The Experts below are selected from a list of 77082 Experts worldwide ranked by ideXlab platform
Kimberly G. Noble - One of the best experts on this subject based on the ideXlab platform.
-
socioeconomic disparities in language input are associated with children s language related Brain Structure and reading skills
Child Development, 2020Co-Authors: Emily C. Merz, Elaine A. Maskus, Samantha A. Melvin, Kimberly G. NobleAbstract:The mechanisms underlying socioeconomic disparities in children's reading skills are not well understood. This study examined associations among socioeconomic background, home linguistic input, Brain Structure, and reading skills in 5-to-9-year-old children (N = 94). Naturalistic home audio recordings and high-resolution, T1-weighted MRI scans were acquired. Children who experienced more adult?child conversational turns or adult words had greater left perisylvian cortical surface area. Language input mediated the association between parental education and left perisylvian cortical surface area. Language input was indirectly associated with children's reading skills via left perisylvian surface area. Left perisylvian surface area mediated the association between parental education and children's reading skills. Language experience may thus partially explain socioeconomic disparities in language-supporting Brain Structure and in turn reading skills.
-
Socioeconomic Disparities in Language Input Are Associated With Children's Language‐Related Brain Structure and Reading Skills
Child development, 2019Co-Authors: Emily C. Merz, Elaine A. Maskus, Samantha A. Melvin, Kimberly G. NobleAbstract:The mechanisms underlying socioeconomic disparities in children's reading skills are not well understood. This study examined associations among socioeconomic background, home linguistic input, Brain Structure, and reading skills in 5-to-9-year-old children (N = 94). Naturalistic home audio recordings and high-resolution, T1-weighted MRI scans were acquired. Children who experienced more adult?child conversational turns or adult words had greater left perisylvian cortical surface area. Language input mediated the association between parental education and left perisylvian cortical surface area. Language input was indirectly associated with children's reading skills via left perisylvian surface area. Left perisylvian surface area mediated the association between parental education and children's reading skills. Language experience may thus partially explain socioeconomic disparities in language-supporting Brain Structure and in turn reading skills.
-
the independent and interacting effects of socioeconomic status and dual language use on Brain Structure and cognition
Developmental Science, 2018Co-Authors: Natalie H Brito, Kimberly G. NobleAbstract:: Family socioeconomic status (SES) is strongly associated with children's cognitive development, and past studies have reported socioeconomic disparities in both neurocognitive skills and Brain Structure across childhood. In other studies, bilingualism has been associated with cognitive advantages and differences in Brain Structure across the lifespan. The aim of the current study is to concurrently examine the joint and independent associations between family SES and dual-language use with Brain Structure and cognitive skills during childhood. A subset of data from the Pediatric Imaging, Neurocognition and Genetics (PING) study was analyzed; propensity score matching established an equal sample (N = 562) of monolinguals and dual-language users with similar socio-demographic characteristics (Mage = 13.5, Range = 3-20 years). When collapsing across all ages, SES was linked to both Brain Structure and cognitive skills. When examining differences by age group, Brain Structure was significantly associated with both income and dual-language use during adolescence, but not earlier in childhood. Additionally, in adolescence, a significant interaction between dual-language use and SES was found, with no difference in cortical surface area (SA) between language groups of higher-SES backgrounds but significantly increased SA for dual-language users from lower-SES families compared to SES-matched monolinguals. These results suggest both independent and interacting associations between SES and dual-language use with Brain development. To our knowledge, this is the first study to concurrently examine dual-language use and socioeconomic differences in Brain Structure during childhood and adolescence.
