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A global multicohort study to map subcortical brain development and cognition in infancy and early childhood. Nat Neurosci 2024; 27:176-186. [PMID: 37996530 PMCID: PMC10774128 DOI: 10.1038/s41593-023-01501-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Accepted: 10/16/2023] [Indexed: 11/25/2023]
Abstract
The human brain grows quickly during infancy and early childhood, but factors influencing brain maturation in this period remain poorly understood. To address this gap, we harmonized data from eight diverse cohorts, creating one of the largest pediatric neuroimaging datasets to date focused on birth to 6 years of age. We mapped the developmental trajectory of intracranial and subcortical volumes in ∼2,000 children and studied how sociodemographic factors and adverse birth outcomes influence brain structure and cognition. The amygdala was the first subcortical volume to mature, whereas the thalamus exhibited protracted development. Males had larger brain volumes than females, and children born preterm or with low birthweight showed catch-up growth with age. Socioeconomic factors exerted region- and time-specific effects. Regarding cognition, males scored lower than females; preterm birth affected all developmental areas tested, and socioeconomic factors affected visual reception and receptive language. Brain-cognition correlations revealed region-specific associations.
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A meta-analysis of mental rotation in the first years of life. Dev Sci 2023; 26:e13381. [PMID: 36843394 DOI: 10.1111/desc.13381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2022] [Revised: 02/10/2023] [Accepted: 02/12/2023] [Indexed: 02/28/2023]
Abstract
Mental rotation, the cognitive process of moving an object in mind to predict how it looks in a new orientation, is coupled to intelligence, learning, and educational achievement. On average, adolescent and adult males solve mental rotation tasks slightly better (i.e., faster and/or more accurate) than females. When such behavioral differences emerge during development, however, remains poorly understood. Here we analyzed effect sizes derived from 62 experiments conducted in 1705 infants aged 3-16 months. We found that male infants recognized rotated objects slightly more reliably than female infants. This difference survives correction for small degrees of publication bias. These findings indicate that gender differences in mental rotation are small and not robustly detectable in the first months of postnatal life. RESEARCH HIGHLIGHTS: We analyzed effect sizes of 62 mental rotation experiments including 1705 infants. Looking time reveals that 3-16-months-old infants are able to perform mental rotation. Mental rotation is slightly more reliable in male infants compared to female infants. Gender difference in mental rotation is robust to small degrees of publication bias.
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Genetic Influences on the Developing Young Brain and Risk for Neuropsychiatric Disorders. Biol Psychiatry 2023; 93:905-920. [PMID: 36932005 PMCID: PMC10136952 DOI: 10.1016/j.biopsych.2023.01.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 01/09/2023] [Accepted: 01/11/2023] [Indexed: 01/30/2023]
Abstract
Imaging genetics provides an opportunity to discern associations between genetic variants and brain imaging phenotypes. Historically, the field has focused on adults and adolescents; very few imaging genetics studies have focused on brain development in infancy and early childhood (from birth to age 6 years). This is an important knowledge gap because developmental changes in the brain during the prenatal and early postnatal period are regulated by dynamic gene expression patterns that likely play an important role in establishing an individual's risk for later psychiatric illness and neurodevelopmental disabilities. In this review, we summarize findings from imaging genetics studies spanning from early infancy to early childhood, with a focus on studies examining genetic risk for neuropsychiatric disorders. We also introduce the Organization for Imaging Genomics in Infancy (ORIGINs), a working group of the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) consortium, which was established to facilitate large-scale imaging genetics studies in infancy and early childhood.
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Mathematical learning deficits originate in early childhood from atypical development of a frontoparietal brain network. PLoS Biol 2021; 19:e3001407. [PMID: 34591838 PMCID: PMC8509954 DOI: 10.1371/journal.pbio.3001407] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 10/12/2021] [Accepted: 09/06/2021] [Indexed: 11/19/2022] Open
Abstract
Mathematical learning deficits are defined as a neurodevelopmental disorder (dyscalculia) in the International Classification of Diseases. It is not known, however, how such deficits emerge in the course of early brain development. Here, we conducted functional and structural magnetic resonance imaging (MRI) experiments in 3- to 6-year-old children without formal mathematical learning experience. We followed this sample until the age of 7 to 9 years, identified individuals who developed deficits, and matched them to a typically developing control group using comprehensive behavioral assessments. Multivariate pattern classification distinguished future cases from controls with up to 87% accuracy based on the regional functional activity of the right posterior parietal cortex (PPC), the network-level functional activity of the right dorsolateral prefrontal cortex (DLPFC), and the effective functional and structural connectivity of these regions. Our results indicate that mathematical learning deficits originate from atypical development of a frontoparietal network that is already detectable in early childhood.
