A global multicohort study to map subcortical brain development and cognition in infancy and early childhood.

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.

Genetic Influences on the Developing Young Brain and Risk for Neuropsychiatric Disorders.

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.

A meta-analysis of mental rotation in the first years of life.

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.

Mathematical learning deficits originate in early childhood from atypical development of a frontoparietal brain network.

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.

A meta-analysis of fMRI studies of semantic cognition in children.

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.

Neurobiological origins of individual differences in mathematical ability.

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.

A meta-analysis of fMRI studies of language comprehension in children.

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 â€‹= â€‹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.

The emergence of dyslexia in the developing brain.

Developmental dyslexia, a severe deficit in literacy learning, is a neurodevelopmental learning disorder. Yet, it is not clear whether existing neurobiological accounts of dyslexia capture potential predispositions of the deficit or consequences of reduced reading experience. Here, we longitudinally followed 32 children from preliterate to school age using functional and structural magnetic resonance imaging techniques. Based on standardised and age-normed reading and spelling tests administered at school age, children were classified as 16 dyslexic participants and 16 controls. This longitudinal design allowed us to disentangle possible neurobiological predispositions for developing dyslexia from effects of individual differences in literacy experience. In our sample, the disorder can be predicted already before literacy learning from auditory cortex gyrification and aberrant downstream connectivity within the speech processing system. These results provide evidence for the notion that dyslexia may originate from an atypical maturation of the speech network that precedes literacy instruction.

Early cortical surface plasticity relates to basic mathematical learning.

Children lay the foundation for later academic achievement by acquiring core mathematical abilities in the first school years. Neural reorganization processes associated with individual differences in early mathematical learning, however, are still poorly understood. To fill this research gap, we followed a sample of 5-6-year-old children longitudinally to the end of second grade in school (age 7-8 years) combining magnetic resonance imaging (MRI) with comprehensive behavioral assessments. We report significant links between the rate of neuroplastic change of cortical surface anatomy, and children's early mathematical skills. In particular, most of the behavioral variance (about 73%) of children's visuospatial abilities was explained by the change in cortical thickness in the right superior parietal cortex. Moreover, half of the behavioral variance (about 55%) of children's arithmetic abilities was explained by the change in cortical folding in the right intraparietal sulcus. Additional associations for arithmetic abilities were found for cortical thickness change of the right temporal lobe, and the left middle occipital gyrus. Visuospatial abilities were related to right precentral and supramarginal thickness, as well as right medial frontal gyrus folding plasticity. These effects were independent of other individual differences in IQ, literacy and maternal education. Our findings highlight the critical role of cortical plasticity during the acquisition of fundamental mathematical abilities.

A new computational approach to estimate whole-brain effective connectivity from functional and structural MRI, applied to language development.

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.

The emergence of long-range language network structural covariance and language abilities.

Language skills increase as the brain matures. Language processing, especially the comprehension of syntactically complex sentences, is supported by a brain network involving functional interactions between left inferior frontal and left temporal regions in the adult brain, with reduced functional interactions in children. Here, we examined the gray matter covariance of the cortical thickness network relevant for syntactic processing in relation to language abilities in preschool children (i.e., 5-year-olds) and analyzed the developmental changes of the cortical thickness covariance cross-sectionally by comparing preschool children, school age children, and adults. Further, to demonstrate the agreement of cortical thickness covariance and white matter connectivity, tractography analyses were performed. Covariance of language-relevant seeds in preschoolers was strongest in contralateral homologous regions. A more adult-like, significant cortical thickness covariance between left frontal and left temporal regions, however, was observed in preschoolers with advanced syntactic language abilities. By comparing the three age groups, we could show that the cortical thickness covariance pattern from the language-associated seeds develops progressively from restricted in preschoolers to widely-distributed brain regions in adults. In addition, our results suggest that the cortical thickness covariance difference of the left inferior frontal gyrus to superior temporal gyrus/sulcus between preschoolers and adults is accompanied by distinctions in the white matter tracts linking these two areas, with more mature white matter in the arcuate fasciculus in adults compared to preschoolers. These findings provide anatomical evidence for developmental changes in language both from the perspective of gray matter structure co-variation within the language network and white matter maturity as the anatomical substrate for the structural covariance.

Neural signatures of co-occurring reading and mathematical difficulties.

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.

Hypermyelination of the left auditory cortex in developmental dyslexia.

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.

ATP2C2 and DYX1C1 are putative modulators of dyslexia-related MMR.

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.

Learning to read alters cortico-subcortical cross-talk in the visual system of illiterates.

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.

Dyslexia risk gene relates to representation of sound in the auditory brainstem.

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.

Predicting early signs of dyslexia at a preliterate age by combining behavioral assessment with structural MRI.

BACKGROUND: Recent studies suggest that neurobiological anomalies are already detectable in pre-school children with a family history of developmental dyslexia (DD). However, there is a lack of longitudinal studies showing a direct link between those differences at a preliterate age and the subsequent literacy difficulties seen in school. It is also not clear whether the prediction of DD in pre-school children can be significantly improved when considering neurobiological predictors, compared to models based on behavioral literacy precursors only. METHODS: We recruited 53 pre-reading children either with (N=25) or without a family risk of DD (N=28). Quantitative T1 MNI data and literacy precursor abilities were assessed at kindergarten age. A subsample of 35 children was tested for literacy skills either one or two years later, that is, either in first or second grade. RESULTS: The group comparison of quantitative T1 measures revealed significantly higher T1 intensities in the left anterior arcuate fascicle (AF), suggesting reduced myelin concentration in preliterate children at risk of DD. A logistic regression showed that DD can be predicted significantly better (p=.024) when neuroanatomical differences between groups are used as predictors (80%) compared to a model based on behavioral predictors only (63%). The Wald statistic confirmed that the T1 intensity of the left AF is a statistically significant predictor of DD (p<.05). CONCLUSIONS: Our longitudinal results provide evidence for the hypothesis that neuroanatomical anomalies in children with a family risk of DD are related to subsequent problems in acquiring literacy. Particularly, solid white matter organization in the left anterior arcuate fascicle seems to play a pivotal role.

NRSN1 associated grey matter volume of the visual word form area reveals dyslexia before school.

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.

The ontogeny of the cortical language network.

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.

Brain Functional and Structural Predictors of Language Performance.

The relation between brain function and behavior on the one hand and the relation between structural changes and behavior on the other as well as the link between the 2 aspects are core issues in cognitive neuroscience. It is an open question, however, whether brain function or brain structure is the better predictor for age-specific cognitive performance. Here, in a comprehensive set of analyses, we investigated the direct relation between hemodynamic activity in 2 pairs of frontal and temporal cortical areas, 2 long-distance white matter fiber tracts connecting each pair and sentence comprehension performance of 4 age groups, including 3 groups of children between 3 and 10 years as well as young adults. We show that the increasing accuracy of processing complex sentences throughout development is correlated with the blood-oxygen-level-dependent activation of 2 core language processing regions in Broca's area and the posterior portion of the superior temporal gyrus. Moreover, both accuracy and speed of processing are correlated with the maturational status of the arcuate fasciculus, that is, the dorsal white matter fiber bundle connecting these 2 regions. The present data provide compelling evidence for the view that brain function and white matter structure together best predict developing cognitive performance.