-
family income parental education and Brain Structure in children and adolescents
Nature Neuroscience, 2015Co-Authors: Kimberly G. Noble, Natalie H Brito, Suzanne M Houston, Hauke Bartsch, Eric Kan, Joshua M Kuperman, Natacha Akshoomoff, David G Amaral, Cinnamon S Bloss, Ondrej LibigerAbstract:Socioeconomic disparities are associated with differences in cognitive development. The extent to which this translates to disparities in Brain Structure is unclear. We investigated relationships between socioeconomic factors and Brain morphometry, independently of genetic ancestry, among a cohort of 1,099 typically developing individuals between 3 and 20 years of age. Income was logarithmically associated with Brain surface area. Among children from lower income families, small differences in income were associated with relatively large differences in surface area, whereas, among children from higher income families, similar income increments were associated with smaller differences in surface area. These relationships were most prominent in regions supporting language, reading, executive functions and spatial skills; surface area mediated socioeconomic differences in certain neurocognitive abilities. These data imply that income relates most strongly to Brain Structure among the most disadvantaged children.
Paul M Thompson - One of the best experts on this subject based on the ideXlab platform.
-
Absolute and relative estimates of genetic and environmental variance in Brain Structure volumes
Brain structure & function, 2019Co-Authors: Lachlan T. Strike, Paul M Thompson, Greig I. De Zubicaray, Katie L. Mcmahon, Narelle K. Hansell, Brendan P. Zietsch, Margaret J. WrightAbstract:Comparing estimates of the amount of genetic and environmental variance for different Brain Structures may elucidate differences in the genetic architecture or developmental constraints of individual Brain Structures. However, most studies compare estimates of relative genetic (heritability) and environmental variance in Brain Structure, which do not reflect differences in absolute variance between Brain regions. Here we used a population sample of young adult twins and singleton siblings of twins (n = 791; M = 23 years, Queensland Twin IMaging study) to estimate the absolute genetic and environmental variance, standardised by the phenotypic mean, in the size of cortical, subcortical, and ventricular Brain Structures. Mean-standardised genetic variance differed widely across Structures [23.5-fold range 0.52% (hippocampus) to 12.28% (lateral ventricles)], but the range of estimates within cortical, subcortical, or ventricular Structures was more moderate (two to fivefold range). There was no association between mean-standardised and relative measures of genetic variance (i.e., heritability) in Brain Structure volumes. We found similar results in an independent sample (n = 1075, M = 29 years, Human Connectome Project). These findings open important new lines of enquiry: namely, understanding the bases of these variance patterns, and their implications regarding the genetic architecture, evolution, and development of the human Brain.
-
polygenic selection underlies evolution of human Brain Structure and behavioral traits
bioRxiv, 2017Co-Authors: Evan R Beiter, Paul M Thompson, Jason L Stein, Simon E Fisher, Ekaterina A Khramtsova, Celia Van Der Merwe, Emile R Chimusa, Corinne N Simonti, Dan J Stein, John A CapraAbstract:Seemingly paradoxical characteristics of psychiatric disorders, including moderate to high prevalence, reduced fecundity, and high heritability have motivated explanations for the persistence of common risk alleles for severe psychiatric phenotypes throughout human evolution. Proposed mechanisms include balancing selection, drift, and weak polygenic adaptation acting either directly, or indirectly through selection on correlated traits. While many mechanisms have been proposed, few have been empirically tested. Leveraging publicly available data of unprecedented sample size, we studied twenty-five traits (i.e., ten neuropsychiatric disorders, three personality traits, total intracranial volume, seven subcortical Brain Structure volume traits, and four complex traits without neuropsychiatric associations) for evidence of several different signatures of selection over a range of evolutionary time scales. Consistent with the largely polygenic architecture of neuropsychiatric traits, we found no enrichment of trait-associated single-nucleotide polymorphisms (SNPs) in regions of the genome that underwent classical selective sweeps (i.e., events which would have driven selected alleles to near fixation). However, we discovered that SNPs associated with some, but not all, behaviors and Brain Structure volumes are enriched in genomic regions under selection since divergence from Neanderthals ~600,000 years ago, and show further evidence for signatures of ancient and recent polygenic adaptation. Individual subcortical Brain Structure volumes demonstrate genome-wide evidence in support of a mosaic theory of Brain evolution while total intracranial volume and height appear to share evolutionary constraints consistent with concerted evolution. We further characterized the biological processes potentially targeted by selection, through expression Quantitative Trait Locus (eQTL) and Gene Ontology (GO) enrichment analyses and found evidence for the role of regulatory functions among selected SNPs in immune and Brain tissues. Taken together, our results suggest that alleles associated with neuropsychiatric, behavioral, and Brain volume phenotypes have experienced both ancient and recent polygenic adaptation in human evolution, acting through neurodevelopmental and immune-mediated pathways.
