Longitudinal Study of the Emerging Functional Connectivity Asymmetry of Primary Language Regions during Infancy

Longitudinal associations between language network characteristics in the infant brain and school-age reading abilities are mediated by early-developing phonological skills

Reading acquisition is a prolonged learning process relying on language development starting in utero. Behavioral longitudinal studies reveal prospective associations between infant language abilities and preschool/kindergarten phonological development that relates to subsequent reading performance. While recent pediatric neuroimaging work has begun to characterize the neural network underlying language development in infants, how this neural network scaffolds long-term language and reading acquisition remains unknown. We addressed this question in a 7-year longitudinal study from infancy to school-age. Seventy-six infants completed resting-state fMRI scanning, and underwent standardized language assessments in kindergarten. Of this larger cohort, forty-one were further assessed on their emergent word reading abilities after receiving formal reading instructions. Hierarchical clustering analyses identified a modular infant language network in which functional connectivity (FC) of the inferior frontal module prospectively correlated with kindergarten-age phonological skills and emergent word reading abilities. These correlations were obtained when controlling for infant age at scan, nonverbal IQ and parental education. Furthermore, kindergarten-age phonological skills mediated the relationship between infant FC and school-age reading abilities, implying a critical mid-way milestone for long-term reading development from infancy. Overall, our findings illuminate the neurobiological mechanisms by which infant language capacities could scaffold long-term reading acquisition.

Longitudinal associations between language network characteristics in the infant brain and school-age reading abilities are mediated by early-developing phonological skills

Reading acquisition is a prolonged learning process relying on language development starting in utero. Behavioral longitudinal studies reveal prospective associations between infant language abilities and preschool/kindergarten phonological development that relates to subsequent reading performance. While recent pediatric neuroimaging work has begun to characterize the neural network underlying language development in infants, how this neural network scaffolds long-term language and reading acquisition remains unknown. We addressed this question in a 7-year longitudinal study from infancy to school-age. Seventy-six infants completed resting-state fMRI scanning, and underwent standardized language assessments in kindergarten. Of this larger cohort, forty-one were further assessed on their emergent word reading abilities after receiving formal reading instructions. Hierarchical clustering analyses identified a modular infant language network in which functional connectivity (FC) of the inferior frontal module prospectively correlated with kindergarten-age phonological skills and emergent word reading abilities. These correlations were obtained when controlling for infant age at scan, nonverbal IQ and parental education. Furthermore, kindergarten-age phonological skills mediated the relationship between infant FC and school-age reading abilities, implying a critical mid-way milestone for long-term reading development from infancy. Overall, our findings illuminate the neurobiological mechanisms by which infant language capacities could scaffold long-term reading acquisition.

Brain age prediction and deviations from normative trajectories in the neonatal connectome

Structural and functional connectomes undergo rapid changes during the third trimester and the first month of postnatal life. Despite progress, our understanding of the developmental trajectories of the connectome in the perinatal period remains incomplete. Brain age prediction uses machine learning to estimate the brain's maturity relative to normative data. The difference between the individual's predicted and chronological age-or brain age gap (BAG)-represents the deviation from these normative trajectories. Here, we assess brain age prediction and BAGs using structural and functional connectomes for infants in the first month of life. We used resting-state fMRI and DTI data from 611 infants (174 preterm; 437 term) from the Developing Human Connectome Project (dHCP) and connectome-based predictive modeling to predict postmenstrual age (PMA). Structural and functional connectomes accurately predicted PMA for term and preterm infants. Predicted ages from each modality were correlated. At the network level, nearly all canonical brain networks-even putatively later developing ones-generated accurate PMA prediction. Additionally, BAGs were associated with perinatal exposures and toddler behavioral outcomes. Overall, our results underscore the importance of normative modeling and deviations from these models during the perinatal period.

Resting-State Functional MRI and PET Imaging as Noninvasive Tools to Study (Ab)Normal Neurodevelopment in Humans and Rodents

Neurodevelopmental disorders (NDDs) are a group of complex neurologic and psychiatric disorders. Functional and molecular imaging techniques, such as resting-state functional magnetic resonance imaging (rs-fMRI) and positron emission tomography (PET), can be used to measure network activity noninvasively and longitudinally during maturation in both humans and rodent models. Here, we review the current knowledge on rs-fMRI and PET biomarkers in the study of normal and abnormal neurodevelopment, including intellectual disability (ID; with/without epilepsy), autism spectrum disorder (ASD), and attention deficit hyperactivity disorder (ADHD), in humans and rodent models from birth until adulthood, and evaluate the cross-species translational value of the imaging biomarkers. To date, only a few isolated studies have used rs-fMRI or PET to study (abnormal) neurodevelopment in rodents during infancy, the critical period of neurodevelopment. Further work to explore the feasibility of performing functional imaging studies in infant rodent models is essential, as rs-fMRI and PET imaging in transgenic rodent models of NDDs are powerful techniques for studying disease pathogenesis, developing noninvasive preclinical imaging biomarkers of neurodevelopmental dysfunction, and evaluating treatment-response in disease-specific models.

Mapping the evolution of regional brain network efficiency and its association with cognitive abilities during the first twenty-eight months of life

Human brain undergoes rapid growth during the first few years of life. While previous research has employed graph theory to study early brain development, it has mostly focused on the topological attributes of the whole brain. However, examining regional graph-theory features may provide unique insights into the development of cognitive abilities. Utilizing a large and longitudinal rsfMRI dataset from the UNC/UMN Baby Connectome Project, we investigated the developmental trajectories of regional efficiency and evaluated the relationships between these changes and cognitive abilities using Mullen Scales of Early Learning during the first twenty-eight months of life. Our results revealed a complex and spatiotemporally heterogeneous development pattern of regional global and local efficiency during this age period. Furthermore, we found that the trajectories of the regional global efficiency at the left temporal occipital fusiform and bilateral occipital fusiform gyri were positively associated with cognitive abilities, including visual reception, expressive language, receptive language, and early learning composite scores (P < 0.05, FDR corrected). However, these associations were weakened with age. These findings offered new insights into the regional developmental features of brain topologies and their associations with cognition and provided evidence of ongoing optimization of brain networks at both whole-brain and regional levels.

