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Living in poverty places children at very high risk for problems across a variety of domains, including schooling, behavioral regulation, and health. Aspects of cognitive functioning, such as information processing, may underlie these kinds of problems. How might poverty affect the brain functions underlying these cognitive processes? Here, we address this question by observing and analyzing repeated measures of brain development of young children between five months and four years of age from economically diverse backgrounds (n = 77). In doing so, we have the opportunity to observe changes in brain growth as children begin to experience the effects of poverty. These children underwent MRI scanning, with subjects completing between 1 and 7 scans longitudinally. Two hundred and three MRI scans were divided into different tissue types using a novel image processing algorithm specifically designed to analyze brain data from young infants. Total gray, white, and cerebral (summation of total gray and white matter) volumes were examined along with volumes of the frontal, parietal, temporal, and occipital lobes. Infants from low-income families had lower volumes of gray matter, tissue critical for processing of information and execution of actions. These differences were found for both the frontal and parietal lobes. No differences were detected in white matter, temporal lobe volumes, or occipital lobe volumes. In addition, differences in brain growth were found to vary with socioeconomic status (SES), with children from lower-income households having slower trajectories of growth during infancy and early childhood. Volumetric differences were associated with the emergence of disruptive behavioral problems.

How does sensory experience shape the development of the visual brain? To answer this eluding question, we examine brain responses to visual categories in a rare group of cataract-reversal individuals who experienced a short transient period of early blindness. Encoding of low-level visual properties is impaired in the early visual cortex (EVC) of cataract-reversal participants, whereas categorical responses in downstream ventral occipito-temporal cortex (VOTC) are preserved. In controls, degrading visual input to mimic the visual deficits of cataracts produces cascading disruptions extending from EVC to VOTC, unlike in the cataract group. A deep neural network trained on altered visual input reproduces this dissociation, supporting the brain findings. These results demonstrate that while EVC is permanently affected by early deprivation, categorical coding in VOTC shows resilience, highlighting different sensitive periods for specific brain regions and computations. This study shows that transient blindness at birth leaves lasting effects on early visual functions, while higher visual regions encoding categories remain unaffected, revealing different sensitive periods for different functions in vision.

The ventral occipitotemporal (vOT) cortex serves as a core region for visual processing, and specific areas of this region show preferential activation for various visual categories such as faces and print. The emergence of such functional specialization in the human cortex represents a pivotal developmental process, which provides a basis for targeted and efficient information processing. For example, functional specialization to print in the left vOT is an important prerequisite for fluent reading. However, it remains unclear, which processes initiate the preferential cortical activations to characters arising in the vOT during child development. Using a multimodal neuroimaging approach with preschool children at familial risk for developmental dyslexia, we demonstrate how varying levels of expertise modulate the neural response to single characters, which represent the building blocks of print units. The level of expertise to characters was manipulated firstly through brief training of false-font speech–sound associations and secondly by comparing characters for which children differed in their level of familiarity and expertise accumulated through abundant exposure in their everyday environment. Neural correlates of character processing were tracked with simultaneous high-density electroencephalography and functional magnetic resonance imaging in a target detection task. We found training performance and expertise-dependent modulation of the visual event-related potential around 220 ms (N1) and the corresponding vOT activation. Additionally, trained false-font characters revealed stronger functional connectivity between the left fusiform gyrus (FFG) seed and left superior parietal/lateral occipital cortex regions with higher training performance. In sum, our results demonstrate that learning artificial-character speech–sound associations enhances activation to trained characters in the vOT and that the magnitude of this activation and the functional connectivity of the left FFG to the parieto-occipital cortex depends on learning performance. This pattern of results suggests emerging development of the reading network after brief training that parallels network specialization during reading acquisition. •Artificial character-speech sound training induced preferred N1 and vOT activation.•N1 and vOT BOLD tuning depends on training performance in prereaders.•Functional connectivity of left FFG and SPL also depends on training performance.•Level of expertise to character types modulates the N1 and vOT BOLD activation.•Results suggest a phonologically guided N1 and vOT tuning in children.

Recent findings indicate robust associations between socioeconomic status (SES) and brain structure in children, raising questions about the ways in which SES may modify structural brain development. In general, cortical thickness and surface area develop in nonlinear patterns across childhood and adolescence, with developmental patterns varying to some degree by cortical region. Here, we examined whether age-related nonlinear changes in cortical thickness and surface area varied by SES, as indexed by family income and parental education. We hypothesized that SES disparities in age-related change may be particularly evident for language- and literacy-supporting cortical regions. Participants were 1148 typically-developing individuals between 3 and 20 years of age. Results indicated that SES factors moderate patterns of age-associated change in cortical thickness but not surface area. Specifically, at lower levels of SES, associations between age and cortical thickness were curvilinear, with relatively steep age-related decreases in cortical thickness earlier in childhood, and subsequent leveling off during adolescence. In contrast, at high levels of SES, associations between age and cortical thickness were linear, with consistent reductions across the age range studied. Notably, this interaction was prominent in the left fusiform gyrus, a region that is critical for reading development. In a similar pattern, SES factors significantly moderated linear age-related change in left superior temporal gyrus, such that higher SES was linked with steeper age-related decreases in cortical thickness in this region. These findings suggest that SES may moderate patterns of age-related cortical thinning, especially in language- and literacy-supporting cortical regions.