-
Brain Structure and function associated with younger adults in growth hormone receptor deficient humans
The Journal of Neuroscience, 2017Co-Authors: Kaoru Nashiro, Paul M Thompson, Jaime Guevaraaguirre, Meredith N Braskie, George W Hafzalla, Rico Velasco, Priya Balasubramanian, Min Wei, Mara Mather, Marvin D NelsonAbstract:Growth hormone receptor deficiency (GHRD) results in short stature, enhanced insulin sensitivity, and low circulating levels of insulin and insulin-like growth factor 1 (IGF-1). Previous studies in mice and humans suggested that GHRD has protective effects against age-related diseases, including cancer and diabetes. Whereas GHRD mice show improved age-dependent cognitive performance, the effect of GHRD on human cognition remains unknown. Using MRI, we compared Brain Structure, function, and connectivity between 13 people with GHRD and 12 unaffected relatives. We assessed differences in white matter microstructural integrity, hippocampal volume, subregional volumes, and cortical thickness and surface area of selected regions. We also evaluated Brain activity at rest and during a hippocampal-dependent pattern separation task. The GHRD group had larger surface areas in several frontal and cingulate regions and showed trends toward larger dentate gyrus and CA1 regions of the hippocampus. They had lower mean diffusivity in the genu of the corpus callosum and the anterior thalamic tracts. The GHRD group showed enhanced cognitive performance and greater task-related activation in frontal, parietal, and hippocampal regions compared with controls. Furthermore, they had greater functional synchronicity of activity between the precuneus and the rest of the default mode network at rest. The results suggest that, compared with controls, GHRD subjects have Brain Structure and function that are more consistent with those observed in younger adults reported in previous studies. Further investigation may lead to improved understanding of underlying mechanisms and could contribute to the identification of treatments for age-related cognitive deficits.SIGNIFICANCE STATEMENT People and mice with growth hormone receptor deficiency (GHRD or Laron syndrome) are protected against age-related diseases including cancer and diabetes. However, in humans, it is unknown whether cognitive function and Brain Structure are affected by GHRD. Using MRI, we examined cognition in an Ecuadorian population with GHRD and their unaffected relatives. The GHRD group showed better memory performance than their relatives. The differences in Brain Structure and function that we saw between the two groups were not consistent with variations typically associated with Brain deficits. This study contributes to our understanding of the connection between growth genes and Brain aging in humans and provides data indicating that GHR inhibition has the potential to protect against age-dependent cognitive decline.
-
neuroimaging endophenotypes strategies for finding genes influencing Brain Structure and function
Human Brain Mapping, 2007Co-Authors: David C Glahn, Paul M Thompson, John BlangeroAbstract:It is vitally important to identify the genetic determinants of complex Brain-related disorders such as autism, dementia, mood disorders, and schizophrenia. However, the search for genes predis- posing individuals to these illnesses has been hampered by their genetic and phenotypic complexity and by reliance upon phenomenologically based qualitative diagnostic systems. Neuroimaging endo- phenotypes are quantitative indicators of Brain Structure or function that index genetic liability for an illness. These indices will significantly improve gene discovery and help us to understand the func- tional consequences of specific genes at the level of systems neuroscience. Here, we review the feasibil- ity of using neuroanatomic and neuropsychological measures as endophenotypes for Brain-related dis- orders. Specifically, we examine specific indices of Brain Structure or function that are genetically influ- enced and associated with neurological and psychiatric illness. In addition, we review genetic approaches that capitalize on the use of quantitative traits, including those derived from Brain images. Hum Brain Mapp 28:488-501, 2007. V C 2007 Wiley-Liss, Inc.
-
Genetics of Brain Structure and intelligence.