Longitudinal developmental trajectories of functional connectivity reveal regional distribution of distinct age effects in infancy

Prior work has shown that different functional brain networks exhibit different maturation rates, but little is known about whether and how different brain areas may differ in the exact shape of longitudinal functional connectivity growth trajectories during infancy. We used resting-state functional magnetic resonance imaging (fMRI) during natural sleep to characterize developmental trajectories of different regions using a longitudinal cohort of infants at 3 weeks (neonate), 1 year, and 2 years of age (n = 90; all with usable data at three time points). A novel whole brain heatmap analysis was performed with four mixed-effect models to determine the best fit of age-related changes for each functional connection: (i) growth effects: positive-linear-age, (ii) emergent effects: positive-log-age, (iii) pruning effects: negative-quadratic-age, and (iv) transient effects: positive-quadratic-age. Our results revealed that emergent (logarithmic) effects dominated developmental trajectory patterns, but significant pruning and transient effects were also observed, particularly in connections centered on inferior frontal and anterior cingulate areas that support social learning and conflict monitoring. Overall, unique global distribution patterns were observed for each growth model indicating that developmental trajectories for different connections are heterogeneous. All models showed significant effects concentrated in association areas, highlighting the dominance of higher-order social/cognitive development during the first 2 years of life.

Early development of the functional brain network in newborns

During the prenatal period and the first postnatal years, the human brain undergoes rapid growth, which establishes a preliminary infrastructure for the subsequent development of cognition and behavior. To understand the underlying processes of brain functioning and identify potential sources of developmental disorders, it is essential to uncover the developmental rules that govern this critical period. In this study, graph theory modeling and network science analysis were employed to investigate the impact of age, gender, weight, and typical and atypical development on brain development. Local and global topologies of functional connectomes obtained from rs-fMRI data were collected from 421 neonates aged between 31 and 45 postmenstrual weeks who were in natural sleep without any sedation. The results showed that global efficiency, local efficiency, clustering coefficient, and small-worldness increased with age, while modularity and characteristic path length decreased with age. The normalized rich-club coefficient displayed a U-shaped pattern during development. The study also examined the global and local impacts of gender, weight, and group differences between typical and atypical cases. The findings presented some new insights into the maturation of functional brain networks and their relationship with cognitive development and neurodevelopmental disorders.

Functional neural network connectivity at 3 months predicts infant-mother dyadic flexibility during play at 6 months

Early functioning of neural networks likely underlies the flexible switching between internal and external orientation and may be key to the infant's ability to effectively engage in social interactions. To test this hypothesis, we examined the association between infants' neural networks at 3 months and infant-mother dyadic flexibility (denoting the structural variability of their interaction dynamics) at 3, 6, and 9 months. Participants included thirty-five infants (37% girls) and their mothers (87% White). At 3 months, infants participated in a resting-state functional magnetic resonance imaging session, and functional connectivity (FC) within the default mode (DMN) and salience (SN) networks, as well as DMN-SN internetwork FC, were derived using a seed-based approach. When infants were 3, 6, and 9 months, infant-mother dyads completed the Still-Face Paradigm where their individual engagement behaviors were observed and used to quantify dyadic flexibility using state space analysis. Results revealed that greater within-DMN FC, within-SN FC, and DMN-SN anticorrelation at 3 months predicted greater dyadic flexibility at 6 months, but not at 3 and 9 months. Findings suggest that early synchronization and interaction between neural networks underlying introspection and salience detection may support infants' flexible social interactions as they become increasingly active and engaged social partners.

Language Experience during Infancy Predicts White Matter Myelination at Age 2 Years

Parental input is considered a key predictor of language achievement during the first years of life, yet relatively few studies have assessed the effects of parental language input and parent-infant interactions on early brain development. We examined the relationship between measures of parent and child language, obtained from naturalistic home recordings at child ages 6, 10, 14, 18, and 24 months, and estimates of white matter myelination, derived from quantitative MRI at age 2 years (mean = 26.30 months, SD = 1.62, N = 22). Analysis of the white matter focused on dorsal pathways associated with expressive language development and long-term language ability, namely, the left arcuate fasciculus (AF) and superior longitudinal fasciculus (SLF). Frequency of parent-infant conversational turns (CT) uniquely predicted myelin density estimates in both the AF and SLF. Moreover, the effect of CT remained significant while controlling for total adult speech and child speech-related utterances, suggesting a specific role for interactive language experience, rather than simply speech exposure or production. An exploratory analysis of 18 additional tracts, including the right AF and SLF, indicated a high degree of anatomic specificity. Longitudinal analyses of parent and child language variables indicated an effect of CT as early as 6 months of age, as well as an ongoing effect over infancy. Together, these results link parent-infant conversational turns to white matter myelination at age 2 years, and suggest that early, interactive experiences with language uniquely contribute to the development of white matter associated with long-term language ability.SIGNIFICANCE STATEMENT Children's earliest experiences with language are thought to have profound and lasting developmental effects. Recent studies suggest that intervention can increase the quality of parental language input and improve children's learning outcomes. However, important questions remain about the optimal timing of intervention, and the relationship between specific aspects of language experience and brain development. We report that parent-infant turn-taking during home language interactions correlates with myelination of language related white matter pathways through age 2 years. Effects were independent of total speech exposure and infant vocalizations and evident starting at 6 months of age, suggesting that structured language interactions throughout infancy may uniquely support the ongoing development of brain systems critical to long-term language ability.

Connections between spatially distant primary language regions strengthen with age during infancy, as revealed by resting-state fNIRS

Objective.Hearing is an important sensory function that plays a key role in how children learn to speak and develop language skills. Although previous neuroimaging studies have established that much of brain network maturation happens in early childhood, our understanding of the developmental trajectory of language areas is still very limited. We hypothesized that typical development trajectory of language areas in early childhood could be established by analyzing the changes of functional connectivity in normal hearing infants at different ages using functional near-infrared spectroscopy.Approach.Resting-state data were recorded from two bilateral temporal and prefrontal regions associated with language processing by measuring the relative changes of oxy-hemoglobin (HbO) and deoxy-hemoglobin (HbR) concentrations. Connectivity was calculated using magnitude-squared coherence of channel pairs located in (a) inter-hemispheric homologous and (b) intra-hemispheric brain regions to assess connectivity between homologous regions across hemispheres and two regions of interest in the same hemisphere, respectively.Main results.A linear regression model fitted to the age vs coherence of inter-hemispheric homologous test group revealed a significant coefficient of determination for both HbO (R²= 0.216,p= 0.0169) and HbR (R²= 0.206,p= 0.0198). A significant coefficient of determination was also found for intra-hemispheric test group for HbO (R²= 0.237,p= 0.0117) but not for HbR (R²= 0.111,p= 0.0956).Significance.The findings from HbO data suggest that both inter-hemispheric homologous and intra-hemispheric connectivity between primary language regions significantly strengthen with age in the first year of life. Mapping out the developmental trajectory of primary language areas of normal hearing infants as measured by functional connectivity could potentially allow us to better understand the altered connectivity and its effects on language delays in infants with hearing impairments.