The ability to attribute mental states to other individuals is crucial for human cognition. A milestone of this ability is reached around the age of 4, when children start understanding that others can have false beliefs about the world. The neural basis supporting this critical step is currently unknown. Here, we relate this behavioural change to the maturation of white matter structure in 3- and 4-year-old children. Tract-based spatial statistics and probabilistic tractography show that the developmental breakthrough in false belief understanding is associated with age-related changes in local white matter structure in temporoparietal regions, the precuneus and medial prefrontal cortex, and with increased dorsal white matter connectivity between temporoparietal and inferior frontal regions. These effects are independent of co-developing cognitive abilities. Our findings show that the emergence of mental state representation is related to the maturation of core belief processing regions and their connection to the prefrontal cortex. At age 4, children start understanding other peoples' false beliefs, but the related neuroanatomical changes are unknown. Here, authors show that false belief understanding is associated with age-related changes in white matter structure, and that this effect is independent of other cognitive abilities.

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. •Syntax and semantics interact in the left superior temporal cortex until age 7.•Semantic-independent syntax activity is established at age 9 to 10.•The left inferior frontal gyrus is the primary syntax processor at age 9 to 10.

This study examined whether variations in brain development between kindergarten and Grade 3 predicted individual differences in reading ability at Grade 3. Structural MRI measurements indicated that increases in the volume of two left temporo-parietal white matter clusters are unique predictors of reading outcomes above and beyond family history, socioeconomic status, and cognitive and preliteracy measures at baseline. Using diffusion MRI, we identified the left arcuate fasciculus and superior corona radiata as key fibers within the two clusters. Bias-free regression analyses using regions of interest from prior literature revealed that volume changes in temporo-parietal white matter, together with preliteracy measures, predicted 56% of the variance in reading outcomes. Our findings demonstrate the important contribution of developmental differences in areas of left dorsal white matter, often implicated in phonological processing, as a sensitive early biomarker for later reading abilities, and by extension, reading difficulties.

•Newborn baboons present a leftward Planum Temporale Asymmetry.•The proportion is similar to human newborns and adults.•As in human infants, the asymmetry strength increases across development.•These findings question early Planum Temporale Asymmetry as a human-specific marker for the prewired language-ready brain. The “language-ready” brain theory suggests that the infant brain is pre-wired for language acquisition prior to language exposure. As a potential brain marker of such a language readiness, a leftward structural brain asymmetry was found in human infants for the Planum Temporale (PT), which overlaps with Wernicke's area. In the present longitudinal in vivo MRI study conducted in 35 newborn monkeys (Papio anubis), we found a similar leftward PT surface asymmetry. Follow-up rescanning sessions on 29 juvenile baboons at 7-10 months showed that such an asymmetry increases across the two ages classes. These original findings in non-linguistic primate infants strongly question the idea that the early PT asymmetry constitutes a human infant-specific marker for language development. Such a shared early perisylvian organization provides additional support that PT asymmetry might be related to a lateralized system inherited from our last common ancestor with Old-World monkeys at least 25–35 million years ago.

Longitudinal imaging and quantitative genetic studies have both provided important insights into the nature of human brain development. In the present study we combine these modalities to obtain dynamic anatomical maps of the genetic contributions to cortical thickness through childhood and adolescence. A total of 1,748 anatomic MRI scans from 792 healthy twins and siblings were studied with up to eight time points per subject. Using genetically informative latent growth curve modeling of 81,924 measures of cortical thickness, changes in the genetic contributions to cortical development could be visualized across the age range at high resolution. There was highly statistically significant (P < 0.0001) genetic variance throughout the majority of the cerebral cortex, with the regions of highest heritability including the most evolutionarily novel regions of the brain. Dynamic modeling of changes in heritability over time demonstrated that the heritability of cortical thickness increases gradually throughout late childhood and adolescence, with sequential emergence of three large regions of high heritability in the temporal poles, the inferior parietal lobes, and the superior and dorsolateral frontal cortices.

Maturation of attentional processes is central to cognitive development. The electrophysiological P300 is associated with rapid allocation of attention, and bridges stimulus and response processing. P300 is among the most studied and robust electrophysiological components, but how different subcomponents of the P300 develop from childhood to adulthood and relate to structural properties of the cerebral cortex is not well understood. We investigated age-related differences in both early visual and P300 components, and how individual differences in these components are related to cortical structure in a cross-sectional sample of participants 8–19 years (n = 86). Participants completed a three-stimulus visual oddball task while high-density EEG was recorded. Cortical surface area and thickness were estimated from T1-weighted MRI. Group-level blind source separation of the EEG data identified two P300-like components, a fronto-central P300 and a parietal P300, as well as a component reflecting N1 and P2. Differences in activity across age were found for the parietal P300, N1 and P2, with the parietal P300 showing stronger activity for older participants, while N1 and P2 were stronger for younger participants. Stronger P300 components were positively associated with task performance, independently of age, while negative associations were found for P2 strength. Parietal P300 strength was age-independently associated with larger surface area in a region in left lateral inferior temporal cortex. We suggest that the age differences in component strength reflect development of attentional mechanisms, with increased brain responses to task-relevant stimuli representing an increasing ability to focus on relevant information and to respond accurately and efficiently.