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A meta-analysis of fMRI studies of semantic cognition in children. Neuroimage 2021; 241:118436. [PMID: 34329724 DOI: 10.1016/j.neuroimage.2021.118436] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 07/20/2021] [Accepted: 07/27/2021] [Indexed: 11/26/2022] Open
Abstract
Our capacity to derive meaning from things that we see and words that we hear is unparalleled in other animal species and current AI systems. Despite a wealth of functional magnetic resonance imaging (fMRI) studies on where different semantic features are processed in the adult brain, the development of these systems in children is poorly understood. Here we conducted an extensive database search and identified 50 fMRI experiments investigating semantic world knowledge, semantic relatedness judgments, and the differentiation of visual semantic object categories in children (total N = 1,018, mean age = 10.1 years, range 4-15 years). Synthesizing the results of these experiments, we found consistent activation in the bilateral inferior frontal gyri (IFG), fusiform gyri (FG), and supplementary motor areas (SMA), as well as in the left middle and superior temporal gyri (MTG/STG). Within this system, we found little evidence for age-related changes across childhood and high overlap with the adult semantic system. In sum, the identification of these cortical areas provides the starting point for further research on the mechanisms by which the developing brain learns to make sense of its environment.
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Neurobiological origins of individual differences in mathematical ability. PLoS Biol 2020; 18:e3000871. [PMID: 33090992 PMCID: PMC7580992 DOI: 10.1371/journal.pbio.3000871] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Accepted: 09/18/2020] [Indexed: 01/23/2023] Open
Abstract
Mathematical ability is heritable and related to several genes expressing proteins in the brain. It is unknown, however, which intermediate neural phenotypes could explain how these genes relate to mathematical ability. Here, we examined genetic effects on cerebral cortical volume of 3-6-year-old children without mathematical training to predict mathematical ability in school at 7-9 years of age. To this end, we followed an exploration sample (n = 101) and an independent replication sample (n = 77). We found that ROBO1, a gene known to regulate prenatal growth of cerebral cortical layers, is associated with the volume of the right parietal cortex, a key region for quantity representation. Individual volume differences in this region predicted up to a fifth of the behavioral variance in mathematical ability. Our findings indicate that a fundamental genetic component of the quantity processing system is rooted in the early development of the parietal cortex.
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A meta-analysis of fMRI studies of language comprehension in children. Neuroimage 2020; 215:116858. [PMID: 32304886 DOI: 10.1016/j.neuroimage.2020.116858] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Revised: 04/10/2020] [Accepted: 04/11/2020] [Indexed: 12/14/2022] Open
Abstract
The neural representation of language comprehension has been examined in several meta-analyses of fMRI studies with human adults. To complement this work from a developmental perspective, we conducted a meta-analysis of fMRI studies of auditory language comprehension in human children. Our analysis included 27 independent experiments involving n = 625 children (49% girls) with a mean age of 8.9 years. Activation likelihood estimation and seed-based effect size mapping revealed activation peaks in the pars triangularis of the left inferior frontal gyrus and bilateral superior and middle temporal gyri. In contrast to this distribution of activation in children, previous work in adults found activation peaks in the pars opercularis of the left inferior frontal gyrus and more left-lateralized temporal activation peaks. Accordingly, brain responses during language comprehension may shift from bilateral temporal and left pars triangularis peaks in childhood to left temporal and pars opercularis peaks in adulthood. This shift could be related to the gradually increasing sensitivity of the developing brain to syntactic information.
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Early cortical surface plasticity relates to basic mathematical learning. Neuroimage 2020; 204:116235. [DOI: 10.1016/j.neuroimage.2019.116235] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2019] [Revised: 09/09/2019] [Accepted: 09/27/2019] [Indexed: 01/20/2023] Open
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A new computational approach to estimate whole-brain effective connectivity from functional and structural MRI, applied to language development. Sci Rep 2019; 9:8479. [PMID: 31186486 PMCID: PMC6559954 DOI: 10.1038/s41598-019-44909-6] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2018] [Accepted: 05/23/2019] [Indexed: 12/14/2022] Open
Abstract
Recently introduced effective connectivity methods allow for the in-vivo investigation of large-scale functional interactions between brain regions. However, dynamic causal modeling, the most widely used technique to date, typically captures only a few predefined regions of interest. In this study, we present an alternative computational approach to infer effective connectivity within the entire connectome and show its performance on a developmental cohort with emerging language capacities. The novel approach provides new opportunities to quantify effective connectivity changes in the human brain.
