Spatial normalization, registration, and segmentation techniques for Magnetic Resonance Imaging (MRI) often use a target or template volume to facilitate processing, take advantage of prior information, and define a common coordinate system for analysis. In the neuroimaging literature, the MNI305 Talairach-like coordinate system is often used as a standard template. However, when studying pediatric populations, variation from the adult brain makes the MNI305 suboptimal for processing brain images of children. Morphological changes occurring during development render the use of age-appropriate templates desirable to reduce potential errors and minimize bias during processing of pediatric data. This paper presents the methods used to create unbiased, age-appropriate MRI atlas templates for pediatric studies that represent the average anatomy for the age range of 4.5–18.5 years, while maintaining a high level of anatomical detail and contrast. The creation of anatomical T1-weighted, T2-weighted, and proton density-weighted templates for specific developmentally important age-ranges, used data derived from the largest epidemiological, representative (healthy and normal) sample of the U.S. population, where each subject was carefully screened for medical and psychiatric factors and characterized using established neuropsychological and behavioral assessments. . Use of these age-specific templates was evaluated by computing average tissue maps for gray matter, white matter, and cerebrospinal fluid for each specific age range, and by conducting an exemplar voxel-wise deformation-based morphometry study using 66 young (4.5–6.9 years) participants to demonstrate the benefits of using the age-appropriate templates. The public availability of these atlases/templates will facilitate analysis of pediatric MRI data and enable comparison of results between studies in a common standardized space specific to pediatric research.

Summary Brain enlargement has been observed in children with Autism Spectrum Disorder (ASD), but the timing of this phenomenon and its relationship to the appearance of behavioral symptoms is unknown. Retrospective head circumference and longitudinal brain volume studies of 2 year olds followed up at age 4 years, have provided evidence that increased brain volume may emerge early in development.1, 2 Studies of infants at high familial risk for autism can provide insight into the early development of autism and have found that characteristic social deficits in ASD emerge during the latter part of the first and in the second year of life3,4. These observations suggest that prospective brain imaging studies of infants at high familial risk for ASD might identify early post-natal changes in brain volume occurring before the emergence of an ASD diagnosis. In this prospective neuroimaging study of 106 infants at high familial risk of ASD and 42 low-risk infants, we show that cortical surface area hyper-expansion between 6-12 months of age precedes brain volume overgrowth observed between 12-24 months in the 15 high-risk infants diagnosed with autism at 24 months. Brain volume overgrowth was linked to the emergence and severity of autistic social deficits. A deep learning algorithm primarily using surface area information from brain MRI at 6 and 12 months of age predicted the diagnosis of autism in individual high-risk children at 24 months (with a positive predictive value of 81%, sensitivity of 88%). These findings demonstrate that early brain changes unfold during the period in which autistic behaviors are first emerging.

OBJECTIVE Evidence from prospective high-risk infant studies suggests that early symptoms of autism usually emerge late in the first- or early in the second-year of life after a period of relatively typical development. This is the first neuroimaging study to prospectively examine white matter fiber tract organization during this interval in infants who develop autism spectrum disorder (ASD) by 24 months. METHOD Participants included 92 infant siblings from an ongoing imaging study of autism. All participants had diffusion tensor imaging at 6 months and behavioral assessments at 24 months, with a majority contributing additional imaging data at either or both 12 and 24 months. At 24 months, 28 infants met criteria for ASD; 64 infants did not. Microstructural properties of white-matter fiber tracts reported to be associated with ASD or related behaviors were characterized by fractional anisotropy (FA) and radial and axial diffusivity. RESULTS FA trajectories differed significantly between infants who did versus did not develop ASD for 12 of 15 fiber tracts. Development for most fiber tracts in infants with ASD was characterized by elevated FA at 6 months followed by slower developmental change overtime relative to infants without ASD. Thus, by 24 months of age, lower FA values were evident for those with ASD. CONCLUSION These results suggest that the aberrant development of white matter pathways precede the manifestation of autistic symptoms in the first year of life. Longitudinal data are critical to characterizing the dynamic age-related brain and behavior changes underlying this neurodevelopmental disorder.

Importance The study provides novel data to inform the mechanisms by which poverty negatively impacts childhood brain development. Objective To investigate whether income to needs ratio experienced in early childhood impacts brain development at school age and to explore the mediators of this effect. Design Data from a prospective longitudinal study of emotion development in preschool children who participated in neuroimaging at school age were used to investigate the effects of poverty on brain development. Children were assessed annually for 3-6 years prior to the time of a MRI scan during which they were evaluated on psychosocial, behavioral and other developmental dimensions. Setting An academic research unit at the Washington University School of Medicine. Participants Preschoolers 3- 6 years of age were ascertained from primary care and day care sites in the St. Louis metropolitan area and annually assessed behaviorally for 5-10 years. Healthy preschoolers and those with clinical symptoms of depression participated in neuroimaging at school age/early adolescence. Main Outcome Measure(s) The main outcomes of interest were brain volumes of children's white matter and cortical gray matter as well as hippocampus and amygdala obtained using MRI. Mediators of interest were caregiver support/hostility measured observationally during the preschool period and stressful life events measured prospectively. Results Poverty was associated with smaller white and cortical gray matter and hippocampal and amygdala volumes. The effects of poverty on hippocampal volume were mediated by caregiving support/hostility on the left and right as well as stressful life events on the left. Conclusions and Relevance The findings that exposure to poverty in early childhood materially impacts brain development at school age further underscores the importance of attention to the well established deleterious effects of poverty on child development. Findings that these effects on the hippocampus are mediated by caregiving and stressful life events suggest that attempts to enhance early caregiving should be a focused public health target for prevention and early intervention. Findings substantiate the behavioral literature on the negative effects of poverty on child development and provide new data confirming that effects extend to brain development. Mechanisms for these effects on the hippocampus are suggested to inform intervention.

