = 1,570). To examine the utility of risk profile classification, a subsample of toddlers (n = 107) was assessed on a distal, independent outcome examining internalizing, externalizing, and dysregulation at approximately 30 months. Results: FMM results identified five asymmetrically sized subgroups. The putative high-and moderate-risk groups comprised 6% of the sample. Followup analyses corroborated the utility of the risk profile classification; the high-, moderate-, and low-risk groups were differentially stratified (i.e., HR > moderate-risk > LR) on outcome measures and comparison of high-and low-risk groups revealed large effect sizes for internalizing (d = 0.83), externalizing (d = 1.39), and dysregulation (d = 1.19). Conclusions: This data-driven approach yielded five subgroups of toddlers, the utility of which was corroborated by later outcomes. Data-driven approaches, leveraging multiple developmentally appropriate dimensional RDoC constructs, hold promise for future efforts aimed toward early identification of at-risk-phenotypes for a variety of early emerging neurodevelopmental disorders.