Topological properties of large-scale structural brain networks in children with familial risk for reading difficulties

Cortical structural network characteristics in non-cognitive impairment end-stage renal disease

Objective

Explore alterations in topological features of gray matter volume (GMV) and structural networks in non-cognitive impairment end-stage renal disease (Non-CI ESRD).

Materials and methods

Utilizing graph theory, we collected structural magnetic resonance imaging (sMRI) data from 38 Non-CI ESRD patients and 50 normal controls (NC). We compared, and extracted the GMV across subject groups, constructed corresponding structural covariance networks (SCNs), and investigated the alterations in SCNs feature parameters between groups.

Results

In Non-CI ESRD patients, The GMV were reduced in several brain regions, predominantly on the left side (p < 0.05, FWE correction). The small-world network characteristics of the patient group's brain networks showed a tendency toward regular. In a few densities, global network parameters, transitivity, (p < 0.05) was significantly increased in the ESRD group. Regional network measurements revealed inconsistent changes in regional efficiency across different brain areas. In the analysis of network hubs, the right temporal pole is likely a compensatory hub for Non-CI ESRD patients. The SCNs in Non-CI ESRD patients demonstrated reduced topological stability against targeted attacks.

Conclusion

This study reveals that patients with renal failure exhibited subtle changes in brain network characteristics even before a decline in cognitive scores. These changes involve compensatory activation in certain brain regions, which enhances network transitivity to maintain the efficiency of whole-brain network information integration without significant loss. Additionally, the SCNs characteristics can serve as a neuroanatomical marker for brain alterations in Non-CI ESRD patients, offering new insights into the mechanisms of early brain injury in ESRD patients.

Brain markers of subtraction and multiplication skills in childhood: task-based functional connectivity and individualized structural similarity

Arithmetic, a high-order cognitive ability, show marked individual difference over development. Despite recent advancements in neuroimaging techniques have enabled the identification of brain markers for individual differences in high-order cognitive abilities, it remains largely unknown about the brain markers for arithmetic. This study used a data-driven connectome-based prediction model to identify brain markers of arithmetic skills from arithmetic-state functional connectivity and individualized structural similarity in 132 children aged 8 to 15 years. We found that both subtraction-state functional connectivity and individualized SS successfully predicted subtraction and multiplication skills but multiplication-state functional connectivity failed to predict either skill. Among the four successful prediction models, most predictive connections were located in frontal-parietal, default-mode, and secondary visual networks. Further computational lesion analyses revealed the essential structural role of frontal-parietal network in predicting subtraction and the essential functional roles of secondary visual, language, and ventral multimodal networks in predicting multiplication. Finally, a few shared nodes but largely nonoverlapping functional and structural connections were found to predict subtraction and multiplication skills. Altogether, our findings provide new insights into the brain markers of arithmetic skills in children and highlight the importance of studying different connectivity modalities and different arithmetic domains to advance our understanding of children's arithmetic skills.

Unique longitudinal contributions of sulcal interruptions to reading acquisition in children

A growing body of literature indicates strong associations between indentations of the cerebral cortex (i.e., sulci) and individual differences in cognitive performance. Interruptions, or gaps, of sulci (historically known as pli de passage) are particularly intriguing as previous work suggests that these interruptions have a causal effect on cognitive development. Here, we tested how the presence and morphology of sulcal interruptions in the left posterior occipitotemporal sulcus (pOTS) longitudinally impact the development of a culturally-acquired skill: reading. Forty-three children were successfully followed from age 5 in kindergarten, at the onset of literacy instruction, to ages 7 and 8 with assessments of cognitive, pre-literacy, and literacy skills, as well as MRI anatomical scans at ages 5 and 8. Crucially, we demonstrate that the presence of a left pOTS gap at 5 years is a specific and robust longitudinal predictor of better future reading skills in children, with large observed benefits on reading behavior ranging from letter knowledge to reading comprehension. The effect of left pOTS interruptions on reading acquisition accumulated through time, and was larger than the impact of benchmark cognitive and familial predictors of reading ability and disability. Finally, we show that increased local U-fiber white matter connectivity associated with such sulcal interruptions possibly underlie these behavioral benefits, by providing a computational advantage. To our knowledge, this is the first quantitative evidence supporting a potential integrative gray-white matter mechanism underlying the cognitive benefits of macro-anatomical differences in sulcal morphology related to longitudinal improvements in a culturally-acquired skill.

Structural network topologies are associated with deep brain stimulation outcomes in Meige syndrome

Deep brain stimulation (DBS) is an effective therapy for Meige syndrome (MS). However, the DBS efficacy varies across MS patients and the factors contributing to the variable responses remain enigmatic. We aim to explain the difference in DBS efficacy from a network perspective. We collected preoperative T1-weighted MRI images of 76 MS patients who received DBS in our center. According to the symptomatic improvement rates, all MS patients were divided into two groups: the high improvement group (HIG) and the low improvement group (LIG). We constructed group-level structural covariance networks in each group and compared the graph-based topological properties and interregional connections between groups. Subsequent functional annotation and correlation analyses were also conducted. The results indicated that HIG showed a higher clustering coefficient, longer characteristic path length, lower small-world index, and lower global efficiency compared with LIG. Different nodal betweennesses and degrees between groups were mainly identified in the precuneus, sensorimotor cortex, and subcortical nuclei, among which the gray matter volume of the left precentral gyrus and left thalamus were positively correlated with the symptomatic improvement rates. Moreover, HIG had enhanced interregional connections within the somatomotor network and between the somatomotor network and default-mode network relative to LIG. We concluded that the high and low DBS responders have notable differences in large-scale network architectures. Our study sheds light on the structural network underpinnings of varying DBS responses in MS patients.

Atypical characteristic changes of surface morphology and structural covariance network in developmental dyslexia

BACKGROUND

Developmental dyslexia (DD) is a neurodevelopmental disorder that is characterized by difficulties with all aspects of information acquisition in the written word, including slow and inaccurate word recognition. The neural basis behind DD has not been fully elucidated.

