Differences between child and adult large-scale functional brain networks for reading tasks

Neural Correlates of Narrative Reading Development: A Comparative fMRI Study of Adults and Children Using Time-Locked Inter-Subject Correlation Analyses

The naturalistic paradigm and analytical methods present new approaches that are particularly suitable for research concentrating on narrative reading development. We analyzed fMRI data from 44 adults and 42 children engaged in story reading using time-locked inter-subject correlation (ISC), inter-subject representation similarity analysis (IS-RSA), and inter-subject functional correlation (ISFC). The ISC results indicated that for both children and adults, narrative reading recruited not only traditional reading areas but also regions that are sensitive to long-time-scale information, such as the medial prefrontal cortex and hippocampus, which increased involvement from children to adults. The results of the IS-RSA indicated that during narrative reading, children exhibited greater uniqueness in neural patterns, while adults demonstrated greater similarity. The analysis of reading-level subgroups with the ISC and ISFC reveals differences in narrative reading development that span from children to adults, especially for regions sensitive to long-time-scale semantic processing. These results indicate that the maturity and experience play a crucial role in narrative reading development.

Control energy detects discrepancies in good vs. poor readers' structural-functional coupling during a rhyming task

Neuroimaging studies have identified functional and structural brain circuits that support reading. However, much less is known about how reading-related functional dynamics are constrained by white matter structure. Network control theory proposes that cortical brain dynamics are linearly determined by the white matter connectome, using control energy to evaluate the difficulty of the transition from one cognitive state to another. Here we apply this approach to linking brain dynamics with reading ability and disability in school-age children. A total of 51 children ages 8.25 -14.6 years performed an in-scanner rhyming task in visual and auditory modalities, with orthographic (spelling) and phonological (rhyming) similarity manipulated across trials. White matter structure and fMRI activation were used conjointly to compute the control energy of the reading network in each condition relative to a null fixation state. We then tested differences in control energy across trial types, finding higher control energy during non-word trials than word trials, and during incongruent trials than congruent trials. ROI analyses further showed a dissociation between control energy of the left fusiform and superior temporal gyrus depending on stimulus modality, with higher control energy for visual modalities in fusiform and higher control energy for auditory modalities in STG. Together, this study highlights that control theory can explain variations on cognitive demands in higher-level abilities such as reading, beyond what can be inferred from either functional or structural MRI measures alone.

Distinct connectivity patterns between perception and attention-related brain networks characterize dyslexia: Machine learning applied to resting-state fMRI

Diagnosis of dyslexia often occurs in late schooling years, leading to academic and psychological challenges. Furthermore, diagnosis is time-consuming, costly, and reliant on arbitrary cutoffs. On the other hand, automated algorithms hold great potential in medical and psychological diagnostics. The aim of the present study was to develop a machine learning tool for the detection of dyslexia in children based on the intrinsic connectivity patterns of different brain networks underlying perception and attention. Here, 117 children (8-12 years old; 58 females; 52 typical readers; TR and 65 children with dyslexia) completed cognitive and reading assessments and underwent 10 min of resting-state fMRI. Functional connectivity coefficients between 264 brain regions were used as features for machine learning. Different supervised algorithms were employed for classification of children with and without dyslexia. A classifier trained on dorsal attention network features exhibited the highest performance (accuracy .79, sensitivity .92, specificity .64). Auditory, visual, and fronto-parietal network-based classification showed intermediate accuracy levels (70-75%). These results highlight significant neurobiological differences in brain networks associated with visual attention between TR and children with dyslexia. Distinct neural integration patterns can differentiate dyslexia from typical development, which may be utilized in the future as a biomarker for the presence and/or severity of dyslexia.

The multiverse of data preprocessing and analysis in graph-based fMRI: A systematic literature review of analytical choices fed into a decision support tool for informed analysis

The large number of different analytical choices used by researchers is partly responsible for the challenge of replication in neuroimaging studies. For an exhaustive robustness analysis, knowledge of the full space of analytical options is essential. We conducted a systematic literature review to identify the analytical decisions in functional neuroimaging data preprocessing and analysis in the emerging field of cognitive network neuroscience. We found 61 different steps, with 17 of them having debatable parameter choices. Scrubbing, global signal regression, and spatial smoothing are among the controversial steps. There is no standardized order in which different steps are applied, and the parameter settings within several steps vary widely across studies. By aggregating the pipelines across studies, we propose three taxonomic levels to categorize analytical choices: 1) inclusion or exclusion of specific steps, 2) parameter tuning within steps, and 3) distinct sequencing of steps. We have developed a decision support application with high educational value called METEOR to facilitate access to the data in order to design well-informed robustness (multiverse) analysis.

