Functional connectivity in the developing language network in 4-year-old children predicts future reading ability

Structural neural connectivity correlates with pre-reading abilities in preschool children

Pre-reading abilities are predictive of later reading ability and can be assessed before reading begins. However, the neural correlates of pre-reading abilities in young children are not fully understood. To address this, we examined 246 datasets collected in an accelerated longitudinal design from 81 children aged 2-6 years (age = 4.6 ± 0.98 years, 47 males). Children completed pre-reading assessments (NEPSY-II Phonological Processing and Speeded Naming) and underwent a diffusion magnetic resonance imaging (MRI) scan to assess white matter connectivity. We defined a core neural network of reading and language regions based on prior literature, and structural connections within this network were assessed using graph theory analysis. Linear mixed models accounting for repeated measures were used to test associations between children's pre-reading performance and graph theory measures for the whole bilateral reading network and each hemisphere separately. Phonological Processing scores were positively associated with global efficiency, local efficiency, and clustering coefficient in the bilateral and right hemisphere networks, as well as local efficiency and clustering coefficient in the left hemisphere network. Our findings provide further evidence that structural neural correlates of Phonological Processing emerge in early childhood, before and during early reading instruction.

Brain bases of morphological awareness and longitudinal word reading outcomes

Children's spoken language skills are essential to the development of the "reading brain," or the neurocognitive systems that underlie successful literacy. Morphological awareness, or sensitivity to the smallest units of meaning, is a language skill that facilitates fluent recognition of meaning in print. Yet despite the growing evidence that morphology is integral to literacy success, associations among morphological awareness, literacy acquisition, and brain development remain largely unexplored. To address this gap, we conducted a longitudinal investigation with 75 elementary school children (5-11 years of age) who completed an auditory morphological awareness neuroimaging task at Time 1 as well as literacy assessments at both Time 1 and Time 2 (1.5 years later). Findings reveal longitudinal brain-behavior associations between morphological processing at Time 1 and reading outcomes at Time 2. First, activation in superior temporal brain regions involved in word segmentation was associated with both future reading skill and steeper reading gains over time. Second, a wider array of brain regions across the language network were associated with polymorphemic word reading as compared with broader word reading skill (reading both simple and complex words). Together, these findings reinforce the importance of word segmentation skills in learning to read and highlight the importance of considering complex word reading skills in building comprehensive neurocognitive models of literacy. This study fills a gap in our knowledge of how processing meaningful units in speech may help to explain differences in children's reading development over time and informs ongoing theoretical questions about the role of morphology in learning to read.

Will you read how I will read? Naturalistic fMRI predictors of emergent reading

Despite reading being an essential and almost universal skill in the developed world, reading proficiency varies substantially from person to person. To study why, the fMRI field is beginning to turn from single-word or nonword reading tasks to naturalistic stimuli like connected text and listening to stories. To study reading development in children just beginning to read, listening to stories is an appropriate paradigm because speech perception and phonological processing are important for, and are predictors of, reading proficiency. Our study examined the relationship between behavioral reading-related skills and the neural response to listening to stories in the fMRI environment. Functional MRI were gathered in a 3T TIM-Trio scanner. During the fMRI scan, children aged approximately 7 years listened to professionally narrated common short stories and answered comprehension questions following the narration. Analyses of the data used inter-subject correlation (ISC), and representational similarity analysis (RSA). Our primary finding is that ISC reveals areas of increased synchrony in both high- and low-performing emergent readers previously implicated in reading ability/disability. Of particular interest are that several previously identified brain regions (medial temporal gyrus (MTG), inferior frontal gyrus (IFG), inferior temporal gyrus (ITG)) were found to "synchronize" across higher reading ability participants, while lower reading ability participants had idiosyncratic activation patterns in these regions. Additionally, two regions (superior frontal gyrus (SFG) and another portion of ITG) were recruited by all participants, but their specific timecourse of activation depended on reading performance. These analyses support the idea that different brain regions involved in reading follow different developmental trajectories that correlate with reading proficiency on a spectrum rather than the usual dichotomy of poor readers versus strong readers.