METHOD

The study included 22 typically developing (TD) children, 16 children with isolated spelling disorder (SpD), and 20 children with DD. The cortical thickness, folding index, and mean curvature of Broca's area, including the triangular part of the left inferior frontal gyrus (IFGtriang) and the opercular part of the left inferior frontal gyrus, were assessed to explore the differences of surface morphology among the TD, SpD, and DD groups. Furthermore, the structural covariance network (SCN) of the triangular part of the left inferior frontal gyrus was analyzed to explore the changes of structural connectivity in the SpD and DD groups.

RESULTS

The DD group showed higher curvature and cortical folding of the left IFGtriang than the TD group and SpD group. In addition, compared with the TD group and the SpD group, the structural connectivity between the left IFGtriang and the left middle-frontal gyrus and the right mid-orbital frontal gyrus was increased in the DD group, and the structural connectivity between the left IFGtriang and the right precuneus and anterior cingulate was decreased in the DD group.

CONCLUSION

DD had atypical structural connectivity in brain regions related to visual attention, memory and which might impact the information input and integration needed for reading and spelling.

Structural brain network connectivity in trichotillomania (hair-pulling disorder)

Neuroimaging studies suggest involvement of frontal, striatal, limbic and cerebellar regions in trichotillomania, an obsessive-compulsive related disorder. However, findings regarding the underlying neural circuitry remains limited and inconsistent. Graph theoretical analysis offers a way to identify structural brain networks in trichotillomania. T1-weighted MRI scans were acquired in adult females with trichotillomania (n = 23) and healthy controls (n = 16). Graph theoretical analysis was used to investigate structural networks as derived from cortical thickness and volumetric FreeSurfer output. Hubs, brain regions with highest connectivity in the global network, were identified, and group differences were determined. Regions with highest connectivity on a regional level were also determined. There were no differences in small-worldness or other network measures between groups. Hubs in the global network of trichotillomania patients included temporal, parietal, and occipital regions (at 2SD above mean network connectivity), as well as frontal and striatal regions (at 1SD above mean network connectivity). In contrast, in healthy controls hubs at 2SD represented different frontal, parietal and temporal regions, while at 1SD hubs were widespread. The inferior temporal gyrus, involved in object recognition as part of the ventral visual pathway, had significantly higher connectivity on a global and regional level in trichotillomania. The study included women only and sample size was limited. This study adds to the trichotillomania literature on structural brain network connectivity. Our study findings are consistent with previous studies that have implicated somatosensory, sensorimotor and frontal-striatal circuitry in trichotillomania, and partially overlap with structural connectivity findings in obsessive-compulsive disorder.

Structural gray matter features and behavioral preliterate skills predict future literacy - A machine learning approach

When children learn to read, their neural system undergoes major changes to become responsive to print. There seem to be nuanced interindividual differences in the neurostructural anatomy of regions that later become integral parts of the reading network. These differences might affect literacy acquisition and, in some cases, might result in developmental disorders like dyslexia. Consequently, the main objective of this longitudinal study was to investigate those interindividual differences in gray matter morphology that might facilitate or hamper future reading acquisition. We used a machine learning approach to examine to what extent gray matter macrostructural features and cognitive-linguistic skills measured before formal literacy teaching could predict literacy 2 years later. Forty-two native German-speaking children underwent T1-weighted magnetic resonance imaging and psychometric testing at the end of kindergarten. They were tested again 2 years later to assess their literacy skills. A leave-one-out cross-validated machine-learning regression approach was applied to identify the best predictors of future literacy based on cognitive-linguistic preliterate behavioral skills and cortical measures in a priori selected areas of the future reading network. With surprisingly high accuracy, future literacy was predicted, predominantly based on gray matter volume in the left occipito-temporal cortex and local gyrification in the left insular, inferior frontal, and supramarginal gyri. Furthermore, phonological awareness significantly predicted future literacy. In sum, the results indicate that the brain morphology of the large-scale reading network at a preliterate age can predict how well children learn to read.

Altered brain network topology during speech tracking in developmental dyslexia

Developmental dyslexia is often accompanied by altered phonological processing of speech. Underlying neural changes have typically been characterized in terms of stimulus- and/or task-related responses within individual brain regions or their functional connectivity. Less is known about potential changes in the more global functional organization of brain networks. Here we recorded electroencephalography (EEG) in typical and dyslexic readers while they listened to (a) a random sequence of syllables and (b) a series of tri-syllabic real words. The network topology of the phase synchronization of evoked cortical oscillations was investigated in four frequency bands (delta, theta, alpha and beta) using minimum spanning tree graphs. We found that, compared to syllable tracking, word tracking triggered a shift toward a more integrated network topology in the theta band in both groups. Importantly, this change was significantly stronger in the dyslexic readers, who also showed increased reliance on a right frontal cluster of electrodes for word tracking. The current findings point towards an altered effect of word-level processing on the functional brain network organization that may be associated with less efficient phonological and reading skills in dyslexia.

Abnormalities of Cortical Morphology and Structural Covariance Network in Patients with Subacute Basal Ganglia Stroke

RATIONALE AND OBJECTIVES

The direct damage caused by ischemic stroke is relatively localized, but structural reorganization of cortical regions could occur across the brain. Changes of large-scale, cortical structural brain networks after basal ganglia stroke are less well reported. We, therefore, aim to explore the abnormalities of cortical morphology and structural network topology in patients with unilateral basal ganglia stroke during the subacute period.

MATERIALS AND METHODS

Thirty patients with first-ever basal ganglia stroke and thirty age- and sex-matched healthy controls were recruited for our analysis. Patients underwent structural magnetic resonance imaging examinations and clinical assessment from seven days to three months post-stroke. Alterations in cortical morphology and topological properties of the cortical structural network were measured respectively using the surface-based morphology and graph-theoretical methods.

RESULTS

We observed focal cortical atrophy, specifically in areas of frontal and temporal cortices. Moreover, the cortical thickness in the contralesional transverse temporal gyrus and superior temporal gyrus was positively correlated with cognitive function scores. Network analysis revealed that patients with basal ganglia stroke showed increased clustering coefficient, increased mean local efficiency as well as a reorganization of degree-based hubs. In addition, these patients also showed reduced robustness under a random attack compared to healthy controls.