Searching Reproducible Brain Features using NeuroMark: Templates for Different Age Populations and Imaging Modalities

A primary challenge to the data-driven analysis is the balance between poor generalizability of population-based research and characterizing more subject-, study- and population-specific variability. We previously introduced a fully automated spatially constrained independent component analysis (ICA) framework called NeuroMark and its functional MRI (fMRI) template. NeuroMark has been successfully applied in numerous studies, identifying brain markers reproducible across datasets and disorders. The first NeuroMark template was constructed based on young adult cohorts. We recently expanded on this initiative by creating a standardized normative multi-spatial-scale functional template using over 100,000 subjects, aiming to improve generalizability and comparability across studies involving diverse cohorts. While a unified template across the lifespan is desirable, a comprehensive investigation of the similarities and differences between components from different age populations might help systematically transform our understanding of the human brain by revealing the most well-replicated and variable network features throughout the lifespan. In this work, we introduced two significant expansions of NeuroMark templates first by generating replicable fMRI templates for infants, adolescents, and aging cohorts, and second by incorporating structural MRI (sMRI) and diffusion MRI (dMRI) modalities. Specifically, we built spatiotemporal fMRI templates based on 6,000 resting-state scans from four datasets. This is the first attempt to create robust ICA templates covering dynamic brain development across the lifespan. For the sMRI and dMRI data, we used two large publicly available datasets including more than 30,000 scans to build reliable templates. We employed a spatial similarity analysis to identify replicable templates and investigate the degree to which unique and similar patterns are reflective in different age populations. Our results suggest remarkably high similarity of the resulting adapted components, even across extreme age differences. With the new templates, the NeuroMark framework allows us to perform age-specific adaptations and to capture features adaptable to each modality, therefore facilitating biomarker identification across brain disorders. In sum, the present work demonstrates the generalizability of NeuroMark templates and suggests the potential of new templates to boost accuracy in mental health research and advance our understanding of lifespan and cross-modal alterations.

The characteristic patterns of individual brain susceptibility networks underlie Alzheimer's disease and white matter hyperintensity-related cognitive impairment

Excessive iron accumulation in the brain cortex increases the risk of cognitive deterioration. However, interregional relationships (defined as susceptibility connectivity) of local brain iron have not been explored, which could provide new insights into the underlying mechanisms of cognitive decline. Seventy-six healthy controls (HC), 58 participants with mild cognitive impairment due to probable Alzheimer's disease (MCI-AD) and 66 participants with white matter hyperintensity (WMH) were included. We proposed a novel approach to construct a brain susceptibility network by using Kullback‒Leibler divergence similarity estimation from quantitative susceptibility mapping and further evaluated its topological organization. Moreover, sparse logistic regression (SLR) was applied to classify MCI-AD from HC and WMH with normal cognition (WMH-NC) from WMH with MCI (WMH-MCI).The altered susceptibility connectivity in the MCI-AD patients indicated that relatively more connectivity was involved in the default mode network (DMN)-related and visual network (VN)-related connectivity, while more altered DMN-related and subcortical network (SN)-related connectivity was found in the WMH-MCI patients. For the HC vs. MCI-AD classification, the features selected by the SLR were primarily distributed throughout the DMN-related and VN-related connectivity (accuracy = 76.12%). For the WMH-NC vs. WMH-MCI classification, the features with high appearance frequency were involved in SN-related and DMN-related connectivity (accuracy = 84.85%). The shared and specific patterns of the susceptibility network identified in both MCI-AD and WMH-MCI may provide a potential diagnostic biomarker for cognitive impairment, which could enhance the understanding of the relationships between brain iron burden and cognitive decline from a network perspective.

Brain health measurement: a scoping review

OBJECTIVES

Preservation of brain health is an urgent priority for the world's ageing population. The evidence base for brain health optimisation strategies is rapidly expanding, but clear recommendations have been limited by heterogeneity in measurement of brain health outcomes. We performed a scoping review to systematically evaluate brain health measurement in the scientific literature to date, informing development of a core outcome set.

DESIGN

Scoping review.

DATA SOURCES

Medline, APA PsycArticles and Embase were searched through until 25 January 2023.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Studies were included if they described brain health evaluation methods in sufficient detail in human adults and were in English language.

DATA EXTRACTION AND SYNTHESIS

Two reviewers independently screened titles, abstracts and full texts for inclusion and extracted data using Covidence software.

RESULTS

From 6987 articles identified by the search, 727 studies met inclusion criteria. Study publication increased by 22 times in the last decade. Cohort study was the most common study design (n=609, 84%). 479 unique methods of measuring brain health were identified, comprising imaging, cognitive, mental health, biological and clinical categories. Seven of the top 10 most frequently used brain health measurement methods were imaging based, including structural imaging of grey matter and hippocampal volumes and white matter hyperintensities. Cognitive tests such as the trail making test accounted for 286 (59.7%) of all brain health measurement methods.

CONCLUSIONS

The scientific literature surrounding brain health has increased exponentially, yet measurement methods are highly heterogeneous across studies which may explain the lack of clinical translation. Future studies should aim to develop a selected group of measures that should be included in all brain health studies to aid interstudy comparison (core outcome set), and broaden from the current focus on neuroimaging outcomes to include a range of outcomes.

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.

The Effects of Age and Reading Experience on the Lifespan Neurodevelopment for Reading Comprehension

Reading comprehension is a vital cognitive skill that individuals use throughout their lives. The neurodevelopment of reading comprehension across the lifespan, however, remains underresearched. Furthermore, factors such as maturation and experience significantly influence functional brain development. Given the complexity of reading comprehension, which incorporates lower-level word reading process and higher-level semantic integration process, our study aims to investigate how age and reading experience influence the neurobiology underpinning these two processes across the lifespan. fMRI data of 158 participants aged from 7 to 77 years were collected during a passive word viewing task and a sentence comprehension task to engage the lower- and higher-level processes, respectively. We found that the neurodevelopment of the lower-level process was primarily influenced by age, showing increased activation and connectivity with age in parieto-occipital and middle/inferior frontal lobes related to morphological-semantic mapping while decreased activation in the temporoparietal regions linked to phonological processing. However, the brain function of the higher-level process was primarily influenced by reading experience, exhibiting a greater reliance on the frontotemporal semantic network with enhanced sentence-level reading performance. Furthermore, reading experience did not significantly affect the brain function of children, but had a positive effect on young adults in the lower-level process and on middle-aged and older adults in the higher-level process. These findings indicate that the brain function for lower- and higher-level processes of reading comprehension is differently affected by maturation and reading experience, and the experience effect is contingent on age regarding the two processes.