Brain myelination at 7 months of age predicts later language development

Between 6 and 12 months of age there are dramatic changes in infants' processing of language. The neurostructural underpinnings of these changes are virtually unknown. The objectives of this study were to (1) examine changes in brain myelination during this developmental period and (2) examine the relationship between myelination during this period and later language development. Macromolecular proton fraction (MPF) was used as a marker of myelination. Whole-brain MPF maps were obtained with 1.25 mm3 isotropic spatial resolution from typically developing children at 7 and 11 months of age. Effective myelin density was calculated from MPF based on a linear relationship known from the literature. Voxel-based analyses were used to identify longitudinal changes in myelin density and to calculate correlations between myelin density at these ages and later language development. Increases in myelin density were more predominant in white matter than in gray matter. A strong predictive relationship was found between myelin density at 7 months of age, language production at 24 and 30 months of age, and rate of language growth. No relationships were found between myelin density at 11 months, or change in myelin density between 7 and 11 months of age, and later language measures. Our findings suggest that critical changes in brain structure may precede periods of pronounced change in early language skills.

Impact of development and recent-onset epilepsy on language dominance

OBJECTIVE

Reorganization of the language network from typically left-lateralized frontotemporal regions to bilaterally distributed or right-lateralized networks occurs in anywhere from 25%-30% of patients with focal epilepsy. In patients who have been recently diagnosed with epilepsy, an important question remains as to whether it is the presence of seizures or the underlying epilepsy etiology that leads to atypical language representations. This question becomes even more interesting in pediatric samples, where the typical developmental processes of the language network may confer more variability and plasticity in the language network. We assessed a carefully selected cohort of children with recent-onset epilepsy to examine whether it is the effects of seizures or their underlying cause that leads to atypical language lateralization.

METHODS

We used functional magnetic resonance imaging (fMRI) to compare language laterality in children with recently diagnosed focal unaware epilepsy and age-matched controls. Age at epilepsy onset (age 4 to 6 years vs age 7 to 12 years) was also examined to determine if age at onset influenced laterality.

RESULTS

The majority of recent-onset patients and controls exhibited left-lateralized language. There was a significant interaction such that the relationship between epilepsy duration and laterality differed by age at onset. In children with onset after age 6, a longer duration of epilepsy was associated with less left-lateralized language dominance. In contrast, in children with onset between 4 and 6 years of age, a longer duration of epilepsy was not associated with less left language dominance.

SIGNIFICANCE

Our results demonstrate that although language remained largely left-lateralized in children recently diagnosed with epilepsy, the impact of seizure duration depended on age at onset, indicating that the timing of developmental and disease factors are important in determining language dominance.

Infant Visual Brain Development and Inherited Genetic Liability in Autism

OBJECTIVE

Autism spectrum disorder (ASD) is heritable, and younger siblings of ASD probands are at higher likelihood of developing ASD themselves. Prospective MRI studies of siblings report that atypical brain development precedes ASD diagnosis, although the link between brain maturation and genetic factors is unclear. Given that familial recurrence of ASD is predicted by higher levels of ASD traits in the proband, the authors investigated associations between proband ASD traits and brain development among younger siblings.

METHODS

In a sample of 384 proband-sibling pairs (89 pairs concordant for ASD), the authors examined associations between proband ASD traits and sibling brain development at 6, 12, and 24 months in key MRI phenotypes: total cerebral volume, cortical surface area, extra-axial cerebrospinal fluid, occipital cortical surface area, and splenium white matter microstructure. Results from primary analyses led the authors to implement a data-driven approach using functional connectivity MRI at 6 months.

RESULTS

Greater levels of proband ASD traits were associated with larger total cerebral volume and surface area and larger surface area and reduced white matter integrity in components of the visual system in siblings who developed ASD. This aligned with weaker functional connectivity between several networks and the visual system among all siblings during infancy.

CONCLUSIONS

The findings provide evidence that specific early brain MRI phenotypes of ASD reflect quantitative variation in familial ASD traits. Multimodal anatomical and functional convergence on cortical regions, fiber pathways, and functional networks involved in visual processing suggest that inherited liability has a role in shaping the prodromal development of visual circuitry in ASD.

Functional connectivity for the language network in the developing brain: 30 weeks of gestation to 30 months of age

Although the neural scaffolding for language is putatively present before birth, the maturation of functional connections among the key nodes of the language network, Broca's and Wernicke's areas, is less known. We leveraged longitudinal and cross-sectional data from three sites collected through six studies to track the development of functional circuits between Broca's and Wernicke's areas from 30 weeks of gestation through 30 months of age in 127 unique participants. Using resting-state fMRI data, functional connectivity was calculated as the correlation between fMRI time courses from pairs of regions, defined as Broca's and Wernicke's in both hemispheres. The primary analysis evaluated 23 individuals longitudinally imaged from 30 weeks postmenstrual age (fetal) through the first postnatal month (neonatal). A secondary analysis in 127 individuals extended these curves into older infants and toddlers. These data demonstrated significant growth of interhemispheric connections including left Broca's and its homolog and left Wernicke's and its homolog from 30 weeks of gestation through the first postnatal month. In contrast, intrahemispheric connections did not show significant increases across this period. These data represent an important baseline for language systems in the developing brain against which to compare those neurobehavioral disorders with the potential fetal onset of disease.