CONCLUSION

These findings indicated a unique pattern of cortical reorganization and the abnormal topological organization of cortical thickness-based structural covariance networks in patients with basal ganglia stroke, which is beneficial to understand the pathophysiological mechanisms of functional disorders at the cortical structural network level and find potential targets for induced neuromodulation.

Mother-child similarity in brain morphology: A comparison of structural characteristics of the brain's reading network

BACKGROUND

Substantial evidence acknowledges the complex gene-environment interplay impacting brain development and learning. Intergenerational neuroimaging allows the assessment of familial transfer effects on brain structure, function and behavior by investigating neural similarity in caregiver-child dyads.

METHODS

Neural similarity in the human reading network was assessed through well-used measures of brain structure (i.e., surface area (SA), gyrification (lG), sulcal morphology, gray matter volume (GMV) and cortical thickness (CT)) in 69 mother-child dyads (children's age~11 y). Regions of interest for the reading network included left-hemispheric inferior frontal gyrus, inferior parietal lobe and fusiform gyrus. Mother-child similarity was quantified by correlation coefficients and familial specificity was tested by comparison to random adult-child dyads. Sulcal morphology analyses focused on occipitotemporal sulcus interruptions and similarity was assessed by chi-square goodness of fit.

RESULTS

Significant structural brain similarity was observed for mother-child dyads in the reading network for lG, SA and GMV (r = 0.349/0.534/0.542, respectively), but not CT. Sulcal morphology associations were non-significant. Structural brain similarity in lG, SA and GMV were specific to mother-child pairs. Furthermore, structural brain similarity for SA and GMV was higher compared to CT.

CONCLUSION

Intergenerational neuroimaging techniques promise to enhance our knowledge of familial transfer effects on brain development and disorders.

Abnormal cortical thickness and structural covariance networks in systemic lupus erythematosus patients without major neuropsychiatric manifestations

BACKGROUND

Non-neuropsychiatric systemic lupus erythematosus (non-NPSLE) has been confirmed to have subtle changes in brain structure before the appearance of obvious neuropsychiatric symptoms. Previous literature mainly focuses on brain structure loss in non-NPSLE; however, the results are heterogeneous, and the impact of structural changes on the topological structure of patients' brain networks remains to be determined. In this study, we combined neuroimaging and network analysis methods to evaluate the changes in cortical thickness and its structural covariance networks (SCNs) in patients with non-NPSLE.

METHODS

We compare the cortical thickness of non-NPSLE patients (N=108) and healthy controls (HCs, N=88) using both surface-based morphometry (SBM) and regions of interest (ROI) methods, respectively. After that, we analyzed the correlation between the abnormal cortical thickness results found in the ROI method and a series of clinical features. Finally, we constructed the SCNs of two groups using the regional cortical thickness and analyzed the abnormal SCNs of non-NPSLE.

RESULTS

By SBM method, we found that cortical thickness of 34 clusters in the non-NPSLE group was thinner than that in the HC group. ROI method based on Destrieux atlas showed that cortical thickness of 57 regions in the non-NPSLE group was thinner than that in the HC group and related to the course of disease, autoantibodies, the cumulative amount of immunosuppressive agents, and cognitive psychological scale. In the SCN analysis, the cortical thickness SCNs of the non-NPSLE group did not follow the small-world attribute at a few densities, and the global clustering coefficient appeared to increase. The area under the curve analysis showed that there were significant differences between the two groups in clustering coefficient, degree, betweenness, and local efficiency. There are a total of seven hubs for non-NPSLE, and five hubs in HCs, the two groups do not share a common hub distribution.

CONCLUSION

Extensive and obvious reduction in cortical thickness and abnormal topological organization of SCNs are observed in non-NPSLE patients. The observed abnormalities may not only be the realization of brain damage caused by the disease, but also the contribution of the compensatory changes within the nervous system.

Potential structural trait markers of depression in the form of alterations in the structures of subcortical nuclei and structural covariance network properties

It has been proposed recently that major depressive disorder (MDD) could represent an adaptation to conserve energy after the perceived loss of an investment in a vital source, such as group identity, personal assets, or relationships. Energy conserving behaviors associated with MDD may form a persistent marker in brain regions and networks involved in cognition and emotion regulation. In this study, we examined whether subcortical regions and volume-based structural covariance networks (SCNs) have state-independent alterations (trait markers). First-episode drug-naïve currently depressed (cMDD) patients (N = 131), remitted MDD (RD) patients (N = 67), and healthy controls (HCs, N = 235) underwent structural magnetic resonance imaging (MRI). Subcortical gray matter volumes (GMVs) were calculated in FreeSurfer software, and group differences in GMVs and SCN were analyzed. Compared to HCs, major findings were decreased GMVs of left pallidum and pulvinar anterior of thalamus in the cMDD and RD groups, indicative of a trait marker. Relative to HCs, subcortical SCNs of both cMDD and RD patients were found to have reduced small-world-ness and path length, which together may represent a trait-like topological feature of depression. In sum, the left pallidum, left pulvinar anterior of thalamus volumetric alterations may represent trait marker and reduced small-world-ness, path length may represent trait-like topological feature of MDD.

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.

Gout Is Not Just Arthritis: Abnormal Cortical Thickness and Structural Covariance Networks in Gout

Background: Hyperuricemia is the cause of gout. The antioxidant and neuroprotective effects of uric acid seem to benefit some patients with central nervous system injury. However, changes in the brain structure have not been discovered in patients with gout.

Object: Clarify the changes in cortical thickness in patients with gout and the alteration of the structural covariance networks (SCNs) based on cortical thickness.

Methods: We collected structural MRIs of 23 male gout patients and 23 age-matched healthy controls. After calculating and comparing the difference in cortical thickness between the two groups, we constructed and analyzed the cortical thickness covariance networks of the two groups, and we investigated for any changes in SCNs of gout patients.