Language First, Cognition Later: Different Trajectories of Subcomponents of the Future-Reading Network in Processing Narratives from Kindergarten to Adolescence

Narrative comprehension is a linguistic ability that emerges early in life and has a critical role in language development, reading acquisition, and comprehension. According to the Simple View of Reading model, reading is acquired through word decoding and linguistic comprehension. Here, within and between networks, functional connectivity in several brain networks supporting both language and reading abilities was examined from prereading to proficient reading age in 32 healthy children, ages 5-18 years, scanned annually while listening to stories over 12 years. Functional connectivity changes within and between the networks were assessed and compared between the years using hierarchical linear regression and were related to reading abilities. At prereading age, the networks related to basic language processing accounted for 32.5% of the variation of reading ability at reading age (at 12-14 years) (R2 = 0.325, p = 0.05). At age 17, more complex cognitive networks were involved and accounted for 97.4% of the variation in reading ability (R2 = 0.974, p = 0.022). Overall, networks composing the future-reading network are highly involved in processing narratives along development; however, networks related to semantic, phonological, and syntactic processing predict reading ability earlier in life, and more complex networks predict reading proficiency later in life.

Individual differences in the neural architecture in semantic processing

Neural mechanisms underlying semantic processing have been extensively studied by using functional magnetic resonance imaging, nevertheless, the individual differences of it are yet to be unveiled. To further our understanding of functional and anatomical brain organization underlying semantic processing to the level of individual humans, we used out-of-scanner language behavioral data, T1, resting-state, and story comprehension task-evoked functional image data in the Human Connectome Project, to investigate individual variability in the task-evoked semantic processing network, and attempted to predict individuals' language skills based on task and intrinsic functional connectivity of highly variable regions, by employing a machine-learning framework. Our findings first confirmed that individual variability in both functional and anatomical markers were heterogeneously distributed throughout the semantic processing network, and that the variability increased towards higher levels in the processing hierarchy. Furthermore, intrinsic functional connectivities among these highly variable regions were found to contribute to predict individual reading decoding abilities. The contributing nodes in the overall network were distributed in the left superior, inferior frontal, and temporo-parietal cortices. Our results suggested that the individual differences of neurobiological markers were heterogeneously distributed in the semantic processing network, and that neurobiological markers of highly variable areas are not only linked to individual variability in language skills, but can predict language skills at the individual level.

Individual differences in the language task-evoked and resting-state functional networks

The resting state functional network is highly variable across individuals. However, inter-individual differences in functional networks evoked by language tasks and their comparison with resting state are still unclear. To address these two questions, we used T1 anatomical data and functional brain imaging data of resting state and a story comprehension task from the Human Connectome Project (HCP) to characterize functional network variability and investigate the uniqueness of the functional network in both task and resting states. We first demonstrated that intrinsic and task-induced functional networks exhibited remarkable differences across individuals, and language tasks can constrain inter-individual variability in the functional brain network. Furthermore, we found that the inter-individual variability of functional networks in two states was broadly consistent and spatially heterogeneous, with high-level association areas manifesting more significant variability than primary visual processing areas. Our results suggested that the functional network underlying language comprehension is unique at the individual level, and the inter-individual variability architecture of the functional network is broadly consistent in language task and resting state.

The Brain's Control Networks in Reading: Insights From Cross-Task Studies of Youth

Humans engage multiple brain systems to read successfully, including using regions important for vision, language, and control. Control refers to the set of executive processes in the brain that guide moment-to-moment behavior in service of our goals. There is a growing appreciation for the role of the brain's control system in reading comprehension, in reading skill change over time, and in those who have difficulty with the reading process. One way to understand the brain's control engagement in reading may be to study control engagement across multiple tasks in order to study consistencies, or cross-task similarities, relative to reading-specific variations. In this commentary, I briefly summarize some of our recent work studying the brain's control networks across different tasks (e.g., when reading, or doing different executive function tasks). I then review our findings of when control activation does or does not relate to measures of reading ability, and reading growth over time. The utility of cross-task comparisons in neuroimaging is noted, as well as the need to better understand multiple sources of heterogeneity in our developmental samples. I end by discussing a few of the many future directions for further study of the brain with regard to the brain's control processing and academic achievement.

Differences in brain functional networks for audiovisual integration during reading between children and adults

Building robust letter-to-sound correspondences is a prerequisite for developing reading capacity. However, the neural mechanisms underlying the development of audiovisual integration for reading are largely unknown. This study used functional magnetic resonance imaging in a lexical decision task to investigate functional brain networks that support audiovisual integration during reading in developing child readers (10-12 years old) and skilled adult readers (20-28 years old). The results revealed enhanced connectivity in a prefrontal-superior temporal network (including the right medial frontal gyrus, right superior frontal gyrus, and left superior temporal gyrus) in adults relative to children, reflecting the development of attentional modulation of audiovisual integration involved in reading processing. Furthermore, the connectivity strength of this brain network was correlated with reading accuracy. Collectively, this study, for the first time, elucidates the differences in brain networks of audiovisual integration for reading between children and adults, promoting the understanding of the neurodevelopment of multisensory integration in high-level human cognition.