Towards a model of language neurobiology in early development

Understanding language neurobiology in early childhood is essential for characterizing the developmental structural and functional changes that lead to the mature adult language network. In the last two decades, the field of language neurodevelopment has received increasing attention, particularly given the rapid advances in the implementation of neuroimaging techniques and analytic approaches that allow detailed investigations into the developing brain across a variety of cognitive domains. These methodological and analytical advances hold the promise of developing early markers of language outcomes that allow diagnosis and clinical interventions at the earliest stages of development. Here, we argue that findings in language neurobiology need to be integrated within an approach that captures the dynamic nature and inherent variability that characterizes the developing brain and the interplay between behavior and (structural and functional) neural patterns. Accordingly, we describe a framework for understanding language neurobiology in early development, which minimally requires an explicit characterization of the following core domains: i) computations underlying language learning mechanisms, ii) developmental patterns of change across neural and behavioral measures, iii) environmental variables that reinforce language learning (e.g., the social context), and iv) brain maturational constraints for optimal neural plasticity, which determine the infant's sensitivity to learning from the environment. We discuss each of these domains in the context of recent behavioral and neuroimaging findings and consider the need for quantitatively modeling two main sources of variation: individual differences or trait-like patterns of variation and within-subject differences or state-like patterns of variation. The goal is to enable models that allow prediction of language outcomes from neural measures that take into account these two types of variation. Finally, we examine how future methodological approaches would benefit from the inclusion of more ecologically valid paradigms that complement and allow generalization of traditional controlled laboratory methods.

Infant social interactions and brain development: A systematic review

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Associations between caregiver-infant behaviours during social interactions and brain development outcomes were investigated.

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Caregivers' and infants' behaviours in interactions related to children’s structural, functional and connectivity measures.

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Concurrent associations between behavioural and brain measures were apparent as early as three months postnatally.

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Long-term associations between behaviours in early interactions and brain development outcomes were observed decades later.

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Individual differences in early interactions and associated brain development is an important avenue for further research.

From birth, interactions with others are an integral part of a person’s daily life. In infancy, social exchanges are thought to be critical for optimal brain development. This systematic review explores this association by drawing together infant studies that relate adult-infant behaviours – coded from their social interactions - to children’s brain measures collected during a neuroimaging session in infancy, childhood, adolescence or adulthood. In total, we identified 55 studies that explored associations between infants’ social interactions and neural measures. These studies show that several aspects of caregiver-infant behaviours are associated with, or predict, a variety of neural responses in infants, children and adolescents. The presence of both concurrent and long-term associations - some of which are first observed just a few months postnatally and extend into adulthood - open an important research avenue and motivate further longitudinal studies.

Functional Connectivity in Infancy and Toddlerhood Predicts Long-Term Language and Preliteracy Outcomes

Functional connectivity (FC) techniques can delineate brain organization as early as infancy, enabling the characterization of early brain characteristics associated with subsequent behavioral outcomes. Previous studies have identified specific functional networks in infant brains that underlie cognitive abilities and pathophysiology subsequently observed in toddlers and preschoolers. However, it is unknown whether and how functional networks emerging within the first 18 months of life contribute to the development of higher order, complex functions of language/literacy at school-age. This 5-year longitudinal imaging project starting in infancy, utilized resting-state functional magnetic resonance imaging and demonstrated prospective associations between FC in infants/toddlers and subsequent language and foundational literacy skills at 6.5 years old. These longitudinal associations were shown independently of key environmental influences and further present in a subsample of infant imaging data (≤12 months), suggesting early emerged functional networks specifically linked to high-order language and preliteracy skills. Moreover, emergent language skills in infancy and toddlerhood contributed to the prospective associations, implicating a role of early linguistic experiences in shaping the FC correlates of long-term oral language skills. The current results highlight the importance of functional organization established in infancy and toddlerhood as a neural scaffold underlying the learning process of complex cognitive functions.

The prenatal brain readiness for speech processing: A review on foetal development of auditory and primordial language networks

Despite consolidated evidence for the prenatal ability to elaborate and respond to sounds and speech stimuli, the ontogenetic functional brain maturation of language responsiveness in the foetus is still poorly understood. Recent advances in in-vivo foetal neuroimaging have contributed to a finely detailed picture of the anatomo-functional hallmarks that define the prenatal neurodevelopment of auditory and language-related networks. Here, we first outline available evidence for the prenatal development of auditory and language-related brain structures and of their anatomical connections. Second, we focus on functional connectivity data showing the emergence of auditory and primordial language networks in the foetal brain. Third, we recapitulate functional neuroimaging studies assessing the prenatal readiness for sound processing, as a crucial prerequisite for the foetus to experientially respond to spoken language. In conclusion, we suggest that the state of the art has reached sufficient maturity to directly assess the neural mechanisms underlying the prenatal readiness for speech processing and to evaluate whether foetal neuromarkers can predict the postnatal development of language acquisition abilities and disabilities.

Hippocampal functional connectivity development during the first two years indexes 4-year working memory performance

The hippocampus is a key limbic region involved in higher-order cognitive processes including learning and memory. Although both typical and atypical functional connectivity patterns of the hippocampus have been well-studied in adults, the developmental trajectory of hippocampal connectivity during infancy and how it relates to later working memory performance remains to be elucidated. Here we used resting state fMRI (rsfMRI) during natural sleep to examine the longitudinal development of hippocampal functional connectivity using a large cohort (N = 202) of infants at 3 weeks (neonate), 1 year, and 2 years of age. Next, we used multivariate modeling to investigate the relationship between both cross-sectional and longitudinal growth in hippocampal connectivity and 4-year working memory outcome. Results showed robust local functional connectivity of the hippocampus in neonates with nearby limbic and subcortical regions, with dramatic maturation and increasing connectivity with key default mode network (DMN) regions resulting in adult-like topology of the hippocampal functional connectivity by the end of the first year. This pattern was stabilized and further consolidated by 2 years of age. Importantly, cross-sectional and longitudinal measures of hippocampal connectivity in the first year predicted subsequent behavioral measures of working memory at 4 years of age. Taken together, our findings provide insight into the development of hippocampal functional circuits underlying working memory during this early critical period.