Results: Gout patients have thicker cortices in the left postcentral, left supramarginal, right medial temporal, and right medial orbitofrontal regions; and thinner cortices were found in the left insula, left superior frontal, right pericalcarine, and right precentral regions. In SCN analysis, between-group differences in global network measures showed that gout patients have a higher global efficiency. In regional network measures, more nodes in gout patients have increased centrality. In network hub analysis, we found that the transfer of the core hub area, rather than the change in number, may be the characteristic of the gout's cortical thickness covariance network.

Conclusion: This is the first study on changes in brain cortical thickness and SCN based on graph theory in patients with gout. The present study found that, compared with healthy controls, gout patients show regional cortical thinning or thickening, and variation in the properties of the cortical thickness covariance network also changed. These alterations may be the combined effect of disease damage and physiological compensation. More research is needed to fully understand the complex underlying mechanisms of gout brain variation.

Convergent and divergent brain structural and functional abnormalities associated with developmental dyslexia

Brain abnormalities in the reading network have been repeatedly reported in individuals with developmental dyslexia (DD); however, it is still not totally understood where the structural and functional abnormalities are consistent/inconsistent across languages. In the current multimodal meta-analysis, we found convergent structural and functional alterations in the left superior temporal gyrus across languages, suggesting a neural signature of DD. We found greater reduction in grey matter volume and brain activation in the left inferior frontal gyrus in morpho-syllabic languages (e.g. Chinese) than in alphabetic languages, and greater reduction in brain activation in the left middle temporal gyrus and fusiform gyrus in alphabetic languages than in morpho-syllabic languages. These language differences are explained as consequences of being DD while learning a specific language. In addition, we also found brain regions that showed increased grey matter volume and brain activation, presumably suggesting compensations and brain regions that showed inconsistent alterations in brain structure and function. Our study provides important insights about the etiology of DD from a cross-linguistic perspective with considerations of consistency/inconsistency between structural and functional alterations.

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.

Cognitive impairment and associations with structural brain networks, endocrine status, and risk genotypes in newly orchiectomized testicular cancer patients

A higher incidence of cognitive impairment (CI) has previously been reported among orchiectomized testicular cancer patients (TCPs), but little is known about the underlying pathophysiology. The present study assessed CI in newly orchiectomized TCPs and explored the structural brain networks, endocrine status, and selected genotypes. Forty TCPs and 22 healthy controls (HCs) underwent neuropsychological testing and magnetic resonance imaging, and provided a blood sample. CI was defined as a z-score ≤ -2 on one neuropsychological test or ≤ -1.5 on two neuropsychological tests, and structural brain networks were investigated using graph theory. Associations of cognitive performance with brain networks, endocrine status (including testosterone levels and androgen receptor CAG repeat length), and genotypes (APOE, BDNF, COMT) were explored. Compared with HCs, TCPs performed poorer on 6 out of 15 neuropsychological tests, of which three tests remained statistically significant when adjusted for relevant between-group differences (p < 0.05). TCPs also demonstrated more CI than HCs (65% vs. 36%; p = 0.04). While global brain network analysis revealed no between-group differences, regional analysis indicated differences in node degree and betweenness centrality in several regions (p < 0.05), which was inconsistently associated with cognitive performance. In TCPs, CAG repeat length was positively correlated with delayed memory performance (r = 0.36; p = 0.02). A COMT group × genotype interaction effect was found for overall cognitive performance in TCPs, with risk carriers performing worse (p = 0.01). No effects were found for APOE, BDNF, or testosterone levels. In conclusion, our results support previous findings of a high incidence of CI in newly orchiectomized TCPs and provide novel insights into possible mechanisms.

Parental Educational Attainment, the Superior Temporal Cortical Surface Area, and Reading Ability among American Children: A Test of Marginalization-Related Diminished Returns

BACKGROUND

Recent studies have shown that parental educational attainment is associated with a larger superior temporal cortical surface area associated with higher reading ability in children. Simultaneously, the marginalization-related diminished returns (MDRs) framework suggests that, due to structural racism and social stratification, returns of parental education are smaller for black and other racial/ethnic minority children compared to their white counterparts.

PURPOSE

This study used a large national sample of 9-10-year-old American children to investigate associations between parental educational attainment, the right and left superior temporal cortical surface area, and reading ability across diverse racial/ethnic groups.

METHODS

This was a cross-sectional analysis that included 10,817 9-10-year-old children from the Adolescent Brain Cognitive Development (ABCD) study. Parental educational attainment was treated as a five-level categorical variable. Children's right and left superior temporal cortical surface area and reading ability were continuous variables. Race/ethnicity was the moderator. To adjust for the nested nature of the ABCD data, mixed-effects regression models were used to test the associations between parental education, superior temporal cortical surface area, and reading ability overall and by race/ethnicity.

RESULTS

Overall, high parental educational attainment was associated with greater superior temporal cortical surface area and reading ability in children. In the pooled sample, we found statistically significant interactions between race/ethnicity and parental educational attainment on children's right and left superior temporal cortical surface area, suggesting that high parental educational attainment has a smaller boosting effect on children's superior temporal cortical surface area for black than white children. We also found a significant interaction between race and the left superior temporal surface area on reading ability, indicating weaker associations for Alaskan Natives, Native Hawaiians, and Pacific Islanders (AIAN/NHPI) than white children. We also found interactions between race and parental educational attainment on reading ability, indicating more potent effects for black children than white children.

CONCLUSION

While parental educational attainment may improve children's superior temporal cortical surface area, promoting reading ability, this effect may be unequal across racial/ethnic groups. To minimize the racial/ethnic gap in children's brain development and school achievement, we need to address societal barriers that diminish parental educational attainment's marginal returns for middle-class minority families. Social and public policies need to go beyond equal access and address structural and societal barriers that hinder middle-class families of color and their children. Future research should test how racism, social stratification, segregation, and discrimination, which shape the daily lives of non-white individuals, take a toll on children's brains and academic development.