Functional brain networks underlying the interaction between central and peripheral processes involved in Chinese handwriting in children and adults

The neural mechanisms that support handwriting, an important mode of human communication, are thought to be controlled by a central process (responsible for spelling) and a peripheral process (responsible for motor output). However, the relationship between central and peripheral processes has been debated. Using functional magnetic resonance imaging, this study examined the neural mechanisms underlying this relationship in Chinese handwriting in 36 children (mean age = 10.40 years) and 56 adults (mean age = 22.36 years) by manipulating character frequency (a central variable). Brain network analysis showed that character frequency reconfigured functional brain networks known to underlie motor processes, including the somatomotor and cerebellar network, in both children and adults, indicating that central processing cascades into peripheral processing. Furthermore, the network analysis characterized the interaction profiles between motor networks and linguistic-cognitive networks, fully mapping the neural architecture that supports the interaction of central and peripheral processes involved in handwriting. Taken together, these results reveal the neural interface underlying the interaction between central and peripheral processes involved in handwriting in a logographic writing system, advancing our understanding of the neural basis of handwriting.

The Brain Connectome for Chinese Reading

Chinese, as a logographic language, fundamentally differs from alphabetic languages like English. Previous neuroimaging studies have mainly focused on alphabetic languages, while the exploration of Chinese reading is still an emerging and fast-growing research field. Recently, a growing number of neuroimaging studies have explored the neural circuit of Chinese reading. Here, we summarize previous research on Chinese reading from a connectomic perspective. Converging evidence indicates that the left middle frontal gyrus is a specialized hub region that connects the ventral with dorsal pathways for Chinese reading. Notably, the orthography-to-phonology and orthography-to-semantics mapping, mainly processed in the ventral pathway, are more specific during Chinese reading. Besides, in addition to the left-lateralized language-related regions, reading pathways in the right hemisphere also play an important role in Chinese reading. Throughout, we comprehensively review prior findings and emphasize several challenging issues to be explored in future work.

Developmental differences of large-scale functional brain networks for spoken word processing

A dual-stream dissociation for separate phonological and semantic processing has been implicated in adults' language processing, but it is unclear how this dissociation emerges with development. By employing a graph-theory based brain network analysis, we compared functional interaction architecture during a rhyming and meaning judgment task of children (aged 8-12) with adults (aged 19-26). We found adults had stronger functional connectivity strength than children between bilateral inferior frontal gyri and left inferior parietal lobule in the rhyming task, between middle frontal gyrus and angular gyrus, and within occipital areas in the meaning task. Meanwhile, adults but not children manifested between-task differences in these properties. In contrast, children had stronger functional connectivity strength or nodal degree in Heschl's gyrus, superior temporal gyrus, and subcortical areas. Our findings indicated spoken word processing development is characterized by increased functional specialization, relying on the dorsal and ventral pathways for phonological and semantic processing respectively.

Disruption of Functional Brain Networks Underlies the Handwriting Deficit in Children With Developmental Dyslexia

Developmental dyslexia (DD) is a neurological-based learning disorder that affects 5-17.5% of children. Handwriting difficulty is a prevailing symptom of dyslexia, but its neural mechanisms remain elusive. Using functional magnetic resonance imaging (fMRI), this study examined functional brain networks associated with handwriting in a copying task in Chinese children with DD (n = 17) and age-matched children (n = 36). We found that dyslexics showed reduced network connectivity between the sensory-motor network (SMN) and the visual network (VN), and between the default mode network (DMN) and the ventral attention network (VAN) during handwriting, but not during drawing geometric figures. Moreover, the connectivity strength of the networks showing group differences was correlated with handwriting speed, reading and working memory, suggesting that the handwriting deficit in DD is linked with disruption of a large-scale brain network supporting motoric, linguistic and executive control processes. Taken together, this study demonstrates the alternations of functional brain networks that underly the handwriting deficit in Chinese dyslexia, providing a new clue for the neural basis of DD.

Behavioral and neurobiological evidence for the effects of reading interventions on autistic children: A systematic review

This study systematically reviewed the literature on reading interventions for autistic children. Peer-reviewed articles that reported behavioral and/or neurobiological effects of reading intervention were identified in five online databases. After screening, 15 studies met the inclusion criteria for this review. These studies focus on interventions targeted towards improving specific reading skills: comprehension, vocabulary, fluency, and phonological awareness. Studied interventions included interactive and shared reading, visualization strategies, vocabulary and main idea instruction, video modeling, and interventions supported by tablet-based technology. Overall, the studies identified in this review reported improvements to each of the targeted reading skills and changes to neural activation and connectivity. In addition, changes at the brain level were associated with improvements in reading. Specifically, frontal, temporal, and occipital regions associated with visual and language processing showed increased activation and functional connectivity following intervention. This review provides important insights into the landscape of reading intervention studies in autism and into the neurobiological underpinnings of reading skills and how interventions affect those processes.