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The emergence of long-range language network structural covariance and language abilities. Neuroimage 2019; 191:36-48. [DOI: 10.1016/j.neuroimage.2019.02.014] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2018] [Revised: 01/28/2019] [Accepted: 02/05/2019] [Indexed: 01/12/2023] Open
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Inside Front Cover: Cover Image, Volume 21, Issue 6. Dev Sci 2018. [DOI: 10.1111/desc.12759] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Neural signatures of co-occurring reading and mathematical difficulties. Dev Sci 2018; 21:e12680. [PMID: 29920856 DOI: 10.1111/desc.12680] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2017] [Accepted: 03/23/2018] [Indexed: 01/13/2023]
Abstract
Impaired abilities in multiple domains is common in children with learning difficulties. Co-occurrence of low reading and mathematical abilities (LRLM) appears in almost every second child with learning difficulties. However, little is known regarding the neural bases of this combination. Leveraging a unique and tightly controlled sample including children with LRLM, isolated low reading ability (LR), and isolated low mathematical ability (LM), we uncover a distinct neural signature in children with co-occurring low reading and mathematical abilities differentiable from LR and LM. Specifically, we show that LRLM is neuroanatomically distinct from both LR and LM based on reduced cortical folding of the right parahippocampal gyrus, a medial temporal lobe region implicated in visual associative learning. LRLM children were further distinguished from LR and LM by patterns of intrinsic functional connectivity between parahippocampal gyrus and brain circuitry underlying reading and numerical quantity processing. Our results critically inform cognitive and neural models of LRLM by implicating aberrations in both domain-specific and domain-general brain regions involved in reading and mathematics. More generally, our results provide the first evidence for distinct multimodal neural signatures associated with LRLM, and suggest that this population displays an independent phenotype of learning difficulty that cannot be explained simply as a combination of isolated low reading and mathematical abilities.
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Hypermyelination of the left auditory cortex in developmental dyslexia. Neurology 2018; 90:e492-e497. [PMID: 29321232 DOI: 10.1212/wnl.0000000000004931] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2017] [Accepted: 10/27/2017] [Indexed: 12/17/2022] Open
Abstract
OBJECTIVE Cortical malformations are documented postmortem in speech processing areas of the dyslexic human brain. The goal of this pilot study was to find out if such anatomic anomalies can be detected noninvasively and in vivo. METHODS We developed a reconstruction of left perisylvian cortex profiles at a resolution of 400 μm using T1 data acquired with ultra-high-field MRI at 7T. Cortical thickness, myelinated cortical thickness, and layer-wise myelination were then compared in 6 men with developmental dyslexia and 6 healthy controls matched for age, sex, handedness, education level, and nonverbal IQ. RESULTS Compared to healthy controls, dyslexic individuals showed comparable cortical thickness (t[1,10] = 1.98, p = 0.311) but significantly increased myelinated cortical thickness ratio (t[1,10] = 3.85, p = 0.013, familywise error-corrected, Cohen d = 2.03), resulting in an area under the receiver operator characteristic curve of 0.944 (p = 0.010, standard error 0.067, 95% confidence interval 0.814-1). Moreover, T1 relaxation, especially in layer IV of the left auditory cortex, was also significantly increased (t[1,10] = 3.32, p = 0.043, familywise-error corrected, Cohen d = 1.67). CONCLUSIONS Our findings provide critical insights into the neurobiological manifestation of the most common learning disorder and suggest that our approach might also shed new light on other neurodevelopmental disorders associated with cortical abnormalities.