Large-scale network topology reveals brain functional abnormality in Chinese dyslexic children

It has been revealed that dyslexic children learning alphabetic languages are characterized by aberrant topological organization of brain networks. However, little is known about the functional organization and the reconfiguration pattern of brain networks in Chinese dyslexic children. Using graph theoretical analysis and functional magnetic resonance images (fMRI), we examined this issue specifically from the perspective of functional integration and segregation. We first compared large-scale topological organizations between dyslexic children and typically developing children during a Chinese phonological rhyming task, and found that dyslexic children showed increased local efficiency and clustering coefficient compared with typically developing children, which were negatively correlated with task performance. Furthermore, dyslexic children and typically developing children could be accurately distinguished at the individual-subject level based on the nodal local efficiency or clustering coefficient. Second, we studied the group difference of network reconfiguration and found that dyslexic children showed more difficulty when shifting from the resting state to the phonological task. Our results suggest an over-segregated brain functional organization and deficits in brain network reconfiguration in Chinese dyslexic children, which helps to advance our knowledge on the neural mechanisms underlying dyslexia.

Structural and functional brain network alterations in prenatal alcohol exposed neonates

Prenatal alcohol exposure leads to alterations in cognition, behavior and underlying brain architecture. However, prior studies have not integrated structural and functional imaging data in children with prenatal alcohol exposure. The aim of this study was to characterize disruptions in both structural and functional brain network organization after prenatal alcohol exposure in very early life. A group of 11 neonates with prenatal alcohol exposure and 14 unexposed controls were investigated using diffusion weighted structural and resting state functional magnetic resonance imaging. Covariance networks were created using graph theoretical analyses for each data set, controlling for age and sex. Group differences in global hub arrangement and regional connectivity were determined using nonparametric permutation tests. Neonates with prenatal alcohol exposure and controls exhibited similar global structural network organization. However, global functional networks of neonates with prenatal alcohol exposure comprised of temporal and limbic hubs, while hubs were more distributed in controls representing an early default mode network. On a regional level, controls showed prominent structural and functional connectivity in parietal and occipital regions. Neonates with prenatal alcohol exposure showed regionally, predominant structural and functional connectivity in several subcortical regions and occipital regions. The findings suggest early functional disruption on a global and regional level after prenatal alcohol exposure and indicate suboptimal organization of functional networks. These differences likely underlie sensory dysregulation and behavioral difficulties in prenatal alcohol exposure.

Visual search efficiency and functional visual cortical size in children with and without dyslexia

Dyslexia is characterised by poor reading ability. Its aetiology is probably multifactorial, with abnormal visual processing playing an important role. Among adults with normal reading ability, there is a larger representation of central visual field in the primary visual cortex (V1) in those with more efficient visuospatial attention. In this study, we tested the hypothesis that poor reading ability in school-aged children (17 children with dyslexia, 14 control children with normal reading ability) is associated with deficits in visuospatial attention using a visual search task. We corroborated the psychophysical findings with neuroimaging, by measuring the functional size of V1 in response to a central 12° visual stimulus. Consistent with other literature, visual search was impaired and less efficient in the dyslexic children, particularly with more distractor elements in the search array (p = 0.04). We also found atypical interhemispheric asymmetry in functional V1 size in the dyslexia group (p = 0.02). Reading impaired children showed poorer visual search efficiency (p = 0.01), needing more time per unit distractor (higher ms/item). Reading ability was also correlated with V1 size asymmetry (p = 0.03), such that poorer readers showed less left hemisphere bias relative to the right hemisphere. Our findings support the view that dyslexic children have abnormal visuospatial attention and interhemispheric V1 asymmetry, relative to chronological age-matched peers, and that these factors may contribute to inter-individual variation in reading performance in children.

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.

Aberrant Brain Network Integration and Segregation in Diabetic Peripheral Neuropathy Revealed by Structural Connectomics

Diabetic peripheral neuropathy (DPN) is one of the most common forms of peripheral neuropathy, and its incidence has been increasing. Mounting evidence has shown that patients with DPN have been associated with widespread alterations in the structure, function and connectivity of the brain, suggesting possible alterations in large-scale brain networks. Using structural covariance networks as well as advanced graph-theory-based computational approaches, we investigated the topological abnormalities of large-scale brain networks for a relatively large sample of patients with DPN (N = 67) compared to matched healthy controls (HCs; N = 88). Compared with HCs, the structural covariance networks of patients with DPN showed an increased characteristic path length, clustering coefficient, sigma, transitivity, and modularity, suggestive of inefficient global integration and increased local segregation. These findings may improve our understanding of the pathophysiological mechanisms underlying alterations in the central nervous system of patients with DPN from the perspective of large-scale structural brain networks.

Shared Neural Substrates Underlying Reading and Visual Matching: A Longitudinal Investigation

The role of visual skills in reading acquisition has long been debated and whether there is shared neurobiological basis between visual skills and reading is not clear. This study investigated the relationship between Visual Matching and reading and their shared neuroanatomical basis. Two hundred and ninety-three typically developing Mandarin-speaking children were followed in a longitudinal study from ages 4 to 11 years old. A subsample of 79 children was further followed up at 14 years old when the MRI data were collected. Results showed that the development of Visual Matching from ages 6 to 8 predicted reading accuracy at age 11. In addition, both the development of Visual Matching and reading accuracy were associated with cortical surface area of a cluster located in fusiform gyrus. These findings suggested that the mapping from visual codes to phonological codes is important in learning to read and that left fusiform gyrus provided neural basis for such mapping. Implications of these findings in light of a new approach toward the neurocognitive mechanisms underlying reading development are discussed.

Irregular structural networks of gray matter in patients with type 2 diabetes mellitus

Type 2 diabetes mellitus (T2DM) induces dementia and cognitive decrements indicating the impairment of the central nervous system. While there is evidence showing abnormalities in white-matter structural networks in T2DM, the topological features of gray matter are still unknown. The study enrolled 30 right-handed T2DM patients and 20 healthy control subjects with matched age, gender, handedness, and education. Graph theoretical analysis of magnetic resonance imaging on gray matter volume was conducted to explore large-scale structural networks of brain. Although retaining small-worldness characteristics, the structural networks of grey matter in the T2DM group exhibited an increased clustering coefficient, prolonged characteristic path, decreased global efficiency, and more vulnerability to random failures or targeted attacks compared with controls. Additionally, the degree of structural networks in both T2DM and control groups was distributed exponentially in truncated power law. Our findings suggest that T2DM disturbed the overall topological features of gray matter networks, which provides a novel insight into the neurobiological mechanisms accounting for the cognitive impairment of T2DM patients.