Annual review of neuroscience, 2005Co-Authors: Arthur W. Toga, Paul M ThompsonAbstract:Genetic influences on Brain morphology and IQ are well studied. A variety of sophisticated Brain-mapping approaches relating genetic influences on Brain Structure and intelligence establishes a regional distribution for this relationship that is consistent with behavioral studies. We highlight those studies that illustrate the complex cortical patterns associated with measures of cognitive ability. A measure of cognitive ability, known as g, has been shown highly heritable across many studies. We argue that these genetic links are partly mediated by Brain Structure that is likewise under strong genetic control. Other factors, such as the environment, obviously play a role, but the predominant determinant appears to genetic.
Arthur W. Toga - One of the best experts on this subject based on the ideXlab platform.
-
Brain Structure differences between chinese and caucasian cohorts a comprehensive morphometry study
Human Brain Mapping, 2018Co-Authors: Lu Zhao, Yuchun Tang, Rui Fang, Arthur W. TogaAbstract:Numerous behavioral observations and Brain function studies have demonstrated that neurological differences exist between East Asians and Westerners. However, the extent to which these factors relate to differences in Brain Structure is still not clear. As the basis of Brain functions, the anatomical differences in Brain Structure play a primary and critical role in the origination of functional and behavior differences. To investigate the underlying differences in Brain Structure between the two cultural/ethnic groups, we conducted a comparative study on education-matched right-handed young male adults (age = 22-29 years) from two cohorts, Han Chinese (n = 45) and Caucasians (n = 45), using high-dimensional structural magnetic resonance imaging (MRI) data. Using two well-validated imaging analysis techniques, surface-based morphometry (SBM) and voxel-based morphometry (VBM), we performed a comprehensive vertex-wise morphometric analysis of the Brain Structures between Chinese and Caucasian cohorts. We identified consistent significant between-group differences in cortical thickness, volume, and surface area in the frontal, temporal, parietal, occipital, and insular lobes as well as the cingulate cortices. The SBM analyses revealed that compared with Caucasians, the Chinese population showed larger cortical Structures in the temporal and cingulate regions, and smaller structural measures in the frontal and parietal cortices. The VBM data of the same sample was well-aligned with the SBM findings. Our findings systematically revealed comprehensive Brain structural differences between young male Chinese and Caucasians, and provided new neuroanatomical insights to the behavioral and functional distinctions in the two cultural/ethnic populations.
-
Genetics of Brain Structure and intelligence.
Annual review of neuroscience, 2005Co-Authors: Arthur W. Toga, Paul M ThompsonAbstract:Genetic influences on Brain morphology and IQ are well studied. A variety of sophisticated Brain-mapping approaches relating genetic influences on Brain Structure and intelligence establishes a regional distribution for this relationship that is consistent with behavioral studies. We highlight those studies that illustrate the complex cortical patterns associated with measures of cognitive ability. A measure of cognitive ability, known as g, has been shown highly heritable across many studies. We argue that these genetic links are partly mediated by Brain Structure that is likewise under strong genetic control. Other factors, such as the environment, obviously play a role, but the predominant determinant appears to genetic.
-
Mapping genetic influences on human Brain Structure.
Annals of Medicine, 2002Co-Authors: Paul M Thompson, Tyrone D. Cannon, Arthur W. TogaAbstract:Recent advances in Brain imaging and genetics have empowered the mapping of genetic and environmental influences on the human Brain. These techniques shed light on the 'nature/nurture' debate, revealing how genes determine individual differences in intelligence quotient (IQ) or risk for disease. They visualize which aspects of Brain Structure and function are heritable, and to what degree, linking these features with behavioral or cognitive traits or disease phenotypes. In genetically transmitted disorders such as schizophrenia, patterns of Brain Structure can be associated with increased disease liability, and sites can be mapped where non-genetic triggers may initiate disease. We recently developed a large-scale computational Brain atlas, including data components from the Finnish Twin registry, to store information on individual variations in Brain Structure and their heritability. Algorithms from random field theory, anatomical modeling, and population genetics were combined to detect a genetic continuum in which Brain Structure is heavily genetically determined in some areas but not others. These algorithmic advances motivate studies of disease in which the normative atlas acts as a quantitative reference for the heritability of structural differences and deficits in patient populations. The resulting genetic Brain maps isolate biological markers for inherited traits and disease susceptibility, which may serve as targets for genetic linkage and association studies. Computational methods from Brain imaging and genetics can be fruitfully merged, to shed light on the inheritance of personality differences and behavioral traits, and the genetic transmission of diseases that affect the human Brain.