Naturalistic Language Input is Associated with Resting-State Functional Connectivity in Infancy

The quantity and quality of the language input that infants receive from their caregivers affects their future language abilities; however, it is unclear how variation in this input relates to preverbal brain circuitry. The current study investigated the relation between naturalistic language input and the functional connectivity (FC) of language networks in human infancy using resting-state functional magnetic resonance imaging (rsfMRI). We recorded the naturalistic language environments of five- to eight-month-old male and female infants using the Linguistic ENvironment Analysis (LENA) system and measured the quantity and consistency of their exposure to adult words (AWs) and adult-infant conversational turns (CTs). Infants completed an rsfMRI scan during natural sleep, and we examined FC among regions of interest (ROIs) previously implicated in language comprehension, including the auditory cortex, the left inferior frontal gyrus (IFG), and the bilateral superior temporal gyrus (STG). Consistent with theory of the ontogeny of the cortical language network (Skeide and Friederici, 2016), we identified two subnetworks posited to have distinct developmental trajectories: a posterior temporal network involving connections of the auditory cortex and bilateral STG and a frontotemporal network involving connections of the left IFG. Independent of socioeconomic status (SES), the quantity of CTs was uniquely associated with FC of these networks. Infants who engaged in a larger number of CTs in daily life had lower connectivity in the posterior temporal language network. These results provide evidence for the role of vocal interactions with caregivers, compared with overheard adult speech, in the function of language networks in infancy.

Lack of neural evidence for implicit language learning in 9-month-old infants at high risk for autism

Word segmentation is a fundamental aspect of language learning, since identification of word boundaries in continuous speech must occur before the acquisition of word meanings can take place. We previously used functional magnetic resonance imaging (fMRI) to show that youth with autism spectrum disorder (ASD) are less sensitive to statistical and speech cues that guide implicit word segmentation. However, little is known about the neural mechanisms underlying this process during infancy and how this may be associated with ASD risk. Here, we examined early neural signatures of language-related learning in 9-month-old infants at high (HR) and low familial risk (LR) for ASD. During natural sleep, infants underwent fMRI while passively listening to three speech streams containing strong statistical and prosodic cues, strong statistical cues only, or minimal statistical cues to word boundaries. Compared to HR infants, LR infants showed greater activity in the left amygdala for the speech stream containing statistical and prosodic cues. While listening to this same speech stream, LR infants also showed more learning-related signal increases in left temporal regions as well as increasing functional connectivity between bilateral primary auditory cortex and right anterior insula. Importantly, learning-related signal increases at 9 months positively correlated with expressive language outcome at 36 months in both groups. In the HR group, greater signal increases were additionally associated with less severe ASD symptomatology at 36 months. These findings suggest that early differences in the neural networks underlying language learning may predict subsequent language development and altered trajectories associated with ASD risk.

Relationships between intrinsic functional connectivity, cognitive control, and reading achievement across development

There are vast individual differences in reading achievement between students. Besides structural and functional variability in domain-specific brain regions, these differences may partially be explained by the organization of domain-general functional brain networks. In the current study we used resting-state functional MRI data from the Philadelphia Neurodevelopmental Cohort (PNC; N = 553; ages 8-22) to examine the relation between performance on a well-validated reading assessment task, the Wide Range Achievement Word Reading Test (WRAT-Reading) and patterns of functional connectivity. We focused specifically on functional connectivity within and between networks associated with cognitive control, and investigated whether the relationship with academic test performance was mediated by cognitive control abilities. We show that individuals with higher scores on the WRAT-Reading, have stronger lateralization in frontoparietal networks, increased functional connectivity between dorsal striatum and the dorsal attention network, and reduced functional connectivity between dorsal and ventral striatum. The relationship between functional connectivity and reading performance was mediated by cognitive control abilities (i.e., performance on a composite measure of executive function and complex cognition), but not by abilities in other domains, demonstrating the specificity of our findings. Finally, there were no significant interactions with age, suggesting that the observed brain-behavior relationships stay relatively stable over the course of development. Our findings provide important insights into the functional significance of inter-individual variability in the network architecture of the developing brain, showing that functional connectivity in domain-general control networks is relevant to academic achievement in the reading domain.

Functional Integration Between the Two Brain Hemispheres: Evidence From the Homotopic Functional Connectivity Under Resting State

Functional integration among neural units is one of the fundamental principles in brain organization that could be examined using resting-state functional connectivity (rs-FC). Interhemispheric functional integration plays a critical role in human cognition. Homotopic functional connectivity (HoFC) under resting state provide an avenue to investigate functional integration between the two brain hemispheres, which can improve the present understanding of how interhemispheric interactions affect cognitive processing. In this review, we summarize the progress of HoFC studies under resting state and highlight how these findings have enhanced our understanding of interhemispheric functional organization of the human brain. Future studies are encouraged to address particular methodological issues and to further ascertain behavioral correlates, brain disease’s modulation, task influence, and genetic basis of HoFC.

The emergence of a functionally flexible brain during early infancy

While adult brains are known to be functionally flexible, the emergence of a functionally flexible brain during early infancy is largely uncharted due the lack of approaches to assess neural flexibility in infants. Using recent advances of multilayer network approaches and a cohort of typically developing children who underwent longitudinal MRI during the first 2 y of life, we investigated the developmental characteristics of brain neural flexibility. The temporal and spatial emergence of a functionally flexible brain was revealed. Brain regions with high neural flexibility appear consistent with the core regions supporting cognitive flexibility processing in adults, whereas brain regions governing basic brain functions exhibit lower neural flexibility, demonstrating the emergence of functionally flexible brain during early infancy.

Adult brains are functionally flexible, a unique characteristic that is thought to contribute to cognitive flexibility. While tools to assess cognitive flexibility during early infancy are lacking, we aimed to assess the spatiotemporal developmental features of “neural flexibility” during the first 2 y of life. Fifty-two typically developing children 0 to 2 y old were longitudinally imaged up to seven times during natural sleep using resting-state functional MRI. Using a sliding window approach, MR-derived neural flexibility, a quantitative measure of the frequency at which brain regions change their allegiance from one functional module to another during a given time period, was used to evaluate the temporal emergence of neural flexibility during early infancy. Results showed that neural flexibility of whole brain, motor, and high-order brain functional networks/regions increased significantly with age, while visual regions exhibited a temporally stable pattern, suggesting spatially and temporally nonuniform developmental features of neural flexibility. Additionally, the neural flexibility of the primary visual network at 3 mo of age was significantly and negatively associated with cognitive ability evaluated at 5/6 y of age. The “flexible club,” comprising brain regions with neural flexibility significantly higher than whole-brain neural flexibility, were consistent with brain regions known to govern cognitive flexibility in adults and exhibited unique characteristics when compared to the functional hub and diverse club regions. Thus, MR-derived neural flexibility has the potential to reveal the underlying neural substrates for developing a cognitively flexible brain during early infancy.