Reproducibility of graph measures at the subject level using resting-state fMRI

INTRODUCTION

Graph metrics have been proposed as potential biomarkers for diagnosis in clinical work. However, before it can be applied in a clinical setting, their reproducibility should be evaluated.

METHODS

This study systematically investigated the effect of two denoising pipelines and different whole-brain network constructions on reproducibility of subject-specific graph measures. We used the multi-session fMRI dataset from the Brain Genomics Superstruct Project consisting of 69 healthy young adults.

RESULTS

In binary networks, the test-retest variability for global measures was large at low density irrespective of the denoising strategy or the type of correlation. Weighted networks showed very low test-retest values (and thus a good reproducibility) for global graph measures irrespective of the strategy used. Comparing the test-retest values for different strategies, there were significant main effects of the type of correlation (Pearson correlation vs. partial correlation), the (partial) correlation value (absolute vs. positive vs. negative), and weight calculation (based on the raw (partial) correlation values vs. based on transformed Z-values). There was also a significant interaction effect between type of correlation and weight calculation. Similarly as for the binary networks, there was no main effect of the denoising pipeline.

CONCLUSION

Our results demonstrated that normalized global graph measures based on a weighted network using the absolute (partial) correlation as weight were reproducible. The denoising pipeline and the granularity of the whole-brain parcellation used to define the nodes were not critical for the reproducibility of normalized graph measures.

Structural brain network development in children following prenatal methamphetamine exposure

Brain imaging studies in children with prenatal methamphetamine exposure (PME) suggest structural and functional alterations of striatal, frontal, parietal, and limbic regions. However, no longitudinal studies have investigated changes in structural connectivity during the first 2 years of formal schooling. The aim of this study was to explore the effects of PME on structural connectivity of brain networks in children over the critical first 2 years of formal schooling when foundational learning takes place. Networks are expected to gradually increase in global connectedness while segregating into defined systems. Graph theoretical analysis was used to investigate changes in structural connectivity at age 6 and 8 years in children with and without PME. While healthy control children showed increased connectivity in frontal and limbic hubs over time, children with PME showed increased connectivity in the superior parietal cortex and striatum in their global network. Furthermore, compared to control children, those with PME were characterized by less change in segregation of structural networks over time. These findings are consistent with previous work on regions implicated in children with PME, but they additionally demonstrate alterations in structural connectivity between regions that underlie primary cognitive, behavioral, and emotional development. Understanding patterns of network development during critical periods in at-risk children may inform strategies for supporting this group of children in these developmental tasks important for lifelong brain health and development.

Putative protective neural mechanisms in prereaders with a family history of dyslexia who subsequently develop typical reading skills

Developmental dyslexia affects 40-60% of children with a familial risk (FHD+) compared to a general prevalence of 5-10%. Despite the increased risk, about half of FHD+ children develop typical reading abilities (FHD+Typical). Yet the underlying neural characteristics of favorable reading outcomes in at-risk children remain unknown. Utilizing a retrospective, longitudinal approach, this study examined whether putative protective neural mechanisms can be observed in FHD+Typical at the prereading stage. Functional and structural brain characteristics were examined in 47 FHD+ prereaders who subsequently developed typical (n = 35) or impaired (n = 12) reading abilities and 34 controls (FHD-Typical). Searchlight-based multivariate pattern analyses identified distinct activation patterns during phonological processing between FHD+Typical and FHD-Typical in right inferior frontal gyrus (RIFG) and left temporo-parietal cortex (LTPC) regions. Follow-up analyses on group-specific classification patterns demonstrated LTPC hypoactivation in FHD+Typical compared to FHD-Typical, suggesting this neural characteristic as an FHD+ phenotype. In contrast, RIFG showed hyperactivation in FHD+Typical than FHD-Typical, and its activation pattern was positively correlated with subsequent reading abilities in FHD+ but not controls (FHD-Typical). RIFG hyperactivation in FHD+Typical was further associated with increased interhemispheric functional and structural connectivity. These results suggest that some protective neural mechanisms are already established in FHD+Typical prereaders supporting their typical reading development.

Impaired Topological Properties of Gray Matter Structural Covariance Network in Epilepsy Children With Generalized Tonic-Clonic Seizures: A Graph Theoretical Analysis

Modern network science has provided exciting new opportunities for understanding the human brain as a complex network of interacting regions. The improved knowledge of human brain network architecture has made it possible for clinicians to detect the network changes in neurological diseases. Generalized tonic–clonic seizure (GTCS) is a subtype of epilepsy characterized by generalized spike-wave discharge involving the bilateral hemispheres during seizure. Network researches in adults with GTCS exhibited that GTCS can be conceptualized as a network disorder. However, the overall organization of the brain structural covariance network in children with GTCS remains largely unclear. Here, we used a graph theory method to assess the gray matter structural covariance network organization of 14 pediatric patients diagnosed with GTCS and 29 healthy control children. The group differences in regional and global topological properties were investigated. Results revealed significant changes in nodal betweenness locating in brain regions known to be abnormal in GTCS (the right thalamus, bilateral temporal pole, and some regions of default mode network). The network hub analysis results were in accordance with the regional betweenness, which presented a disrupted regional topology of structural covariance network in children with GTCS. To our knowledge, the present study is the first work reporting the changes of structural topological properties in children with GTCS. The findings contribute new insights into the understanding of the neural mechanisms underlying GTCS and highlight critical regions for future neuroimaging research in children with GTCS.