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ATP2C2 and DYX1C1 are putative modulators of dyslexia-related MMR. Brain Behav 2017; 7:e00851. [PMID: 29201552 PMCID: PMC5698869 DOI: 10.1002/brb3.851] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/30/2016] [Revised: 08/23/2017] [Accepted: 09/01/2017] [Indexed: 11/07/2022] Open
Abstract
BACKGROUND Dyslexia is a specific learning disorder affecting reading and spelling abilities. Its prevalence is ~5% in German-speaking individuals. Although the etiology of dyslexia largely remains to be determined, comprehensive evidence supports deficient phonological processing as a major contributing factor. An important prerequisite for phonological processing is auditory discrimination and, thus, essential for acquiring reading and spelling skills. The event-related potential Mismatch Response (MMR) is an indicator for auditory discrimination capabilities with dyslexics showing an altered late component of MMR in response to auditory input. METHODS In this study, we comprehensively analyzed associations of dyslexia-specific late MMRs with genetic variants previously reported to be associated with dyslexia-related phenotypes in multiple studies comprising 25 independent single-nucleotide polymorphisms (SNPs) within 10 genes. RESULTS First, we demonstrated validity of these SNPs for dyslexia in our sample by showing that additional inclusion of a polygenic risk score improved prediction of impaired writing compared with a model that used MMR alone. Secondly, a multifactorial regression analysis was conducted to uncover the subset of the 25 SNPs that is associated with the dyslexia-specific late component of MMR. In total, four independent SNPs within DYX1C1 and ATP2C2 were found to be associated with MMR stronger than expected from multiple testing. To explore potential pathomechanisms, we annotated these variants with functional data including tissue-specific expression analysis and eQTLs. CONCLUSION Our findings corroborate the late component of MMR as a potential endophenotype for dyslexia and support tripartite relationships between dyslexia-related SNPs, the late component of MMR and dyslexia.
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Learning to read alters cortico-subcortical cross-talk in the visual system of illiterates. SCIENCE ADVANCES 2017; 3:e1602612. [PMID: 28560333 PMCID: PMC5443643 DOI: 10.1126/sciadv.1602612] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2016] [Accepted: 03/23/2017] [Indexed: 05/22/2023]
Abstract
Learning to read is known to result in a reorganization of the developing cerebral cortex. In this longitudinal resting-state functional magnetic resonance imaging study in illiterate adults, we show that only 6 months of literacy training can lead to neuroplastic changes in the mature brain. We observed that literacy-induced neuroplasticity is not confined to the cortex but increases the functional connectivity between the occipital lobe and subcortical areas in the midbrain and the thalamus. Individual rates of connectivity increase were significantly related to the individual decoding skill gains. These findings crucially complement current neurobiological concepts of normal and impaired literacy acquisition.
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Dyslexia risk gene relates to representation of sound in the auditory brainstem. Dev Cogn Neurosci 2017; 24:63-71. [PMID: 28182973 PMCID: PMC6987796 DOI: 10.1016/j.dcn.2017.01.008] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2016] [Revised: 01/15/2017] [Accepted: 01/15/2017] [Indexed: 12/20/2022] Open
Abstract
Previous studies associate poor reading with unstable speech-evoked brainstem responses. DCDC2 and KIAA0319 risk alleles form a strong genetic link with developmental dyslexia. Genetic burden with KIAA0319 risk is related to unstable speech-evoked brainstem responses. Genetic burden with DCDC2 risk is related to intact speech-evoked brainstem responses. Revealed brain-gene relationships may inform the multifactorial pathophysiology of dyslexia.
Dyslexia is a reading disorder with strong associations with KIAA0319 and DCDC2. Both genes play a functional role in spike time precision of neurons. Strikingly, poor readers show an imprecise encoding of fast transients of speech in the auditory brainstem. Whether dyslexia risk genes are related to the quality of sound encoding in the auditory brainstem remains to be investigated. Here, we quantified the response consistency of speech-evoked brainstem responses to the acoustically presented syllable [da] in 159 genotyped, literate and preliterate children. When controlling for age, sex, familial risk and intelligence, partial correlation analyses associated a higher dyslexia risk loading with KIAA0319 with noisier responses. In contrast, a higher risk loading with DCDC2 was associated with a trend towards more stable responses. These results suggest that unstable representation of sound, and thus, reduced neural discrimination ability of stop consonants, occurred in genotypes carrying a higher amount of KIAA0319 risk alleles. Current data provide the first evidence that the dyslexia-associated gene KIAA0319 can alter brainstem responses and impair phoneme processing in the auditory brainstem. This brain-gene relationship provides insight into the complex relationships between phenotype and genotype thereby improving the understanding of the dyslexia-inherent complex multifactorial condition.