Neural representation of phonological information during Chinese character reading

Previous studies have revealed that phonological processing of Chinese characters elicited activation in the left prefrontal cortex, bilateral parietal cortex, and occipitotemporal regions. However, it is controversial what role the left middle frontal gyrus plays in Chinese character reading, and whether the core regions (e.g., the left superior temporal gyrus and supramarginal gyrus) for phonological processing of alphabetic languages are also involved in Chinese character reading. To address these questions, the present study used both univariate and multivariate analysis (i.e., representational similarity analysis, RSA) to explore neural representations of phonological information during Chinese character reading. Participants were scanned while performing a reading aloud task. Univariate activation analysis revealed a widely distributed network for word reading, including the bilateral inferior frontal gyrus, middle frontal gyrus, lateral temporal cortex, and occipitotemporal cortex. More importantly, RSA showed that the left prefrontal (i.e., the left middle frontal gyrus and left inferior frontal gyrus) and bilateral occipitotemporal areas (i.e., the left inferior and middle temporal gyrus and bilateral fusiform gyrus) represented phonological information of Chinese characters. These results confirmed the importance of the left middle frontal gyrus and regions in ventral pathway in representing phonological information of Chinese characters.

The longitudinal development of large-scale functional brain networks for arithmetic ability from childhood to adolescence

Arithmetic ability is an important high-level cognitive function that requires interaction among multiple brain regions. Previous studies on arithmetic development have focused on task-induced activation in isolated brain regions or functional connectivity among particular seed regions. However, it remains largely unknown whether and how functional connectivity among large-scale brain modules contributes to arithmetic development. In the present study, we used a longitudinal sample of task-based functional magnetic resonance imaging (fMRI) data comprising 63 typically developing children, with two testing points being about two years apart. With graph theory, we examined the longitudinal development of large-scale brain modules for a multiplication task in younger (mean age 9.88 at time 1) and older children (mean age 12.34 at time 1), respectively. The results showed that the default-mode (DMN) and frontal-parietal networks (FPN) became increasingly segregated over time. Specifically, intra-connectivity within the DMN and FPN increased significantly with age, and inter-connectivity between the DMN and visual network decreased significantly with age. Such developmental changes were mainly observed in the younger children, but not in the older children. Moreover, the change in network segregation of the DMN was positively correlated with longitudinal gain in arithmetic performance in the younger children, and individual difference in network segregation of the FPN was positively correlated with arithmetic performance at time 2 in the older children. Taken together, the present results highlight the development of the functional architecture in large-scale brain networks from childhood to adolescence, which may provide insights into potential neural mechanisms underlying arithmetic development.

Sex differences in the intrinsic reading neural networks of Chinese children

Sex differences in reading performance have been considered a relatively stable phenomenon. However, there is no general agreement about their neural basis, which might be due to that sex differences are largely influenced by age. This paper focuses on the sex differences in the reading-related neural network of Chinese children and its interaction with age. We also attempt to predict reading abilities based on neural network. Fifty-three boys and 56 girls (8.2–14.6 years of age) were recruited. We collected their resting-state fMRI and behavioural data. Restricted sex differences were found in the resting-state reading neural network compared to extensive age by sex interaction effect. Specifically, the interactions between sex and age indicated that with increasing age, girls showed greater connectivity strength between visual orthographic areas and other brain areas within the reading network, while boys showed an opposite trend. After controlling age, the prediction models of reading performance for the girls mainly included interhemispheric connections, while the intrahemispheric connections (particularly the phonological route) mainly contributed to predicting the reading ability for boys. Taken together, these findings suggest that sex differences in reading neural networks are modulated by age. Partialling out age, boys and girls also show the stable sex differences in relationship between reading neural circuit and reading behaviour.

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Sex differences in reading neural networks are modulated by age.

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Girls’ RSFCs within reading neural networks increase with age, contrary to boys.

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Intra- and interhemispheric RSFCs predict the reading ability of boys and girls, respectively.

Left and Right Arcuate Fasciculi Are Uniquely Related to Word Reading Skills in Chinese-English Bilingual Children

Whether reading in different writing systems recruits language-unique or language-universal neural processes is a long-standing debate. Many studies have shown the left arcuate fasciculus (AF) to be involved in phonological and reading processes. In contrast, little is known about the role of the right AF in reading, but some have suggested that it may play a role in visual spatial aspects of reading or the prosodic components of language. The right AF may be more important for reading in Chinese due to its logographic and tonal properties, but this hypothesis has yet to be tested. We recruited a group of Chinese-English bilingual children (8.2 to 12.0 years old) to explore the common and unique relation of reading skill in English and Chinese to fractional anisotropy (FA) in the bilateral AF. We found that both English and Chinese reading skills were positively correlated with FA in the rostral part of the left AF-direct segment. Additionally, English reading skill was positively correlated with FA in the caudal part of the left AF-direct segment, which was also positively correlated with phonological awareness. In contrast, Chinese reading skill was positively correlated with FA in certain segments of the right AF, which was positively correlated with visual spatial ability, but not tone discrimination ability. Our results suggest that there are language universal substrates of reading across languages, but that certain left AF nodes support phonological mechanisms important for reading in English, whereas certain right AF nodes support visual spatial mechanisms important for reading in Chinese.