Disrupted Structural Brain Network Organization Behind Depressive Symptoms in Major Depressive Disorder

Major depressive disorder (MDD) is a severe and devastating condition. However, the anatomical basis behind the affective symptoms, cognitive symptoms, and somatic-vegetative symptoms of MDD is still unknown. To explore the mechanism behind the depressive symptoms in MDD, we used diffusion tensor imaging (DTI)-based structural brain connectivity analysis to investigate the network difference between MDD patients and healthy controls (CN), and to explore the association between network metrics and patients' clinical symptoms. Twenty-six patients with MDD and 25 CN were included. A baseline 24-item Hamilton rating scale for depression (HAMD-24) score ≥ 21 and seven factors (anxiety/somatization, weight loss, cognitive disturbance, diurnal variation, retardation, sleep disturbance, hopelessness) scores were assessed. When compared with healthy subjects, significantly higher characteristic path length and clustering coefficient as well as significantly lower network efficiencies were observed in patients with MDD. Furthermore, MDD patients demonstrated significantly lower nodal degree and nodal efficiency in multiple brain regions including superior frontal gyrus (SFG), supplementary motor area (SMA), calcarine fissure, middle temporal gyrus (MTG), and inferior temporal gyrus (ITG). We also found that the characteristic path length of MDD patients was associated with weight loss. Moreover, significantly lower global efficiency of MDD patients was correlated with higher total HAMD score, anxiety somatization, and cognitive disturbance. The nodal degree in SFG was also found to be negatively associated with disease duration. In conclusion, our results demonstrated that MDD patients had impaired structural network features compared to CN, and disruption of optimal network architecture might be the mechanism behind the depressive symptoms and emotion disturbance in MDD patients.

Structural brain network fingerprints of focal dystonia

Background:

Focal dystonias are severe and disabling movement disorders of a still unclear origin. The structural brain networks associated with focal dystonia have not been well characterized. Here, we investigated structural brain network fingerprints in patients with blepharospasm (BSP) compared with those with hemifacial spasm (HFS), and healthy controls (HC). The patients were also examined following treatment with botulinum neurotoxin (BoNT).

Methods:

This study included matched groups of 13 BSP patients, 13 HFS patients, and 13 HC. We measured patients using structural-magnetic resonance imaging (MRI) at baseline and after one month BoNT treatment, at time points of maximal and minimal clinical symptom representation, and HC at baseline. Group regional cross-correlation matrices calculated based on grey matter volume were included in graph-based network analysis. We used these to quantify global network measures of segregation and integration, and also looked at local connectivity properties of different brain regions.

Results:

The networks in patients with BSP were more segregated than in patients with HFS and HC (p < 0.001). BSP patients had increased connectivity in frontal and temporal cortices, including sensorimotor cortex, and reduced connectivity in the cerebellum, relative to both HFS patients and HC (p < 0.05). Compared with HC, HFS patients showed increased connectivity in temporal and parietal cortices and a decreased connectivity in the frontal cortex (p < 0.05). In BSP patients, the connectivity of the frontal cortex diminished after BoNT treatment (p < 0.05). In contrast, HFS patients showed increased connectivity in the temporal cortex and reduced connectivity in cerebellum after BoNT treatment (p < 0.05).

Conclusions:

Our results show that BSP patients display alterations in both segregation and integration in the brain at the network level. The regional differences identified in the sensorimotor cortex and cerebellum of these patients may play a role in the pathophysiology of focal dystonia. Moreover, symptomatic reduction of hyperkinesia by BoNT treatment was associated with different brain network fingerprints in both BSP and HFS patients.

Atypical gray matter in children with dyslexia before the onset of reading instruction

Many studies have focused on neuroanatomical anomalies in dyslexia, yet primarily in school-aged children and adults. In the present study, we investigated gray matter surface area and cortical thickness at the pre-reading stage in a cohort of 54 children, 31 with a family risk for dyslexia and 23 without a family risk for dyslexia, of whom 16 children developed dyslexia. Surface-based analyses in the core regions of the reading network in the left hemisphere and in the corresponding right hemispheric regions were performed in FreeSurfer. Results revealed that pre-readers who develop dyslexia show reduced surface area in bilateral fusiform gyri. In addition, anomalies related to a family risk for dyslexia, irrespectively of later reading ability, were observed in the area of the bilateral inferior and middle temporal gyri. Differences were apparent in surface area, as opposed to cortical thickness. Results indicate that the neuroanatomical anomalies, since they are observed in the pre-reading phase, are not the consequence of impoverished reading experience.

White matter network connectivity deficits in developmental dyslexia

A number of studies have shown an abnormal connectivity of certain white matter pathways in developmental dyslexia, as well as correlations between these white matter pathways and behavioral deficits. However, whether developmental dyslexia presents broader white matter network connectivity disruption is currently unknown. The present study reconstructed white matter networks for 26 dyslexic children (11.61 ± 1.31 years) and 31 age-matched controls (11.49 ± 1.36 years) using constrained spherical deconvolution tractography. Network-based statistics (NBS) analysis was performed to identify network connectivity deficits in dyslexic individuals. Network topological features were measured based on graph theory to examine whether these parameters correlate with literacy skills, and whether they explain additional variance over previously established white matter connectivity abnormalities in dyslexic children. The NBS analysis identified a network connecting the left-occipital-temporal cortex and temporo-parietal cortex that had decreased streamlines in dyslexic children. Four network topological parameters (clustering coefficient, local efficiency, transitivity, and global efficiency) were positively correlated with literacy skills of dyslexic children, and explained a substantial proportion of additional variance in literacy skills beyond connectivity measures of white matter pathways. This study for the first time reports a disconnection in a local subnetwork in the left hemisphere in dyslexia and shows that the global white matter network topological properties contribute to reduced literacy skills in dyslexic children.

Structural covariance and cortical reorganisation in schizophrenia: a MRI-based morphometric study

BACKGROUND

In patients with schizophrenia, distributed abnormalities are observed in grey matter volume. A recent hypothesis posits that these distributed changes are indicative of a plastic reorganisation process occurring in response to a functional defect in neuronal information transmission. We investigated the structural covariance across various brain regions in early-stage schizophrenia to determine if indeed the observed patterns of volumetric loss conform to a coordinated pattern of structural reorganisation.

METHODS

Structural magnetic resonance imaging scans were obtained from 40 healthy adults and 41 age, gender and parental socioeconomic status matched patients with schizophrenia. Volumes of grey matter tissue were estimated at the regional level across 90 atlas-based parcellations. Group-level structural covariance was studied using a graph theoretical framework.

