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Social motivation--the psychobiological predisposition for social orienting, seeking social contact, and maintaining social interaction--manifests in early infancy and is hypothesized to be foundational for social communication development in typical and atypical populations. However, the lack of infant social-motivation measures has hindered delineation of associations between infant social motivation, other early-arising social abilities such as joint attention, and language outcomes. To investigate how infant social motivation contributes to joint attention and language, this study utilizes a mixed longitudinal sample of 741 infants at high (HL = 515) and low (LL = 226) likelihood for ASD. Using moderated nonlinear factor analysis (MNLFA), we incorporated items from parent-report measures to establish a novel latent factor model of infant social motivation that exhibits measurement invariance by age, sex, and familial ASD likelihood. We then examined developmental associations between 6- and 12-month social motivation, joint attention at 12-15 months, and language at 24 months of age. On average, greater social-motivation growth from 6-12 months was associated with greater initiating joint attention (IJA) and trend-level increases in sophistication of responding to joint attention (RJA). IJA and RJA were both positively associated with 24-month language abilities. There were no additional associations between social motivation and future language in our path model. These findings substantiate a novel, theoretically driven approach to modeling social motivation and suggest a developmental cascade through which social motivation impacts other foundational skills. These findings have implications for the timing and nature of intervention targets to support social communication development in infancy.

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.

T1- and T2-weighted (T1w and T2w) images are essential for tissue classification and anatomical localization in Magnetic Resonance Imaging (MRI) analyses. However, these anatomical data can be challenging to acquire in non-sedated neonatal cohorts, which are prone to high amplitude movement and display lower tissue contrast than adults. As a result, one of these modalities may be missing or of such poor quality that they cannot be used for accurate image processing, resulting in subject loss. While recent literature attempts to overcome these issues in adult populations using synthetic imaging approaches, evaluation of the efficacy of these methods in pediatric populations and the impact of these techniques in conventional MR analyses has not been performed. In this work, we present two novel methods to generate pseudo-T2w images: the first is based in deep learning and expands upon previous models to 3D imaging without the requirement of paired data, the second is based in nonlinear multi-atlas registration providing a computationally lightweight alternative. We demonstrate the anatomical accuracy of pseudo-T2w images and their efficacy in existing MR processing pipelines in two independent neonatal cohorts. Critically, we show that implementing these pseudo-T2w methods in resting-state functional MRI analyses produces virtually identical functional connectivity results when compared to those resulting from T2w images, confirming their utility in infant MRI studies for salvaging otherwise lost subject data.

A critical question in the study of language development is to understand lexical and syntactic acquisition, which play different roles in speech to the extent it would be natural to surmise they are acquired differently. As measured through the comprehension and production of closed-class words, syntactic ability emerges at roughly the 400-word mark. However, a significant proportion of the developmental work uses a coarse combination of function and content words on the MacArthur-Bates Communicative Development Inventory (MB-CDI). Using the MB-CDI Wordbank database, we implemented a factor analytic approach to distinguish between lexical and syntactic development from the Words and Sentences (WS) form that involves both function words and the explicit categorizations. Although the Words and Gestures (WG) form did not share the factor structure, common WG/WS elements recapitulate the expected age-related changes. This parsing of the MB-CDI may prove simple, yet fruitful in subsequent investigation.

Using the Infant Behavior Questionnaire--Revised in a longitudinal sample of infant siblings of autistic children (HR; n = 427, 171 female, 83.4% White) and a comparison group of low-risk controls (LR, n = 200, 86 female, 81.5% White), collected between 2007 and 2017, this study identified an invariant factor structure of temperament traits across groups at 6 and 12 months. Second, after partitioning the groups by familial risk and diagnostic outcome at 24 months, results reveal an endophenotypic pattern of Positive Emotionality at both 6 and 12 months, (HR-autism spectrum disorder [ASD] < HR-no-ASD < LR). Third, increased 'Duration of Orienting' at 12 months was associated with lower scores on the 24-month developmental outcomes in HR infants. These findings may augment efforts for early identification of ASD.