BackgroundTo delineate the early progression of autism spectrum disorder (ASD) symptoms, this study investigated developmental characteristics of infants at high familial risk for ASD (HR), and infants at low risk (LR).MethodsParticipants included 210 HR and 98 LR infants across 4 sites with comparable behavioral data at age 6, 12, and 24 months assessed in the domains of cognitive development (Mullen Scales of Early Learning), adaptive skills (Vineland Adaptive Behavioral Scales), and early behavioral features of ASD (Autism Observation Scale for Infants). Participants evaluated according to the DSM-IV-TR criteria at 24 months and categorized as ASD-positive or ASD-negative were further stratified by empirically derived cutoff scores using the Autism Diagnostic Observation Schedule yielding four groups: HR-ASD-High, HR-ASD-Moderate (HR-ASD-Mod), HR-ASD-Negative (HR-Neg), and LR-ASD-Negative (LR-Neg).ResultsThe four groups demonstrated different developmental trajectories that became increasingly distinct from 6 to 24 months across all domains. At 6 months, the HR-ASD-High group demonstrated less advanced Gross Motor and Visual Reception skills compared with the LR-Neg group. By 12 months, the HR-ASD-High group demonstrated increased behavioral features of ASD and decreased cognitive and adaptive functioning compared to the HR-Neg and LR-Neg groups. By 24 months, both the HR-ASD-High and HR-ASD-Moderate groups demonstrated differences from the LR- and HR-Neg groups in all domains.ConclusionsThese findings reveal atypical sensorimotor development at 6 months of age which is associated with ASD at 24 months in the most severely affected group of infants. Sensorimotor differences precede the unfolding of cognitive and adaptive deficits and behavioral features of autism across the 6- to 24-month interval. The less severely affected group demonstrates later symptom onset, in the second year of life, with initial differences in the social-communication domain.Electronic supplementary materialThe online version of this article (doi:10.1186/s11689-015-9117-6) contains supplementary material, which is available to authorized users.

The National Institutes of Health (NIH) Magnetic Resonance Imaging (MRI) Study of Normal Brain Development is a landmark study in which structural and metabolic brain development and behavior are followed longitudinally from birth to young adulthood in a population-based sample of healthy children. The neuropsychological assessment protocol for children aged 6 to 18 years is described and normative data are presented for participants in that age range (N = 385). For many measures, raw score performance improved steeply from 6 to 10 years, decelerating during adolescence. Sex differences were documented for Block Design (male advantage), CVLT, Pegboard and Coding (female advantage). Household income predicted IQ and achievement, as well as externalizing problems and social competence, but not the other cognitive or behavioral measures. Performance of this healthy sample was generally better than published norms. This linked imaging-clinical/behavioral database will be an invaluable public resource for researchers for many years to come.

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Depression has been linked to increased cortisol reactivity and differences in limbic brain volumes, yet the mechanisms underlying these alterations are unclear. One main hypothesis is that stress causes these effects. This is supported by animal studies showing that chronic stress or glucocorticoid administration can lead to alterations in hippocampal and amygdala structures. Relatedly, life stress is cited as one of the major risk factors for depression and candidate gene studies have related variation in stress-system genes to increased prevalence and severity of depression. The present study tested the hypothesis that genetic profile scores combining variance across 10 single nucleotide polymorphisms from four stress-system genes (CRHR1, NR3C2, NR3C1, and FKBP5) and early life stress would predict increases in cortisol levels during laboratory stressors in 120 preschool-age children (3-5 years old), as well as hippocampal and amygdala volumes assessed with MRI in these same children at school age (7-12 years old). We found that stress-system genetic profile scores positively predicted cortisol levels while the number of stressful/traumatic life events experienced by 3-5 years old negatively predicted cortisol levels. The interaction of genetic profile scores and early life stress predicted left hippocampal and left amygdala volumes. Cortisol partially mediated the effects of genetic variation and life stress on limbic brain volumes, particularly on left amygdala volume. These results suggest that stress-related genetic and early environmental factors contribute to variation in stress cortisol reactivity and limbic brain volumes in children, phenotypes associated with depression in adulthood.