The overarching goal of this paper is to examine the efficacy of early intervention when viewed through the lens of developmental neuroscience. We begin by briefly summarizing neural development from conception through the first few postnatal years. We emphasize the role of experience during the postnatal period, and consistent with decades of research on critical periods, we argue that experience can represent both a period of opportunity and a period of vulnerability. Because plasticity is at the heart of early intervention, we next turn our attention to the efficacy of early intervention drawing from two distinct literatures: early intervention services for children growing up in disadvantaged environments, and children at elevated likelihood of developing a neurodevelopmental delay or disorder. In the case of the former, we single out interventions that target caregiving and in the case of the latter, we highlight recent work on autism. A consistent theme throughout our review is a discussion of how early intervention is embedded in the developing brain. We conclude our article by discussing the implications our review has for policy, and we then offer recommendations for future research. 

Annual Research Review: Early intervention viewed through the lens of developmental neuroscience

Autism spectrum disorder (ASD) is rather common, presenting with prevalent early problems in social communication and accompanied by repetitive behavior. As vasopressin was implicated not only in salt-water homeostasis and stress-axis regulation, but also in social behavior, its role in the development of ASD might be suggested. In this review, we summarized a wide range of problems associated with ASD to which vasopressin might contribute, from social skills to communication, motor function problems, autonomous nervous system alterations as well as sleep disturbances, and altered sensory information processing. Beside functional connections between vasopressin and ASD, we draw attention to the anatomical background, highlighting several brain areas, including the paraventricular nucleus of the hypothalamus, medial preoptic area, lateral septum, bed nucleus of stria terminalis, amygdala, hippocampus, olfactory bulb and even the cerebellum, either producing vasopressin or containing vasopressinergic receptors (presumably V1a). Sex differences in the vasopressinergic system might underline the male prevalence of ASD. Moreover, vasopressin might contribute to the effectiveness of available off-label therapies as well as serve as a possible target for intervention. In this sense, vasopressin, but paradoxically also V1a receptor antagonist, were found to be effective in some clinical trials. We concluded that although vasopressin might be an effective candidate for ASD treatment, we might assume that only a subgroup (e.g., with stress-axis disturbances), a certain sex (most probably males) and a certain brain area (targeting by means of virus vectors) would benefit from this therapy.

Vasopressin as Possible Treatment Option in Autism Spectrum Disorder

Key Points Question Can a battery of eye-tracking measures accurately identify young children with autism, and does integrating biomarkers with primary care practitioner (PCP) diagnosis provide a method for improving diagnostic accuracy? Findings In this diagnostic study of 146 children aged 14 to 48 months, 6 eye-tracking indices were associated with reference standard autism outcome. A composite eye-tracking biomarker had 78% sensitivity and 77% specificity, and when integrated with PCP diagnosis and diagnostic certainty, had 91% sensitivity and 87% specificity. Meaning These findings suggest that equipping PCPs with a validated, multimethod approach to autism evaluation has the potential to substantially improve access to timely, accurate diagnosis.

Eye-Tracking Biomarkers and Autism Diagnosis in Primary Care

Autism spectrum disorder is a common neurodevelopmental condition that manifests as a disruption in sensory and social skills. Although it has been shown that the brain morphology of individuals with autism is asymmetric, how this differentially affects the structural connectome organization of each hemisphere remains under-investigated. We studied whole-brain structural connectivity-based brain asymmetry in individuals with autism using diffusion magnetic resonance imaging obtained from the Autism Brain Imaging Data Exchange initiative. By leveraging dimensionality reduction techniques, we constructed low-dimensional representations of structural connectivity and calculated their asymmetry index. Comparing the asymmetry index between individuals with autism and neurotypical controls, we found atypical structural connectome asymmetry in the sensory and default-mode regions, particularly showing weaker asymmetry towards the right hemisphere in autism. Network communication provided topological underpinnings by demonstrating that the inferior temporal cortex and limbic and frontoparietal regions showed reduced global network communication efficiency and decreased send-receive network navigation in the inferior temporal and lateral visual cortices in individuals with autism. Finally, supervised machine learning revealed that structural connectome asymmetry could be used as a measure for predicting communication-related autistic symptoms and nonverbal intelligence. Our findings provide insights into macroscale structural connectome alterations in autism and their topological underpinnings. 

