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    Parental socioeconomic status is linked to cortical microstructure and language abilities in children and adolescents
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    Abstract:
    Gradients in parental socioeconomic status (SES) are closely linked to important life outcomes in children and adolescents, such as cognitive abilities, school achievement, and mental health. Parental SES may also influence brain development, with several magnetic resonance imaging (MRI) studies reporting associations with youth brain morphometry. However, MRI signal intensity metrics have not been assessed, but could offer a microstructural correlate, thereby increasing our understanding of SES influences on neurobiology. We computed a parental SES score from family income, parental education and parental occupation, and assessed relations with cortical microstructure as measured by T1w/T2w ratio (n= 504, age=3-21 years). We found negative age-stabile relations between parental SES and T1w/T2w ratio, indicating that youths from lower SES families have higher ratio in widespread frontal, temporal, medial parietal and occipital regions, possibly indicating a more developed cortex. Effect sizes were small, but larger than for conventional morphometric properties i.e. cortical surface area and thickness, which were not significantly associated with parental SES. Youths from lower SES families had poorer language related abilities, but microstructural differences did not mediate these relations. T1w/T2w ratio appears to be a sensitive imaging marker for further exploring the association between parental SES and child brain development.
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    Association (psychology)
    Brain morphometry
    Brain Development
    Language development in preterm children is quite special.Behavioral studies found that preterm children were lagging behind their full term peers in areas such as vocabulary,syntax,and semantic verbal fluency.The effect of preterm birth on language development may last till early adulthood,and the degrees of such lags were influenced by biological and social factors.With the development of brain imaging,studies began to examine the brain development of premature children.Researchers have found group differences in white matter(WM) structures,subcortical gray matter(GM),and the cerebellum among preterm adolescents and their full term peers;yet the brain mechanism of language development in preterm children needs further researches to confirm.The paper describes the latest progress of behavior and neuron studies on preterm children's language development,thus to explore the law of language development and cognitive neuroscience mechanism in preterm children.Research suggests that behavior study and brain research should be combined to extend their advantages,thus to explore the mechanism of the language development of premature children,and to provide unique evidence of language acquirement of normal children.
    Brain Development
    Premature birth
    Citations (0)
    The language environment to which children are exposed has an impact on later language abilities as well as on brain development; however, it is unclear how early such impacts emerge. This study investigates the effects of children's early language environment and socioeconomic status (SES) on brain structure in infancy at 6 and 30 months of age (both sexes included). We used magnetic resonance imaging to quantify concentrations of myelin in specific fiber tracts in the brain. Our central question was whether Language Environment Analysis (LENA) measures from in-home recording devices and SES measures of maternal education predicted myelin concentrations over the course of development. Results indicate that 30-month-old children exposed to larger amounts of in-home adult input showed more myelination in the white matter tracts most associated with language. Right hemisphere regions also show an association with SES, with older children from more highly educated mothers and exposed to more adult input, showing greater myelin concentrations in language-related areas. We discuss these results in relation to the current literature and implications for future research. SIGNIFICANCE STATEMENT This is the first study to look at how brain myelination is impacted by language input and socioeconomic status early in development. We find robust relationships of both factors in language-related brain areas at 30 months of age.
    Brain Development
    Abstract The neonatal period represents a critical phase of human brain development. During this time, the brain shows a dramatic increase in size, but it remains largely unclear how the morphology of the human brain develops in early post-partum life. Here we show that human newborns undergo a rapid formation of brain shape, beyond the expected growth in brain size. Using fractal analysis of structural neuroimaging data, we show that brain shape (i) strongly reflects infant maturity beyond differences in brain size, (ii) significantly outperforms brain size in predicting infant age at scan (mean error ~4 days), (iii) detects persistent alterations in prematurely born infants that are not captured by brain size, (iv) is consistently more sensitive to genetic similarity among neonates, and (v) is superior in predicting which newborns are twin siblings, with up to 97% accuracy. These findings identify the formation of brain shape as a fundamental maturational process in human brain development.
    Human brain
    Brain Development
    Brain morphometry
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    This article discusses recent scientific advances in the study of individual differences in human brain development. Focusing on structural neuroimaging measures of brain morphology and tissue properties, two kinds of variability are related and explored: differences across individuals of the same age and differences across age as a result of development. A recent multidimensional modeling study is explained, which was able to use brain measures to predict an individual's chronological age within about one year on average, in children, adolescents, and young adults between 3 and 20 years old. These findings reveal great regularity in the sequence of the aggregate brain state across different ages and phases of development, despite the pronounced individual differences people show on any single brain measure at any given age. Future research is suggested, incorporating additional measures of brain activity and function. WIREs Cogn Sci 2017, 8:e1389. doi: 10.1002/wcs.1389 For further resources related to this article, please visit the WIREs website.
    Brain Development
    Brain morphometry
    Human brain
    Brain Function
    Citations (27)
    This chapter gives an overview of the field of brain morphometry and development from birth to adult age, including selected methodological considerations and fields of application. Brain development is an area of research where morphometry studies have greatly increased our knowledge, revealing organized patterns where regional differences in cortical, subcortical, and white matter structural maturation play a role for cognitive development. Studies show that early rapid increases in gray matter structures are generally followed by decreases, whereas white matter continues to increase throughout childhood and adolescence. The chapter also highlights the importance of developmental perspectives in structural neuroimaging studies for our understanding of clinical conditions such as schizophrenia, autism spectrum disorders, and epilepsy.
    Brain morphometry
    Brain Development
    Abstract Brain development from 1 to 6 years-of-age anchors the rapid development of a wide range of functional capabilities. However, quantitative growth charts of typical development during this age period are lacking, preventing the identification of early brain abnormalities. Here we characterize the time-dependent individual differences of cortical thickness and subcortical volume in 340 typically developing children and construct regional growth curves for these brain morphological measures. The growth curves reflect four types of time-dependence for cortical thickness and subcortical volume metrics. At the individual level, the growth curve model provides percentiles for each brain region’s cortical thickness or volume during ages 1 to 6, allowing for individualized inferences of brain developmental status relative to the same-age population. The growth curves further demonstrate clinical utility potentials by identifying children with developmental speech and language disorders, achieving high accuracies on data collected on both 1.5T and 3T scanners. Our results fill the knowledge gap in brain morphometrics in a critical development period and provide an avenue for individualized brain developmental status evaluation, with demonstrated sensitivity and generalizability.
    Brain Development
    Brain morphometry
    Growth curve (statistics)