Maladaptive compensation of right fusiform gyrus in developmental dyslexia: A hub-based white matter network analysis

Cognitive theories have been proposed to clarify the causes and symptoms of dyslexia. However, correlations between local network parameters of white matter connectivity and literacy skills remain poorly known. An unbiased hypothesis-free approach was adopted to examine the correlations between literacy symptoms (reading and spelling) and hub-based white matter networks' connectivity parameters [nodal degree fractional anisotropy (FA) values] of 90 brain regions based on Anatomical Atlas Labels (AAL) in a group of French children with dyslexia aged 9-14 years. Results revealed that the higher the right fusiform gyrus's (FFG) nodal degree FA values, the lower the reading accuracy for words and pseudowords in dyslexic children. The results indicate that the severity of word/pseudoword reading symptoms in dyslexia relates to a white matter network centered around the right FFG. The negative correlation between right FFG network connectivity and reading accuracy, in particular pseudoword reading accuracy, suggests that right FFG represents a maladaptive compensation towards a general orthography-to-phonology decoding ability in developmental dyslexia.

Poor reading is characterized by a more connected network with wrong hubs

Using graph theory, we examined topological organization of the language network in Chinese children with poor reading during an auditory rhyming task and a visual spelling task, compared to reading-matched controls and age-matched controls. First, poor readers (PR) showed reduced clustering coefficient in the left inferior frontal gyrus (IFG) and higher nodal efficiency in the bilateral superior temporal gyri (STG) during the visual task, indicating a less functionally specialized cluster around the left IFG and stronger functional links between bilateral STGs and other regions. Furthermore, PR adopted additional right-hemispheric hubs in both tasks, which may explain increased global efficiency across both tasks and lower normalized characteristic shortest path length in the visual task for the PR. These results underscore deficits in the left IFG during visual word processing and conform previous findings about compensation in the right hemisphere in children with poor reading.

Functional brain networks underlying automatic and controlled handwriting in Chinese

This study aimed to identify the functional brain networks underlying the distinctions between automatic and controlled handwriting in Chinese. Network-based analysis was applied to functional magnetic resonance imaging data collected while adult participants performed a copying task under automatic and speed-controlled conditions. We found significant differences between automatic and speed-controlled handwriting in functional connectivity within and between the frontoparietal network, default mode network, dorsal attention network, somatomotor network and visual network; these differences reflect the variations in general attentional control and task-relevant visuomotor operations. However, no differences in brain activation were detected between the two handwriting conditions, suggesting that the reorganization of functional networks, rather than the modulation of local brain activation, underlies the dissociations between automatic and controlled handwriting in Chinese. Our findings illustrate the brain basis of handwriting automaticity, shedding new light on how handwriting automaticity may be disrupted in individuals with neurological disorders.

Voxel and surface based whole brain analysis shows reading skill associated grey matter abnormalities in dyslexia

Developmental dyslexia (DD) is the most prevalent neurodevelopmental disorder with a substantial negative influence on the individual's academic achievement and career. Research on its neuroanatomical origins has continued for half a century, yielding, however, inconsistent results, lowered total brain volume being the most consistent finding. We set out to evaluate the grey matter (GM) volume and cortical abnormalities in adult dyslexic individuals, employing a combination of whole-brain voxel- and surface-based morphometry following current recommendations on analysis approaches, coupled with rigorous neuropsychological testing. Whilst controlling for age, sex, total intracranial volume, and performance IQ, we found both decreased GM volume and cortical thickness in the left insula in participants with DD. Moreover, they had decreased GM volume in left superior temporal gyrus, putamen, globus pallidus, and parahippocampal gyrus. Higher GM volumes and cortical thickness in these areas correlated with better reading and phonological skills, deficits of which are pivotal to DD. Crucially, total brain volume did not influence our results, since it did not differ between the groups. Our findings demonstrating abnormalities in brain areas in individuals with DD, which previously were associated with phonological processing, are compatible with the leading hypotheses on the neurocognitive origins of DD.

Both frontal and temporal cortex exhibit phonological and semantic specialization during spoken language processing in 7- to 8-year-old children

A previous functional magnetic resonance imaging (fMRI) study by Weiss et al. (Weiss et al., Human Brain Mapping, 2018, 39, 4334–4348) examined brain specialization for phonological and semantic processing of spoken words in young children who were 5 to 6 years old and found evidence for specialization in the temporal but not the frontal lobe. According to a prominent neurocognitive model of language development (Skeide & Friederici, Nature Reviews Neuroscience, 2016, 17, 323–332), the frontal lobe matures later than the temporal lobe. Thus, the current study aimed to examine if brain specialization in the frontal lobe can be observed in a slightly older cohort of children aged 7 to 8 years old using the same experimental and analytical approach as in Weiss et al. (Weiss et al., Human Brain Mapping, 2018, 39, 4334–4348). One hundred and ten typically developing children were recruited and were asked to perform a sound judgment task, tapping into phonological processing, and a meaning judgment task, tapping into semantic processing, while in the MRI scanner. Direct task comparisons showed that these children exhibited language specialization in both the temporal and the frontal lobes, with the left posterior dorsal inferior frontal gyrus (IFG) showing greater activation for the sound than the meaning judgment task, and the left anterior ventral IFG and the left posterior middle temporal gyrus (MTG) showing greater activation for the meaning than the sound judgment task. These findings demonstrate that 7‐ to 8‐year‐old children have already begun to develop a language‐related specialization in the frontal lobe, suggesting that early elementary schoolers rely on both specialized linguistic manipulation and representation mechanisms to perform language tasks.