Emily C. Merz - One of the best experts on this subject based on the ideXlab platform.
-
socioeconomic disparities in language input are associated with children s language related Brain Structure and reading skills
Child Development, 2020Co-Authors: Emily C. Merz, Elaine A. Maskus, Samantha A. Melvin, Kimberly G. NobleAbstract:The mechanisms underlying socioeconomic disparities in children's reading skills are not well understood. This study examined associations among socioeconomic background, home linguistic input, Brain Structure, and reading skills in 5-to-9-year-old children (N = 94). Naturalistic home audio recordings and high-resolution, T1-weighted MRI scans were acquired. Children who experienced more adult?child conversational turns or adult words had greater left perisylvian cortical surface area. Language input mediated the association between parental education and left perisylvian cortical surface area. Language input was indirectly associated with children's reading skills via left perisylvian surface area. Left perisylvian surface area mediated the association between parental education and children's reading skills. Language experience may thus partially explain socioeconomic disparities in language-supporting Brain Structure and in turn reading skills.
-
Socioeconomic Disparities in Language Input Are Associated With Children's Language‐Related Brain Structure and Reading Skills
Child development, 2019Co-Authors: Emily C. Merz, Elaine A. Maskus, Samantha A. Melvin, Kimberly G. NobleAbstract:The mechanisms underlying socioeconomic disparities in children's reading skills are not well understood. This study examined associations among socioeconomic background, home linguistic input, Brain Structure, and reading skills in 5-to-9-year-old children (N = 94). Naturalistic home audio recordings and high-resolution, T1-weighted MRI scans were acquired. Children who experienced more adult?child conversational turns or adult words had greater left perisylvian cortical surface area. Language input mediated the association between parental education and left perisylvian cortical surface area. Language input was indirectly associated with children's reading skills via left perisylvian surface area. Left perisylvian surface area mediated the association between parental education and children's reading skills. Language experience may thus partially explain socioeconomic disparities in language-supporting Brain Structure and in turn reading skills.
Jianfeng Feng - One of the best experts on this subject based on the ideXlab platform.
-
sleep duration Brain Structure and psychiatric and cognitive problems in children
Molecular Psychiatry, 2020Co-Authors: Wei Cheng, Edmund T Rolls, Weikang Gong, Jie Zhang, Xiaoyong Zhang, Jianfeng FengAbstract:Low sleep duration in adults is correlated with psychiatric and cognitive problems. We performed for the first time a large-scale analysis of sleep duration in children, and how this relates to psychiatric problems including depression, to cognition, and to Brain Structure. Structural MRI was analyzed in relation to sleep duration, and psychiatric and cognitive measures in 11,067 9-11-year-old children from the Adolescent Brain Cognitive Development (ABCD) Study, using a linear mixed model, mediation analysis, and structural equation methods in a longitudinal analysis. Dimensional psychopathology (including depression, anxiety, impulsive behavior) in the children was negatively correlated with sleep duration. Dimensional psychopathology in the parents was also correlated with short sleep duration in their children. The Brain areas in which higher volume was correlated with longer sleep duration included the orbitofrontal cortex, prefrontal and temporal cortex, precuneus, and supramarginal gyrus. Longitudinal data analysis showed that the psychiatric problems, especially the depressive problems, were significantly associated with short sleep duration 1 year later. Further, mediation analysis showed that depressive problems significantly mediate the effect of these Brain regions on sleep. Higher cognitive scores were associated with higher volume of the prefrontal cortex, temporal cortex, and medial orbitofrontal cortex. Public health implications are that psychopathology in the parents should be considered in relation to sleep problems in children. Moreover, we show that Brain Structure is associated with sleep problems in children, and that this is related to whether or not the child has depressive problems.