The present study investigated the relationship between infant temperament characteristics and autism spectrum disorder (ASD) risk status. Temperament was examined at 6, 12, and 24 months in 282 infants at high familial risk for ASD and 114 low-risk controls using the Infant Behavior Questionnaire-Revised and Early Childhood Behavior Questionnaire. Infants were divided into three groups at 24 months: High-Risk Positive--classified as ASD (HR Pos), High-Risk Negative (HR Neg), and Low-Risk Negative (LR Neg). At 6 and 12 months HR Pos infants exhibited lower Surgency and Regulatory Capacity than LR Neg infants. By 12 months they also demonstrated increased Negative Affect. Group differences remained, when early signs of ASD were controlled for, suggesting that temperament differences could be useful targets for understanding the development of ASD.

Gestures are an important social communication skill that infants and toddlers use to convey their thoughts, ideas, and intentions. Research suggests that early gesture use has important downstream impacts on developmental processes, such as language learning. However, autistic children are more likely to have challenges in their gestural development. The current study expands upon previous literature on the differences in gesture use between young autistic and non‐autistic toddlers by collecting data using a parent‐report questionnaire called the MCDI–Words and Gestures at three time points, 12, 18, and 24 months of age. Results (N = 467) showed that high‐likelihood infants who later met diagnostic criteria for ASD (n = 73 HL‐ASD) have attenuated gesture growth from 12 to 24 months for both deictic gestures and symbolic gestures when compared to high‐likelihood infants who later did not meet criteria for ASD (n = 249 HL‐Neg) and low‐likelihood infants who did not meet criteria for ASD (n = 145 LL‐Neg). Other social communicative skills, like play behaviors and imitation, were also found to be impacted in young autistic children when compared to their non‐autistic peers. Understanding early differences in social communication growth before a formal autism diagnosis can provide important insights for early intervention. Lay Summary: As infants learn to talk, they use gestures to communicate. In this study, we used a parent‐report questionnaire to look at the group level differences of gestures in the first 2 years of life by comparing infants who later developed autism to infants who did not develop autism. We found that infants who later developed autism have fewer gestures and a slower rate of gesture growth compared to infants who did not develop autism. Play behaviors and imitation skills were also impacted in young autistic children when compared to their non‐autistic peers. [ABSTRACT FROM AUTHOR]

Pre-diagnostic deficits in social motivation are hypothesized to contribute to autism spectrum disorder (ASD), a heritable neurodevelopmental condition. We evaluated psychometric properties of a social motivation index (SMI) using parent-report item-level data from 597 participants in a prospective cohort of infant siblings at high and low familial risk for ASD. We tested whether lower SMI scores at 6, 12, and 24 months were associated with a 24-month ASD diagnosis and whether social motivation's course differed relative to familial ASD liability. The SMI displayed good internal consistency and temporal stability. Children diagnosed with ASD displayed lower mean SMI T-scores at all ages and a decrease in mean T-scores across age. Lower group-level 6-month scores corresponded with higher familial ASD liability. Among high-risk infants, strong decline in SMI T-scores was associated with 10-fold odds of diagnosis. Infant social motivation is quantifiable by parental report, differentiates children with versus without later ASD by age 6 months, and tracks with familial ASD liability, consistent with a diagnostic and susceptibility marker of ASD. Early decrements and decline in social motivation indicate increased likelihood of ASD, highlighting social motivation's importance to risk assessment and clarification of the ontogeny of ASD. [ABSTRACT FROM AUTHOR]

Children's early language environments are related to later development. Little is known about this association in siblings of children with autism spectrum disorder (ASD), who often experience language delays or have ASD. Fifty-nine 9-month-old infants at high or low familial risk for ASD contributed full-day in-home language recordings. High-risk infants produced more vocalizations than low-risk peers; conversational turns and adult words did not differ by group. Vocalization differences were driven by a subgroup of "hypervocal" infants. Despite more vocalizations overall, these infants engaged in less social babbling during a standardized clinic assessment, and they experienced fewer conversational turns relative to their rate of vocalizations. Two ways in which these individual and environmental differences may relate to subsequent development are discussed.