Whole-brain structural connectome asymmetry in autism

Autism spectrum disorder is a common neurodevelopmental condition that manifests as a disruption in sensory and social skills. Although it has been shown that the brain morphology of individuals with autism is asymmetric, how this differentially affects the structural connectome organization of each hemisphere remains under-investigated. We studied whole-brain structural connectivity-based brain asymmetry in 47 individuals with autism and 37 healthy controls using diffusion magnetic resonance imaging obtained from the Autism Brain Imaging Data Exchange initiative. By leveraging dimensionality reduction techniques, we constructed low-dimensional representations of structural connectivity and calculated their asymmetry index. We compared the asymmetry index between individuals with autism and neurotypical controls and found atypical structural connectome asymmetry in the sensory, default-mode, and limbic networks and the caudate in autism. Network communication provided topological underpinnings by demonstrating that the temporal and dorsolateral prefrontal regions showed reduced global network communication efficiency and decreased send-receive network navigation in the caudate region in individuals with autism. Finally, supervised machine learning revealed that structural connectome asymmetry is associated with communication-related autistic symptoms and nonverbal intelligence. Our findings provide insights into macroscale structural connectome alterations in autism and their topological underpinnings.

/pdf/whole-brain-structural-connectome-asymmetry-in-autism-2sjx13ce.pdf

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by behavioral features that appear early in life. Although studies have shown that atypical brain functional and structural connectivity are associated with these behavioral traits, the occurrence and initial alterations of brain networks have not been fully investigated. The current study aimed to map early brain network efficiency and information transferring in infants at elevated likelihood (EL) compared to infants at typical likelihood (TL) for ASD in the first year of life. This study used a resting‐state functional near‐infrared spectroscopy (fNIRS) approach to obtain the length and strength of functional connections in the frontal and temporal areas in 45 5‐month‐old and 38 10‐month‐old infants. Modular organization and small‐world properties were detected in both EL and TL infants at 5 and 10 months. In 5‐month‐old EL infants, local and nodal efficiency were significantly greater than age‐matched TL infants, indicating overgrown local connections. Furthermore, we used a support vector machine (SVM) model to classify infants with or without EL based on the obtained global properties of the network, achieving an accuracy of 77.6%. These results suggest that infants with EL for ASD exhibit inefficiencies in the organization of brain networks during the first year of life.

/pdf/atypical-brain-network-development-of-infants-at-elevated-293x7bfd.pdf

Atypical brain network development of infants at elevated likelihood for autism spectrum disorder during the first year of life

Wellbeing does not predict change in parenting behaviours among mothers of young children at elevated likelihood of autism

We aim to investigate early developmental trajectories of the autonomic nervous system (ANS) as indexed by the pupillary light reflex (PLR) in infants with (i.e. preterm birth, feeding difficulties, or siblings of children with autism spectrum disorder) and without (controls) increased likelihood for atypical ANS development. We used eye-tracking to capture the PLR in 216 infants in a longitudinal follow-up study spanning 5 to 24 months of age, and linear mixed models to investigate effects of age and group on three PLR parameters: baseline pupil diameter, latency to constriction and relative constriction amplitude. An increase with age was found in baseline pupil diameter (F(3,273.21) = 13.15, p < 0.001, [Formula: see text] = 0.13), latency to constriction (F(3,326.41) = 3.84, p = 0.010, [Formula: see text] = 0.03) and relative constriction amplitude(F(3,282.53) = 3.70, p = 0.012, [Formula: see text] = 0.04). Group differences were found for baseline pupil diameter (F(3,235.91) = 9.40, p < 0.001, [Formula: see text] = 0.11), with larger diameter in preterms and siblings than in controls, and for latency to constriction (F(3,237.10) = 3.48, p = 0.017, [Formula: see text] = 0.04), with preterms having a longer latency than controls. The results align with previous evidence, with development over time that could be explained by ANS maturation. To better understand the cause of the group differences, further research in a larger sample is necessary, combining pupillometry with other measures to further validate its value. 

/pdf/investigating-the-development-of-the-autonomic-nervous-fvsee3ts.pdf

Investigating the development of the autonomic nervous system in infancy through pupillometry

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Atypical brain network development of infants at elevated likelihood for autism spectrum disorder during the first year of life

Wellbeing does not predict change in parenting behaviours among mothers of young children at elevated likelihood of autism

Investigating the development of the autonomic nervous system in infancy through pupillometry