The development of brain functional connectome during text reading

Reading is an important skill for human beings to obtain information, whose acquisition is a major learning task for children. Especially, compared with single word reading, text reading requires an integration of multiple cognitive processes, which makes its underlying neural developmental mechanism not only extremely complicated but also remained poorly understood. Employing the graph theory analysis method, the present study explored the development of brain in the context of story reading from the perspective of connectomics. Forty-two primary school students and thirty-two adults read the stories in the functional magnetic resonance imaging (fMRI) experiment. We found that compared with children, adults had increased connectivity strength, nodal degree, and modular interactions for vision-related and semantics-related brain regions while decreased connectivity strength, nodal degree, and modular interactions for phonology-related brain regions. Brain-behavior association analysis suggested that the transmission to vision-related brain circuits would enhance the reading performance in adults, whereas phonology-related brain circuits played important roles in children’s reading before they develop into fluent readers. Collectivity, we highlight a shift from reliance on phonology-related networks to semantics-related and vision-related networks with age for text reading, which provides insights into the underlying neural signature of developmental cognitive mechanisms.

Disrupted Subcortical-Cortical Connections in a Phonological but Not Semantic Task in Chinese Children With Dyslexia

Reading disability has been considered as a disconnection syndrome. Recently, an increasing number of studies have emphasized the role of subcortical regions in reading. However, the majority of research on reading disability has focused on the connections amongst brain regions within the classic cortical reading network. Here, we used graph theoretical analysis to investigate whether subcortical regions serve as hubs (regions highly connected with other brain regions) during reading both in Chinese children with reading disability (N = 15, age ranging from 11.03 to 13.08 years) and in age-matched typically developing children (N = 16, age ranging from 11.17 to 12.75 years) using a visual rhyming judgment task and a visual meaning judgment task. We found that the bilateral thalami were the unique hubs for typically developing children across both tasks. Additionally, subcortical regions (right putamen, left pallidum) were also unique hubs for typically developing children but only in the rhyming task. Among these subcortical hub regions, the left pallidum showed reduced connectivity with inferior frontal regions in the rhyming judgment but not semantic task in reading disabled compared with typically developing children. These results suggest that subcortical-cortical disconnection, which may be particularly relevant to the phonological and phonology-related learning process, may be associated with Chinese reading disability.

Changed functional connectivity at rest in functional illiterates after extensive literacy training

Background

About 6.2 million adults in Germany cannot read and write properly despite attending school for several years. They are considered to be functional illiterates (FI). Since the ability to read and write is crucial for being employed and socially accepted, we developed a special literacy training to overcome these deficits.

Methods

In this study, we investigate training-related changes in intrinsic functional connectivity (iFC) at rest in a group of 20 FI and 20 adult normal readers using resting state functional magnetic resonance imaging (rsfMRI). We used independent component analysis (ICA) to define different networks.

Results

Before training, the between group analysis showed increased iFC in FI in a left-fronto-parietal network (LFPN; anterior insula, medial frontal cortex, lateral and frontal parietal regions) and in the Basal Ganglia network (BGN: thalamus, caudate, putamen, pallidum, amygdala, supplementary motor cortex and cingulate gyrus). Furthermore, the Visual Network-1 (VN1; temporal occipital fusiform gyrus, lateral occipital cortex, occipital pole, lingual gyrus, thalamus) showed decreased iFC in FI. After training the FI group showed reversal of the “hyperconnectivity” in middle frontal gyrus and in the frontal orbital cortex and between supramarginal gyrus and the BGN. Furthermore, functional connectivity increased in FI VN1 (lateral occipital cortex, insular cortex). These changes in connectivity correlated with gains in reading speed and spelling accuracy.

Conclusions

These findings show that poor reading and writing abilities are associated with abnormalities in iFC in several brain areas subserving cognitive processes important for reading. Intensive literacy training induces changes in the functional connectivity between and within neural networks important for literacy skills.

Neural Bases of Phonological and Semantic Processing in Early Childhood

During the early period of reading development, children gain phonological (letter-to-sound mapping) and semantic knowledge (storage and retrieval of word meaning). Their reading ability changes rapidly, accompanied by learning-induced brain plasticity as they learn to read. This study aims at identifying the neural bases of phonological and semantic processing in early childhood by using a combination of univariate and multivariate pattern analysis. Nineteen typically developing children between the age of five and seven performed visual word-level phonological (rhyming) and semantic (related meaning) judgment tasks during functional magnetic resonance imaging scans. Our multivariate analysis showed that young children with good reading ability have already recruited the left hemispheric regions in the brain for phonological processing, including the inferior frontal gyrus (IFG), superior and middle temporal gyrus, and fusiform gyrus. In addition, our multivariate results suggested that different sub-regions of the left IFG were recruited for the two tasks. Our results suggested the left lateralization of frontotemporal regions for phonological processing and semantic processing. In addition, we observed bilateral activations of parietal regions for semantic processing during early childhood. Our findings indicate that the neural bases of reading have already begun to be shaped in early childhood for typically developing children, which can be used as a control baseline for comparison of children at risk for reading difficulties.