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NRSN1 associated grey matter volume of the visual word form area reveals dyslexia before school. Brain 2016; 139:2792-2803. [PMID: 27343255 DOI: 10.1093/brain/aww153] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2015] [Accepted: 05/08/2016] [Indexed: 02/02/2023] Open
Abstract
Literacy learning depends on the flexibility of the human brain to reconfigure itself in response to environmental influences. At the same time, literacy and disorders of literacy acquisition are heritable and thus to some degree genetically predetermined. Here we used a multivariate non-parametric genetic model to relate literacy-associated genetic variants to grey and white matter volumes derived by voxel-based morphometry in a cohort of 141 children. Subsequently, a sample of 34 children attending grades 4 to 8, and another sample of 20 children, longitudinally followed from kindergarten to first grade, were classified as dyslexics and controls using linear binary support vector machines. The NRSN1-associated grey matter volume of the 'visual word form area' achieved a classification accuracy of ~ 73% in literacy-experienced students and distinguished between later dyslexic individuals and controls with an accuracy of 75% at kindergarten age. These findings suggest that the cortical plasticity of a region vital for literacy might be genetically modulated, thereby potentially preconstraining literacy outcome. Accordingly, these results could pave the way for identifying and treating the most common learning disorder before it manifests itself in school.
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Abstract
Language-processing functions follow heterogeneous developmental trajectories. The human embryo can already distinguish vowels in utero, but grammatical complexity is usually not fully mastered until at least 7 years of age. Examining the current literature, we propose that the ontogeny of the cortical language network can be roughly subdivided into two main developmental stages. In the first stage extending over the first 3 years of life, the infant rapidly acquires bottom-up processing capacities, which are primarily implemented bilaterally in the temporal cortices. In the second stage continuing into adolescence, top-down processes emerge gradually with the increasing functional selectivity and structural connectivity of the left inferior frontal cortex.
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Response to Bornkessel-Schlesewsky et al.--towards a nonhuman primate model of language? Trends Cogn Sci 2015; 19:483. [PMID: 26094088 DOI: 10.1016/j.tics.2015.05.011] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2015] [Revised: 05/19/2015] [Accepted: 05/26/2015] [Indexed: 11/18/2022]
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Genetic dyslexia risk variant is related to neural connectivity patterns underlying phonological awareness in children. Neuroimage 2015; 118:414-21. [PMID: 26080313 DOI: 10.1016/j.neuroimage.2015.06.024] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2014] [Revised: 04/29/2015] [Accepted: 06/06/2015] [Indexed: 11/30/2022] Open
Abstract
Phonological awareness is the best-validated predictor of reading and spelling skill and therefore highly relevant for developmental dyslexia. Prior imaging genetics studies link several dyslexia risk genes to either brain-functional or brain-structural factors of phonological deficits. However, coherent evidence for genetic associations with both functional and structural neural phenotypes underlying variation in phonological awareness has not yet been provided. Here we demonstrate that rs11100040, a reported modifier of SLC2A3, is related to the functional connectivity of left fronto-temporal phonological processing areas at resting state in a sample of 9- to 12-year-old children. Furthermore, we provide evidence that rs11100040 is related to the fractional anisotropy of the arcuate fasciculus, which forms the structural connection between these areas. This structural connectivity phenotype is associated with phonological awareness, which is in turn associated with the individual retrospective risk scores in an early dyslexia screening as well as to spelling. These results suggest a link between a dyslexia risk genotype and a functional as well as a structural neural phenotype, which is associated with a phonological awareness phenotype. The present study goes beyond previous work by integrating genetic, brain-functional and brain-structural aspects of phonological awareness within a single approach. These combined findings might be another step towards a multimodal biomarker for developmental dyslexia.
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Cortical differences in preliterate children at familiar risk of dyslexia are similar to those observed in dyslexic readers. Brain 2015; 138:e378. [DOI: 10.1093/brain/awv036] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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Syntax gradually segregates from semantics in the developing brain. Neuroimage 2014; 100:106-11. [PMID: 24927987 DOI: 10.1016/j.neuroimage.2014.05.080] [Citation(s) in RCA: 50] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2014] [Revised: 05/02/2014] [Accepted: 05/28/2014] [Indexed: 11/15/2022] Open
Abstract
An essential computational component of the human language faculty is syntax as it regulates how words are combined into sentences. Although its neuroanatomical basis is well-specified in adults, its emergence in the maturing brain is not yet understood. Using event-related functional magnetic resonance imaging (fMRI) in a cross-sectional design, we discovered, that in contrast to what is known about adults 3-to-4- and 6-to-7-year-old children do not process syntax independently from semantics at the neural level already before these two types of information are integrated for the interpretation of a sentence. It is not until the end of the 10th year of life that children show a neural selectivity for syntax, segregated and gradually independent from semantics, in the left inferior frontal cortex as in the adult brain. Our results indicate that it takes until early adolescence for the domain-specific selectivity of syntax within the language network to develop.
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