The behavioral and neurobiological relationships between executive function and reading: A review and preliminary findings

Despite decades of prior research, the mechanisms for how skilled reading develops remain elusive. Numerous studies have identified word recognition and oral language ability as key components to explain later reading comprehension performance. However, these components alone do not fully explain differences in reading achievement. There is ongoing work exploring other candidate processes important for reading, such as the domain-general cognitive ability of executive function (EF). Here, we summarize our work on the behavioral and neurobiological connections between EF and reading and present preliminary neuroimaging findings from ongoing work. Together, these studies suggest 1) that EF plays a supportive and perhaps indirect role in reading achievement and 2) that EF-related brain regions interface with the reading and language networks. While further work is needed to dissect the specifics of how EF interacts with reading, these studies begin to reveal the complex role that EF plays in reading development.

Machine Learning and Prediction in Fetal, Infant, and Toddler Neuroimaging: A Review and Primer

Predictive models in neuroimaging are increasingly designed with the intent to improve risk stratification and support interventional efforts in psychiatry. Many of these models have been developed in samples of children school-aged or older. Nevertheless, despite growing evidence that altered brain maturation during the fetal, infant, and toddler (FIT) period modulates risk for poor mental health outcomes in childhood, these models are rarely implemented in FIT samples. Applications of predictive modeling in children of these ages provide an opportunity to develop powerful tools for improved characterization of the neural mechanisms underlying development. To facilitate the broader use of predictive models in FIT neuroimaging, we present a brief primer and systematic review on the methods used in current predictive modeling FIT studies. Reflecting on current practices in more than 100 studies conducted over the past decade, we provide an overview of topics, modalities, and methods commonly used in the field and under-researched areas. We then outline ethical and future considerations for neuroimaging researchers interested in predicting health outcomes in early life, including researchers who may be relatively new to either advanced machine learning methods or using FIT data. Altogether, the last decade of FIT research in machine learning has provided a foundation for accelerating the prediction of early-life trajectories across the full spectrum of illness and health.

Sources of Heterogeneity in Functional Connectivity During English Word Processing in Bilingual and Monolingual Children

Diversity and variation in language experiences, such as bilingualism, contribute to heterogeneity in children's neural organization for language and brain development. To uncover sources of such heterogeneity in children's neural language networks, the present study examined the effects of bilingual proficiency on children's neural organization for language function. To do so, we took an innovative person-specific analytical approach to investigate young Chinese-English and Spanish-English bilingual learners of structurally distinct languages. Bilingual and English monolingual children (N = 152, M(SD)_age = 7.71(1.32)) completed an English word recognition task during functional near-infrared spectroscopy neuroimaging, along with language and literacy tasks in each of their languages. Two key findings emerged. First, bilinguals' heritage language proficiency (Chinese or Spanish) made a unique contribution to children's language network density. Second, the findings reveal common and unique patterns in children's patterns of task-related functional connectivity. Common across all participants were short-distance neural connections within left hemisphere regions associated with semantic processes (within middle temporal and frontal regions). Unique to more proficient language users were additional long-distance connections between frontal, temporal, and bilateral regions within the broader language network. The study informs neurodevelopmental theories of language by revealing the effects of heterogeneity in language proficiency and experiences on the structure and quality of emerging language neural networks in linguistically diverse learners.

Modulations of right hemisphere connectivity in young children relates to the perception of spoken words

The early school years shape a young brain's capability to comprehend and contextualize words within milliseconds of exposure. Parsing word sounds (phonological interpretation) and word recognition (enabling semantic interpretation) are integral to this process. Yet little is known about the causal mechanisms of cortical activity during these early developmental stages. In this study, we aimed to explore these causal mechanisms via dynamic causal modelling of event-related potentials (ERPs) acquired from 30 typically developing children (ages 6-8 years) as they completed a spoken word-picture matching task. Source reconstruction of high-density electroencephalography (128 channels) was used to ascertain differences in whole-brain cortical activity during semantically "congruent" and "incongruent" conditions. Source activations analyzed during the N400 ERP window identified significant regions-of-interest (p_FWE<.05) localized primarily in the right hemisphere when contrasting congruent and incongruent word-picture stimuli. Dynamic causal models (DCMs) were tested on source activations in the fusiform gyrus (rFusi), inferior parietal lobule (rIPL), inferior temporal gyrus (rITG) and superior frontal gyrus (rSFG). DCM results indicated that a fully connected bidirectional model with self-(inhibiting) connections over rFusi, rIPL and rSFG provided the highest model evidence, based on exceedance probabilities derived from Bayesian statistical inferences. Connectivity parameters of rITG and rSFG regions from the winning DCM were negatively correlated with behavioural measures of receptive vocabulary and phonological memory (p_FDR<.05), such that lower scores on these assessments corresponded with increased connectivity between temporal pole and anterior frontal regions. The findings suggest that children with lower language processing skills required increased recruitment of right hemisphere frontal/temporal areas during task performance.