Estimating Dynamic Functional Brain Connectivity With a Sparse Hidden Markov Model

Estimating dynamic functional network connectivity (dFNC) of the brain from functional magnetic resonance imaging (fMRI) data can reveal both spatial and temporal organization and can be applied to track the developmental trajectory of brain maturity as well as to study mental illness. Resting state fMRI (rs-fMRI) is regarded as a promising task since it reflects the spontaneous brain activity without an external stimulus. The sliding window method has been successfully used to extract dFNC but typically assumes a fixed window size. The hidden Markov model (HMM) based method is an alternative approach for estimating time-varying connectivity. In this paper, we propose a sparse HMM based on Gaussian HMM and Gaussian graphical model (GGM). In this model, the time-varying neural processes are represented as discrete brain states which are described with functional connectivity networks. By enforcing the sparsity on the precision matrix, we can get interpretable connectivity between different functional regions. The optimization of our model can be realized with the expectation maximization (EM) and graphical least absolute shrinkage and selection operator (glasso) algorithms. The proposed model is validated on both simulated blood oxygenation-level dependent (BOLD) time series and rs-fMRI data. Results indicate that the proposed model can capture both stationary and abrupt brain activity fluctuations. We also compare dFNC patterns between children and young adults from the Philadelphia Neurodevelopmental Cohort (PNC) study. Both spatial and temporal behavior of the dFNC are analyzed and compared. The results provide insight into the developmental trajectory across childhood and motivate further research on brain connectivity.

Dyslexia on a continuum: A complex network approach

We investigated the efficacy of graph-theoretic metrics of task-related functional brain connectivity in predicting reading difficulty and explored the hypothesis that task conditions emphasizing audiovisual integration would be especially diagnostic of reading difficulty. An fMRI study was conducted in which 24 children (8 to 14 years old) who were previously diagnosed with dyslexia completed a rhyming judgment task under three presentation modality conditions. Regression analyses found that characteristic connectivity metrics of the reading network showed a presentation modality dependent relationship with reading difficulty: Children with more segregated reading networks and those that used fewer of the available connections were those with the least severe reading difficulty. These results are consistent with the hypothesis that a lack of coordinated processing between the neural regions involved in phonological and orthographic processing contributes towards reading difficulty.

Longitudinal Task-Related Functional Connectivity Changes Predict Reading Development

Longitudinal studies suggest developmentally dependent changes in lexical processing during reading development, implying a change in inter-regional functional connectivity over this period. The current study used functional magnetic resonance imaging (fMRI) to explore developmental changes in functional connectivity across multiple runs of a rhyming judgment task in young readers (8–14 years) over an average 2.5-year span. Changes in functional segregation are correlated with and predict changes in the skill with which typically developing children learn to apply the alphabetic principle, as measured by pseudoword decoding. This indicates a developmental shift in the proportion of specialized functional clusters is associated with changes in reading skill and suggests a dependency of reading development on changes of particular neural pathways, specifically decreases in transitivity is indicative of greater network integration. This work provides evidence that characteristics of these pathways, quantified using graph-theoretic metrics, can be used to predict individual differences in reading development.

Structural and functional abnormality of the putamen in children with developmental dyslexia

There is currently debate with regards to the role of phonological deficit in Chinese reading difficulty, even though some researchers have suggested that the deficit of phonological processing is also a signature of developmental dyslexia in Chinese, as has been found in alphabetic languages. In this study, we examined the brain mechanisms of phonological deficit in Chinese children with developmental dyslexia (DD) during an auditory rhyming judgment task. First, we examined structural differences in Chinese dyslexia by comparing gray and white matter volume in Chinese children with DD, age-matched controls (AC), and reading-matched controls (RC). Next, we examined whether the regions with an abnormal volume in DD showed deficient functional connectivity with the rest of the brain during a phonological task (i.e. auditory rhyming judgment). We found that both AC and RC had greater gray matter volume (GMV) at the left putamen and right dorsal lateral frontal cortex than DD, suggesting possible neural signatures of developmental dyslexia. Functional connectivity analysis revealed that the left putamen was more connected with the right inferior occipital gyrus (IOG) in AC and RC than in DD, suggesting that automatic orthographic involvement during spoken language processing is more salient in controls, while the left putamen was more connected with the left transverse temporal gyrus (TTG) and left insula in DD than in AC and RC, suggesting the phonological articulation -auditory feedback loop is more involved in DD. These findings suggest that the reduced left putamen might contribute to phonological deficits experienced in DD, since it showed deficient connectivity with the rest of the brain during phonological processing.

Differences between child and adult large-scale functional brain networks for reading tasks

Reading is an important high-level cognitive function of the human brain, requiring interaction among multiple brain regions. Revealing differences between children's large-scale functional brain networks for reading tasks and those of adults helps us to understand how the functional network changes over reading development. Here we used functional magnetic resonance imaging data of 17 adults (19-28 years old) and 16 children (11-13 years old), and graph theoretical analyses to investigate age-related changes in large-scale functional networks during rhyming and meaning judgment tasks on pairs of visually presented Chinese characters. We found that: (1) adults had stronger inter-regional connectivity and nodal degree in occipital regions, while children had stronger inter-regional connectivity in temporal regions, suggesting that adults rely more on visual orthographic processing whereas children rely more on auditory phonological processing during reading. (2) Only adults showed between-task differences in inter-regional connectivity and nodal degree, whereas children showed no task differences, suggesting the topological organization of adults' reading network is more specialized. (3) Children showed greater inter-regional connectivity and nodal degree than adults in multiple subcortical regions; the hubs in children were more distributed in subcortical regions while the hubs in adults were more distributed in cortical regions. These findings suggest that reading development is manifested by a shift from reliance on subcortical to cortical regions. Taken together, our study suggests that Chinese reading development is supported by developmental changes in brain connectivity properties, and some of these changes may be domain-general while others may be specific to the reading domain.