Neonatal Brain Microstructure and Machine-Learning-Based Prediction of Early Language Development in Children Born Very Preterm

BACKGROUND

Very-low-birth-weight preterm infants have a higher rate of language impairments compared with children born full term. Early identification of preterm infants at risk for language delay is essential to guide early intervention at the time of optimal neuroplasticity. This study examined near-term structural brain magnetic resonance imaging (MRI) and white matter microstructure assessed on diffusion tensor imaging (DTI) in relation to early language development in children born very preterm.

METHODS

A total of 102 very-low-birth-weight neonates (birthweight≤1500g, gestational age ≤32-weeks) were recruited to participate from 2010 to 2011. Near-term structural MRI was evaluated for white matter and cerebellar abnormalities. DTI fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity were assessed. Language development was assessed with Bayley Scales of Infant-Toddler Development-III at 18 to 22 months adjusted age. Multivariate models with leave-one-out cross-validation and exhaustive feature selection identified three brain regions most predictive of language function. Distinct logistic regression models predicted high-risk infants, defined by language scores >1 S.D. below average.

RESULTS

Of 102 children, 92 returned for neurodevelopmental testing. Composite language score mean ± S.D. was 89.0 ± 16.0; 31 of 92 children scored <85, including 15 of 92 scoring <70, suggesting moderate-to-severe delay. Children with cerebellar asymmetry had lower receptive language subscores (P = 0.016). Infants at high risk for language impairments were predicted based on regional white matter microstructure on DTI with high accuracy (sensitivity, specificity) for composite (89%, 86%), expressive (100%, 90%), and receptive language (100%, 90%).

CONCLUSIONS

Multivariate models of near-term structural MRI and white matter microstructure on DTI may assist in identification of preterm infants at risk for language impairment, guiding early intervention.

Emerging atypicalities in functional connectivity of language-related networks in young infants at high familial risk for ASD

Prior studies have demonstrated that infants and toddlers who later go on to develop autism spectrum disorder (ASD) show atypical functional connectivity as well as altered neural processing of language and other auditory stimuli, but the timeline underlying the emergence of these altered developmental trajectories is still unclear. Here we used resting-state fMRI (rsfMRI) during natural sleep to examine the longitudinal development of functional connectivity in language-related networks from 1.5 to 9 months of age. We found that functional connectivity of networks that underlie the integration of sensory and motor representations, which is crucial for language development, is disrupted in infants at high familial risk (HR) for developing ASD as early as 1.5 months of age. By 9 months of age, HR infants showed hyperconnectivity between auditory and somatosensory regions whereas low risk (LR) infants displayed greater intrahemispheric connectivity between auditory cortex and higher-order temporal regions as well as the hippocampus. Furthermore, while LR infants showed robust changes in functional connectivity during the first year of life with increasing long-range connectivity accompanied by decreasing short-range connectivity over time, HR infants displayed limited developmental changes. Our findings demonstrate that early disruptions in the development of language-related network connectivity may provide an early marker for the later emergence of ASD symptomatology.

Functional brain connectivity changes across the human life span: From fetal development to old age

The dynamic of the temporal correlations between brain areas, called functional connectivity (FC), undergoes complex transformations through the life span. In this review, we aim to provide an overview of these changes in the nonpathological brain from fetal life to advanced age. After a brief description of the main methods, we propose that FC development can be divided into four main phases: first, before birth, a strong change in FC leads to the emergence of functional proto-networks, involving mainly within network short-range connections. Then, during the first years of life, there is a strong widespread organization of networks which starts with segregation processes followed by a continuous increase in integration. Thereafter, from adolescence to early adulthood, a refinement of existing networks in the brain occurs, characterized by an increase in integrative processes until about 40 years. Middle age constitutes a pivotal period associated with an inversion of the functional brain trajectories with a decrease in segregation process in conjunction to a large-scale reorganization of between network connections. Studies suggest that these processes are in line with the development of cognitive and sensory functions throughout life as well as their deterioration. During aging, results support the notion of dedifferentiation processes, which refer to the decrease in functional selectivity of the brain regions, resulting in more diffuse and less specialized FC, associated with the disruption of cognitive functions with age. The inversion of developmental processes during aging is in accordance with the developmental models of neuroanatomy for which the latest matured regions are the first to deteriorate.

Resting-state networks of the neonate brain identified using independent component analysis

Resting-state functional magnetic resonance imaging (rs-fMRI) has been successfully used to probe the intrinsic functional organization of the brain and to study brain development. Here, we implemented a combination of individual and group independent component analysis (ICA) of FSL on a 6-min resting-state data set acquired from 21 naturally sleeping term-born (age 26 ± 6.7 d), healthy neonates to investigate the emerging functional resting-state networks (RSNs). In line with the previous literature, we found evidence of sensorimotor, auditory/language, visual, cerebellar, thalmic, parietal, prefrontal, anterior cingulate as well as dorsal and ventral aspects of the default-mode-network. Additionally, we identified RSNs in frontal, parietal, and temporal regions that have not been previously described in this age group and correspond to the canonical RSNs established in adults. Importantly, we found that careful ICA-based denoising of fMRI data increased the number of networks identified with group-ICA, whereas the degree of spatial smoothing did not change the number of identified networks. Our results show that the infant brain has an established set of RSNs soon after birth.

Cerebral asymmetry during development using linear measures from MRI

Asymmetry of the human brain is a well-known phenomenon, but the nature and extent of these differences throughout postnatal development have not been examined. Accordingly, linear measurements of the brains of 121 infants, children, and adolescents were determined to ascertain cerebral hemispheric asymmetries. Using multiple statistical methods, the results showed that: 1) the frontal lobe is wider on the right, while the occipital lobe is wider on the left; 2) there are no side to side differences in cerebral hemispheric length or height; and 3) there are no major sex differences. Especially notable is the lack of any correlation between side to side differences in length, width, or height and increasing age, which was also the case for cerebral hemispheric area or volume with increasing age. Regarding petalias: 1) the right frontal petalia occurs in 61%, the left occipital in 60%, and both petalias in 36% of the cohort; 2) the right frontal and left occipital petalias are of similar lengths; 3) the distances of both petalias increase with advancing age but not when scaled to either cerebral hemispheric area or volume, indicating that petalias are equally prominent early in postnatal life compared to later development; and 4) there are no major sex differences in the frequency or magnitude of either petalia. These findings provide comprehensive new information regarding age and sex related cerebral hemispheric asymmetries during development.