Longitudinal investigation of executive function development employing task-based, teacher reports, and fNIRS multimethodology in 4- to 5-year-old children

Increased focus on resting-state functional connectivity (rsFC) and the use and accessibility of functional near-infrared spectroscopy (fNIRS) have advanced knowledge on the interconnected nature of neural substrates underlying executive function (EF) development in adults and clinical populations. Less is known about the relationship between rsFC and developmental changes in EF during preschool years in typically developing children, a gap the present study addresses employing task-based assessment, teacher reports, and fNIRS multimethodology. This preregistered study contributes to our understanding of the neural basis of EF development longitudinally with 41 children ages 4-5. Changes in prefrontal cortex (PFC) rsFC utilizing fNIRS, EF measured with a common task-based assessment (Day-Night task), and teacher reports of behavior (BRIEF-P) were monitored over multiple timepoints: Initial Assessment, 72 h follow-up, 1 Month Follow-up, and 4 Month Follow-up. Measures of rsFC were strongly correlated 72 h apart, providing evidence of high rsFC measurement reliability using fNIRS with preschool-aged children. PFC rsFC was positively correlated with performance on task-based and report-based EF assessments. Children's PFC functional connectivity at rest uniquely predicted later EF, controlling for verbal IQ, age, and sex. Functional connectivity at rest using fNIRS may potentially show the rapid changes in EF development in young children, not only neurophysiologically, but also as a correlate of task-based EF performance and ecologically-relevant teacher reports of EF in a classroom context.

Neural pathways of phonological and semantic processing and its relations to children's reading skills

Behavioral research shows that children's phonological ability is strongly associated with better word reading skills, whereas semantic knowledge is strongly related to better reading comprehension. However, most neuroscience research has investigated how brain activation during phonological and semantic processing is related to word reading skill. This study examines if connectivity during phonological processing in the dorsal inferior frontal gyrus (dIFG) to posterior superior temporal gyrus (pSTG) pathway is related to word reading skill, whereas connectivity during semantic processing in the ventral inferior frontal gyrus (vIFG) to posterior middle temporal gyrus (pMTG) pathway is related to reading comprehension skill. We used behavioral and functional magnetic resonance imaging (fMRI) data from a publicly accessible dataset on OpenNeuro.org. The research hypotheses and analytical plan were pre-registered on the Open Science Framework. Forty-six children ages 8-15 years old were included in the final analyses. Participants completed an in-scanner reading task tapping into phonology (i.e., word rhyming) and semantics (i.e., word meaning) as well as standardized measures of word reading and reading comprehension skill. In a series of registered and exploratory analyses, we correlated connectivity coefficients from generalized psychophysiological interactions (gPPI) with behavioral measures and used z-scores to test the equality of two correlation coefficients. Results from the preregistered and exploratory analyses indicated weak evidence that functional connectivity of dIFG to pSTG during phonological processing is positively correlated with better word reading skill, but no evidence that connectivity in the vIFG-pMTG pathway during semantic processing is related to better reading comprehension skill. Moreover, there was no evidence to support the differentiation between the dorsal pathway's relation to word reading and the ventral pathway's relation to reading comprehension skills. Our finding suggesting the importance of phonological processing to word reading is in line with prior behavioral and neurodevelopmental models.