Prevalence of self-injurious behavior (SIB) is as high as 50% among children with autism spectrum disorder (ASD). Identification of risk factors for the development of SIB is critical to early intervention and prevention. However, there is little empirical research utilizing a prospective design to identify early risk factors for SIB. The purpose of this study was to evaluate behavioral characteristics predicting SIB at age 2 years among 235 infants at high familial risk for ASD. Logistic regression results indicated that presence of SIB or proto-SIB and lower developmental functioning at age 12 months significantly predicted SIB at 24 months. A pattern of persistent SIB over this period was associated with a diagnosis of autism and poorer cognitive and adaptive outcomes.

The association between developmental trajectories of language-related white matter fiber pathways from 6 to 24 months of age and individual differences in language production at 24 months of age was investigated. The splenium of the corpus callosum, a fiber pathway projecting through the posterior hub of the default mode network to occipital visual areas, was examined as well as pathways implicated in language function in the mature brain, including the arcuate fasciculi, uncinate fasciculi, and inferior longitudinal fasciculi. The hypothesis that the development of neural circuitry supporting domain-general orienting skills would relate to later language performance was tested in a large sample of typically developing infants. The present study included 77 infants with diffusion weighted MRI scans at 6, 12 and 24 months and language assessment at 24 months. The rate of change in splenium development varied significantly as a function of language production, such that children with greater change in fractional anisotropy (FA) from 6 to 24 months produced more words at 24 months. Contrary to findings from older children and adults, significant associations between language production and FA in the arcuate, uncinate, or left inferior longitudinal fasciculi were not observed. The current study highlights the importance of tracing brain development trajectories from infancy to fully elucidate emerging brain-behavior associations while also emphasizing the role of the splenium as a key node in the structural network that supports the acquisition of spoken language.

The present study investigated the relationship between infant temperament characteristics and autism spectrum disorder (ASD) risk status. Temperament was examined at 6, 12, and 24 months in 282 infants at high familial risk for ASD and 114 low-risk controls using the Infant Behavior Questionnaire-Revised and Early Childhood Behavior Questionnaire. Infants were divided into three groups at 24 months: High-Risk Positive-classified as ASD (HR Pos), High-Risk Negative (HR Neg), and Low-Risk Negative (LR Neg). At 6 and 12 months HR Pos infants exhibited lower Surgency and Regulatory Capacity than LR Neg infants. By 12 months they also demonstrated increased Negative Affect. Group differences remained, when early signs of ASD were controlled for, suggesting that temperament differences could be useful targets for understanding the development of ASD., Author(s): Sarah J. Paterson [sup.1] , Jason J. Wolff [sup.3] , Jed T. Elison [sup.4] , Breanna Winder-Patel [sup.5] , Lonnie Zwaigenbaum [sup.6] , Annette Estes [sup.7] , Juhi Pandey [...]

Objective: According to Cybernetic Big Five Theory (CB5T), personality traits reflect variation in the parameters of evolved cybernetic mechanisms, and extreme manifestations of these traits correspond to a risk for psychopathology because they threaten the organism's ability to pursue its goals effectively. Our theory of autism as a consequence of low Plasticity extends CB5T to provide a cybernetic account of the origin of autistic traits. The theory argues that, because all psychological competencies are initially developed through exploration, typical development requires sensitivity to the incentive reward value of the unknown (i.e., the unpredicted). According to CB5T, motivation to explore the unknown is the core function underlying the metatrait Plasticity, the shared variance of Extraversion and Openness/Intellect. This theory makes predictions regarding the downstream developmental consequences of early low Plasticity, and each prediction maps well onto autistic symptomatology. Method: We surveyed 387 people. Measures included the Autism Quotient (AQ) scale and International Personality Item Pool items that are indicators of Plasticity and Stability. Results: The association between AQ and Plasticity was β = −.64. Conclusion: A strong negative correlation between Plasticity and AQ suggests ASD may be closely linked to a low sensitivity to the incentive reward value of the unknown. [ABSTRACT FROM AUTHOR]