Altered lateralization of dorsal language tracts in 6-week-old infants at risk for autism

Altered structural connectivity has been identified as a possible biomarker of autism spectrum disorder (ASD) risk in the developing brain. Core features of ASD include impaired social communication and early language delay. Thus, examining white matter tracts associated with language may lend further insight into early signs of ASD risk and the mechanisms that underlie language impairments associated with the disorder. Evidence of altered structural connectivity has previously been detected in 6-month-old infants at high familial risk for developing ASD. However, as language processing begins in utero, differences in structural connectivity between language regions may be present in the early infant brain shortly after birth. Here we investigated key white matter pathways of the dorsal language network in 6-week-old infants at high (HR) and low (LR) risk for ASD to identify atypicalities in structural connectivity that may predict altered developmental trajectories prior to overt language delays and the onset of ASD symptomatology. Compared to HR infants, LR infants showed higher fractional anisotropy (FA) in the left superior longitudinal fasciculus (SLF); in contrast, in the right SLF, HR infants showed higher FA than LR infants. Additionally, HR infants showed more rightward lateralization of the SLF. Across both groups, measures of FA and lateralization of these pathways at 6 weeks of age were related to later language development at 18 months of age as well as ASD symptomatology at 36 months of age. These findings indicate that early differences in the structure of language pathways may provide an early predictor of future language development and ASD risk.

Sex differences in functional connectivity during fetal brain development

Sex-related differences in brain and behavior are apparent across the life course, but the exact set of processes that guide their emergence in utero remains a topic of vigorous scientific inquiry. Here, we evaluate sex and gestational age (GA)-related change in functional connectivity (FC) within and between brain wide networks. Using resting-state functional magnetic resonance imaging we examined FC in 118 human fetuses between 25.9 and 39.6 weeks GA (70 male; 48 female). Infomap was applied to the functional connectome to identify discrete prenatal brain networks in utero. A consensus procedure produced an optimal model comprised of 16 distinct fetal neural networks distributed throughout the cortex and subcortical regions. We used enrichment analysis to assess network-level clustering of strong FC-GA correlations separately in each sex group, and to identify network pairs exhibiting distinct patterns of GA-related change in FC between males and females. We discovered both within and between network FC-GA associations that varied with sex. Specifically, associations between GA and posterior cingulate-temporal pole and fronto-cerebellar FC were observed in females only, whereas the association between GA and increased intracerebellar FC was stronger in males. These observations confirm that sexual dimorphism in functional brain systems emerges during human gestation.

Resting-state functional MRI studies on infant brains: A decade of gap-filling efforts

Resting-state functional MRI (rs-fMRI) is one of the most prevalent brain functional imaging modalities. Previous rs-fMRI studies have mainly focused on adults and elderly subjects. Recently, infant rs-fMRI studies have become an area of active research. After a decade of gap filling studies, many facets of the brain functional development from early infancy to toddler has been uncovered. However, infant rs-fMRI is still in its infancy. The image analysis tools for neonates and young infants can be quite different from those for adults. From data analysis to result interpretation, more questions and issues have been raised, and new hypotheses have been formed. With the anticipated availability of unprecedented high-resolution rs-fMRI and dedicated analysis pipelines from the Baby Connectome Project (BCP), it is important now to revisit previous findings and hypotheses, discuss and comment existing issues and problems, and make a "to-do-list" for the future studies. This review article aims to comprehensively review a decade of the findings, unveiling hidden jewels of the fields of developmental neuroscience and neuroimage computing. Emphases will be given to early infancy, particularly the first few years of life. In this review, an end-to-end summary, from infant rs-fMRI experimental design to data processing, and from the development of individual functional systems to large-scale brain functional networks, is provided. A comprehensive summary of the rs-fMRI findings in developmental patterns is highlighted. Furthermore, an extensive summary of the neurodevelopmental disorders and the effects of other hazardous factors is provided. Finally, future research trends focusing on emerging dynamic functional connectivity and state-of-the-art functional connectome analysis are summarized. In next decade, early infant rs-fMRI and developmental connectome study could be one of the shining research topics.

Challenges in pediatric neuroimaging

Pediatric neuroimaging is challenging due the rapid structural, metabolic, and functional changes that occur in the developing brain. A specially trained team is needed to produce high quality diagnostic images in children, due to their small physical size and immaturity. Patient motion, cooperation and medical condition dictate the methods and equipment used. A customized approach tailored to each child's age and functional status with the appropriate combination of dedicated staff, imaging hardware, and software is key; these range from low-tech techniques, such as feed and swaddle, to specialized small bore MRI scanners, MRI compatible incubators and neonatal head coils. New pre-and post-processing techniques can also compensate for the motion artifacts and low signal that often degrade neonatal scans.

Brain functional development separates into three distinct time periods in the first two years of life

Recently, resting functional MRI has provided invaluable insight into the brain developmental processes of early infancy and childhood. A common feature of previous functional development studies is the use of age to separate subjects into different cohorts for group comparisons. However, functional maturation paces vary tremendously from subject to subject. Since this is particularly true for the first years of life, an alternative to physical age alone is needed for cluster analysis. Here, a data-driven approach based on individual brain functional connectivity was employed to cluster typically developing children who were longitudinally imaged using MRI without sedation for the first two years of life. Specifically, three time periods were determined based on the distinction of brain functional connectivity patterns, including 0-1 month (group 1), 2-7 months (group 2), and 8-24 (group 3) of age, respectively. From groups 1 to 2, connection density increased by almost two-fold, local efficacy (LE) is significantly improved, and there was no change in global efficiency (GE). From groups 2 to 3, connection density increased slightly, LE showed no change, and a significant increase in GE were observed. Furthermore, 27 core brain regions were identified which yielded clustering results that resemble those obtained using all brain regions. These core regions were largely associated with the motor, visual and language functional domains as well as regions associated with higher order cognitive functional domains. Both visual and language functional domains exhibited a persistent and significant increase within domain connection from groups 1 to 3, while no changes were observed for the motor domain. In contrast, while a reduction of inter-domain connection was the general developmental pattern, the motor domain exhibited an interesting "V" shape pattern in its relationship to visual and language associated areas, showing a decrease from groups 1 to 2, followed by an increase from groups 2 to 3. In summary, our results offer new insights into functional brain development and identify 27 core brain regions critically important for early brain development.