Multimodal brain features at 3 years of age and their relationship with pre-reading measures 1 year later

Pre-reading language skills develop rapidly in early childhood and are related to brain structure and functional architecture in young children prior to formal education. However, the early neurobiological development that supports these skills is not well understood. Here we acquired anatomical, diffusion tensor imaging (DTI) and resting state functional MRI (rs-fMRI) from 35 children at 3.5 years of age. Children were assessed for pre-reading abilities using the NEPSY-II subtests 1 year later (4.5 years). We applied a data-driven linked independent component analysis (ICA) to explore the shared co-variation of gray and white matter measures. Two sources of structural variation at 3.5 years of age demonstrated relationships with Speeded Naming scores at 4.5 years of age. The first imaging component involved volumetric variability in reading-related cortical regions alongside microstructural features of the superior longitudinal fasciculus (SLF). The second component was dominated by cortical volumetric variations within the cerebellum and visual association area. In a subset of children with rs-fMRI data, we evaluated the inter-network functional connectivity of the left-lateralized fronto-parietal language network (FPL) and its relationship with pre-reading measures. Higher functional connectivity between the FPL and the default mode and visual networks at 3.5 years significantly predicted better Phonological Processing scores at 4.5 years. Together, these results suggest that the integration of functional networks, as well as the co-development of white and gray matter brain structures in early childhood, support the emergence of pre-reading measures in preschool children.

Mechanical Properties of the Developing Brain are Associated with Language Input and Vocabulary Outcome

The quality of language that children hear in their environment is associated with the development of language-related brain regions, in turn promoting vocabulary knowledge. Although informative, it remains unknown how these environmental influences alter the structure of neural tissue and subsequent vocabulary outcomes. The current study uses magnetic resonance elastography (MRE) to examine how children's language environments underlie brain tissue mechanical properties, characterized as brain tissue stiffness and damping ratio, and promote vocabulary knowledge. Twenty-five children, ages 5-7, had their audio and video recorded while engaging in a play session with their parents. Children also completed the Picture Vocabulary Task (from NIH Toolbox) and participated in an MRI, where MRE and anatomical images were acquired. Higher quality input was associated with greater stiffness in the bilateral inferior frontal gyrus and right superior temporal gyrus, whereas greater vocabulary knowledge was associated with lower damping ratio in the right inferior frontal gyrus. These findings suggest changes in neural tissue composition are sensitive to malleable aspects of the environment, whereas tissue organization is more strongly associated with vocabulary outcome. Notably, these associations were independent of maternal education, suggesting more proximal measures of a child's environment may be the source of differences in neural tissue structure underlying variability in vocabulary outcomes.

Resting-state functional connectivity identifies individuals and predicts age in 8-to-26-month-olds

Resting-state functional connectivity (rsFC) measured with fMRI has been used to characterize functional brain maturation in typically and atypically developing children and adults. However, its reliability and utility for predicting development in infants and toddlers is less well understood. Here, we use fMRI data from the Baby Connectome Project study to measure the reliability and uniqueness of rsFC in infants and toddlers and predict age in this sample (8-to-26 months old; n = 170). We observed medium reliability for within-session infant rsFC in our sample, and found that individual infant and toddler's connectomes were sufficiently distinct for successful functional connectome fingerprinting. Next, we trained and tested support vector regression models to predict age-at-scan with rsFC. Models successfully predicted novel infants' age within ± 3.6 months error and a prediction R² = .51. To characterize the anatomy of predictive networks, we grouped connections into 11 infant-specific resting-state functional networks defined in a data-driven manner. We found that connections between regions of the same network-i.e. within-network connections-predicted age significantly better than between-network connections. Looking ahead, these findings can help characterize changes in functional brain organization in infancy and toddlerhood and inform work predicting developmental outcome measures in this age range.

Covid-19 pandemic and its impact on increasing the risks of children's addiction to electronic games from a social work perspective