Neural histology and neurogenesis of the human fetal and infant brain

The human brain develops slowly and over a long period of time which lasts for almost three decades. This enables good spatio-temporal resolution of histogenetic and neurogenetic events as well as an appropriate and clinically relevant timing of these events. In order to successfully apply in vivo neuroimaging data, in analyzing both the normal brain development and the neurodevelopmental origin of major neurological and mental disorders, it is important to correlate these neuroimaging data with the existing data on morphogenetic, histogenetic and neurogenetic events. Furthermore, when performing such correlation, the genetic, genomic, and molecular biology data on phenotypic specification of developing brain regions, areas and neurons should also be included. In this review, we focus on early developmental periods (form 8 postconceptional weeks to the second postnatal year) and describe the microstructural organization and neural circuitry elements of the fetal and early postnatal human cerebrum.

Language lateralization with resting-state and task-based functional MRI in pediatric epilepsy

In Brief: The study compared two types of functional MRI (fMRI) to see which side of the brain is most responsible for language: traditional task-based fMRI, which requires a high level of patient interaction, and resting-state fMRI, which is typically performed with the patient under light sedation and has no interaction requirement. The authors found that the test correlation was 93%, indicating resting state fMRI has potential to locate language in those unable to participate in task-based fMRI.

Prenatal neural origins of infant motor development: Associations between fetal brain and infant motor development

Functional circuits of the human brain emerge and change dramatically over the second half of gestation. It is possible that variation in neural functional system connectivity in utero predicts individual differences in infant behavioral development, but this possibility has yet to be examined. The current study examines the association between fetal sensorimotor brain system functional connectivity and infant postnatal motor ability. Resting-state functional connectivity data was obtained in 96 healthy human fetuses during the second and third trimesters of pregnancy. Infant motor ability was measured 7 months after birth using the Bayley Scales of Infant Development. Increased connectivity between the emerging motor network and regions of the prefrontal cortex, temporal lobes, posterior cingulate, and supplementary motor regions was observed in infants that showed more mature motor functions. In addition, females demonstrated stronger fetal-brain to infant-behavior associations. These observations extend prior longitudinal research back into prenatal brain development and raise exciting new ideas about the advent of risk and the ontogeny of early sex differences.

The UNC/UMN Baby Connectome Project (BCP): An overview of the study design and protocol development

The human brain undergoes extensive and dynamic growth during the first years of life. The UNC/UMN Baby Connectome Project (BCP), one of the Lifespan Connectome Projects funded by NIH, is an ongoing study jointly conducted by investigators at the University of North Carolina at Chapel Hill and the University of Minnesota. The primary objective of the BCP is to characterize brain and behavioral development in typically developing infants across the first 5 years of life. The ultimate goals are to chart emerging patterns of structural and functional connectivity during this period, map brain-behavior associations, and establish a foundation from which to further explore trajectories of health and disease. To accomplish these goals, we are combining state of the art MRI acquisition and analysis techniques, including high-resolution structural MRI (T1-and T2-weighted images), diffusion imaging (dMRI), and resting state functional connectivity MRI (rfMRI). While the overall design of the BCP largely is built on the protocol developed by the Lifespan Human Connectome Project (HCP), given the unique age range of the BCP cohort, additional optimization of imaging parameters and consideration of an age appropriate battery of behavioral assessments were needed. Here we provide the overall study protocol, including approaches for subject recruitment, strategies for imaging typically developing children 0-5 years of age without sedation, imaging protocol and optimization, a description of the battery of behavioral assessments, and QA/QC procedures. Combining HCP inspired neuroimaging data with well-established behavioral assessments during this time period will yield an invaluable resource for the scientific community.

Imaging structural and functional brain development in early childhood

In humans, the period from term birth to ∼2 years of age is characterized by rapid and dynamic brain development and plays an important role in cognitive development and risk of disorders such as autism and schizophrenia. Recent imaging studies have begun to delineate the growth trajectories of brain structure and function in the first years after birth and their relationship to cognition and risk of neuropsychiatric disorders. This Review discusses the development of grey and white matter and structural and functional networks, as well as genetic and environmental influences on early-childhood brain development. We also discuss initial evidence regarding the usefulness of early imaging biomarkers for predicting cognitive outcomes and risk of neuropsychiatric disorders.

Subcortical Brain and Behavior Phenotypes Differentiate Infants With Autism Versus Language Delay

BACKGROUND

Younger siblings of children with autism spectrum disorder (ASD) are themselves at increased risk for ASD and other developmental concerns. It is unclear if infants who display developmental concerns, but are unaffected by ASD, share similar or dissimilar behavioral and brain phenotypes to infants with ASD. Most individuals with ASD exhibit heterogeneous difficulties with language, and their receptive-expressive language profiles are often atypical. Yet, little is known about the neurobiology that contributes to these language difficulties.

METHODS

In this study, we used behavioral assessments and structural magnetic resonance imaging to investigate early brain structures and associations with later language skills. High-risk infants who were later diagnosed with ASD (n = 86) were compared with high-risk infants who showed signs of early language delay (n = 41) as well as with high- and low-risk infants who did not have ASD or language delay (n = 255 and 143, respectively).

RESULTS

Results indicated that diminished language skills were evident at 12 months in infants with ASD and infants with early language delay. At 24 months of age, only the infants with ASD displayed atypical receptive-expressive language profiles. Associations between 12-month subcortical volumes and 24-month language skills were moderated by group status, indicating disordinal brain-behavior associations among infants with ASD and infants with language delay.

CONCLUSIONS

These results suggest that there are different brain mechanisms influencing language development in infants with ASD and infants with language delay, and that the two groups likely experience unique sets of genetic and environmental risk factors.