Children are among the social groups most affected by the COVID-19 pandemic because they have found themselves forced to stay at home, far from their schoolmates, their friends, and far from all the activities they used to do before the pandemic. so, it was their only refuge for recreation during their stay in Home is staying in front of the screens of tablets, smartphones, and computers to play electronic games for long hours, and there is no doubt that the sudden shift in the lifestyle of children during the Covid-19 pandemic had serious consequences and risks threatening their stability at all levels. In light of that, the current study aimed to determine the impact of the Covid-19 pandemic on increasing the social, psychological, behavioral, and health risks of children's addiction to electronic games from a social work perspective. This study falls under the type of descriptive-analytical studies that are based on describing the reality of the problem under study. The study sample included 289 children in the age group 6-17 years in the first grade to the twelfth grade at school. The researcher designed a questionnaire that reflects the four risks facing children to assess these risks. The results showed is that the value of all impacts of the Covid-19 pandemic on the increasing risks of children's addiction to electronic games came to a total weight of (27907), weighted relative weight of (80.47%). This indication is High, indicating that the level of impact is High for the Covid-19 pandemic on the increase in all types of risks of children's addiction to electronic games. It ranked first " Behavioral Risks " at 91.15%, It is followed by the ranked second "Social risks " at 85.5%, Then came third place " Psychological Risks" at 80.91%, and in finally in fourth place " Health Risks" at 64.28%, which necessitates the need to take a set of serious measures by educating parents to monitor the content of electronic games that their children play, especially violent games, in addition to, reduce the number of hours the child spends practicing these games, and to encourage parents to form a bridge of communication and constructive dialogue between them and their children, and that parents put controls and restrictions on their children's practice of electronic games to confront abnormal behavioral, psychological and social patterns such as aggression, violence, deception, lying, imitation, vigilance, physical stress, poor eyesight, distance from practicing religious rituals, academic delay, introversion, depression, intolerance, selfishness, sadness, isolation from society, social withdrawal and lack of forming social relationships and lack of communication with others. The researcher took care that the results of the current study are very accurate and representative of the reality of the research problem, in light of the researcher's emphasis on the commitment to observe ethical rules to ensure the confidentiality of data. finally, the current study will greatly benefit researchers interested in the field of childhood and its problems and they will rely on its results and recommendations in how to protect children from the dangers of electronic game addiction in light of the Covid-19 crisis in particular.

Theory-driven classification of reading difficulties from fMRI data using Bayesian latent-mixture models

Decades of research have led to several competing theories regarding the neural contributors to impaired reading. But how can we know which theory (or theories) identifies the types of markers that indeed differentiate between individuals with reading disabilities (RD) and their typically developing (TD) peers? To answer this question, we propose a new analytical tool for theory evaluation and comparison, grounded in the Bayesian latent-mixture modeling framework. We start by constructing a series of latent-mixture classification models, each reflecting one existing theoretical claim regarding the neurofunctional markers of RD (highlighting network-level differences in either mean activation, inter-subject heterogeneity, inter-region variability, or connectivity). Then, we run each model on fMRI data alone (i.e., while models are blind to participants' behavioral status), which enables us to interpret the fit between a model's classification of participants and their behavioral (known) RD/TD status as an estimate of its explanatory power. Results from n=127 adolescents and young adults (RD: n=59; TD: n=68) show that models based on network-level differences in mean activation and heterogeneity failed to differentiate between TD and RD individuals. In contrast, classifications based on variability and connectivity were significantly associated with participants' behavioral status. These findings suggest that differences in inter-region variability and connectivity may be better network-level markers of RD than mean activation or heterogeneity (at least in some populations and tasks). More broadly, the results demonstrate the promise of latent-mixture modeling as a theory-driven tool for evaluating different theoretical claims regarding neural contributors to language disorders and other cognitive traits.

Early Phonological Neural Specialization Predicts Later Growth in Word Reading Skills

According to the Interactive Specialization Theory, cognitive skill development is facilitated by a process of neural specialization. In line with this theory, the current study investigated whether neural specialization for phonological and semantic processing at 5-to-6 years old was predictive of growth in word reading skills 2 years later. Specifically, four regression models were estimated in which reading growth was predicted from: (1) an intercept-only model; (2) measures of semantic and phonological neural specialization; (3) performance on semantic and phonological behavioral tasks; or (4) a combination of neural specialization and behavioral performance. Results from the preregistered analyses revealed little evidence in favor of the hypothesis that early semantic and phonological skills are predictive of growth in reading. However, results from the exploratory analyses, which included a larger sample, added age at Time 1 as a covariate, and investigated relative growth in reading, demonstrated decisive evidence that variability in phonological processing is predictive of reading growth. The best fitting model included both measures of specialization within the posterior superior temporal gyrus (pSTG) and behavioral performance. This work provides important evidence in favor of the Interactive Specialization Theory and, more specifically, for the role of phonological neural specialization in the development of early word reading skills.