RESULTS

Patients had distributed reduction in grey matter volume, with high degree of localised covariance (clustering) compared with controls. Patients with schizophrenia had reduced centrality of anterior cingulate and insula but increased centrality of the fusiform cortex, compared with controls. Simulating targeted removal of highly central nodes resulted in significant loss of the overall covariance patterns in patients compared with controls.

CONCLUSION

Regional volumetric deficits in schizophrenia are not a result of random, mutually independent processes. Our observations support the occurrence of a spatially interconnected reorganisation with the systematic de-escalation of conventional 'hub' regions. This raises the question of whether the morphological architecture in schizophrenia is primed for compensatory functions, albeit with a high risk of inefficiency.

Abnormal topological organization of structural covariance networks in amyotrophic lateral sclerosis

Neuroimaging studies of patients with amyotrophic lateral sclerosis (ALS) have shown widespread alterations in structure, function, and connectivity in both motor and non-motor brain regions, suggesting multi-systemic neurobiological abnormalities that might impact large-scale brain networks. Here, we examined the alterations in the topological organization of structural covariance networks of ALS patients (N = 60) compared with normal controls (N = 60). We found that structural covariance networks of ALS patients showed a consistent rearrangement towards a regularized architecture evidenced by increased path length, clustering coefficient, small-world index, and modularity, as well as decreased global efficiency, suggesting inefficient global integration and increased local segregation. Locally, ALS patients showed decreased nodal degree and betweenness in the gyrus rectus and/or Heschl's gyrus, and increased betweenness in the supplementary motor area, triangular part of the inferior frontal gyrus, supramarginal gyrus and posterior cingulate cortex. In addition, we identified a different number and distribution of hubs in ALS patients, showing more frontal and subcortical hubs than in normal controls. In conclusion, we reveal abnormal topological organization of structural covariance networks in ALS patients, and provide network-level evidence for the concept that ALS is a multisystem disorder with a cerebral involvement extending beyond the motor areas.

Abnormal Gray Matter Structural Networks in Idiopathic Normal Pressure Hydrocephalus

Purpose: Idiopathic normal pressure hydrocephalus (iNPH) is known as a treatable form of dementia. Network analysis is emerging as a useful method to study neurological disorder diseases. No study has examined changes of structural brain networks of iNPH patients. We aimed to investigate alterations in the gray matter (GM) structural network of iNPH patients compared with normal elderly volunteers.

Materials and Methods: Structural networks were reconstructed using covariance between regional GM volumes extracted from three-dimensional T1-weighted images of 29 possible iNPH patients and 30 demographically similar normal-control (NC) participants and compared with each other.

Results: Global network modularity was significantly larger in the iNPH network (P < 0.05). Global network measures were not significantly different between the two networks (P > 0.05). Regional network analysis demonstrated eight nodes with significantly decreased betweenness located in the bilateral frontal, right temporal, right insula and right posterior cingulate regions, whereas only the left anterior cingulate was detected with significantly larger betweenness. The hubs of the iNPH network were mostly located in temporal areas and the limbic lobe, those of the NC network were mainly located in frontal areas.

Conclusions: Network analysis was a promising method to study iNPH. Increased network modularity of the iNPH group was detected here, and modularity analysis should be paid much attention to explore the biomarker to select shunting-responsive patients.

Processing of structural neuroimaging data in young children: Bridging the gap between current practice and state-of-the-art methods

The structure of the brain is subject to very rapid developmental changes during early childhood. Pediatric studies based on Magnetic Resonance Imaging (MRI) over this age range have recently become more frequent, with the advantage of providing in vivo and non-invasive high-resolution images of the developing brain, toward understanding typical and atypical trajectories. However, it has also been demonstrated that application of currently standard MRI processing methods that have been developed with datasets from adults may not be appropriate for use with pediatric datasets. In this review, we examine the approaches currently used in MRI studies involving young children, including an overview of the rationale for new MRI processing methods that have been designed specifically for pediatric investigations. These methods are mainly related to the use of age-specific or 4D brain atlases, improved methods for quantifying and optimizing image quality, and provision for registration of developmental data obtained with longitudinal designs. The overall goal is to raise awareness of the existence of these methods and the possibilities for implementing them in developmental neuroimaging studies.

Neural Correlates of Oral Word Reading, Silent Reading Comprehension, and Cognitive Subcomponents

The ability to read is essential for cognitive development. To deepen our understanding of reading acquisition, we explored the neuroanatomical correlates (cortical thickness (CT)) of word reading fluency and sentence comprehension efficiency in Chinese with a group of typically developing children (N = 21; 12 females and 9 males; age range 10.7-12.3 years). Then, we investigated the relationship between the CT of reading-defined regions and the cognitive subcomponents of reading to determine whether our study lends support to the multi-component model. The results demonstrated that children's performance on oral word reading was positively correlated with CT in the left superior temporal gyrus (LSTG), inferior temporal gyrus (LITG), supramarginal gyrus (LSMG) and right superior temporal gyrus (RSTG). Moreover, CT in the LSTG, LSMG and LITG uniquely predicted children's phonetic representation, phonological awareness, and orthography-phonology mapping skills, respectively. By contrast, children's performance on sentence reading comprehension was positively correlated with CT in the left parahippocampus (LPHP) and right calcarine fissure (RV1). As for the subcomponents of reading, CT in the LPHP was exclusively correlated with morphological awareness, whereas CT in the RV1 was correlated with orthography-semantic mapping. Taken together, these findings indicate that the reading network of typically developing children consists of multiple subdivisions, thus providing neuroanatomical evidence in support of the multi-componential view of reading.

Atypical Structural Asymmetry of the Planum Temporale is Related to Family History of Dyslexia

Research on the neural correlates of developmental dyslexia indicates atypical anatomical lateralization of the planum temporale, a higher-order cortical auditory region. Yet whether this atypical lateralization precedes reading acquisition and is related to a familial risk for dyslexia is not currently known. In this study, we address these questions in 2 separate cohorts of young children and adolescents with and without a familial risk for dyslexia. Planum temporale surface area was manually labeled bilaterally, on the T1-weighted MR brain images of 54 pre-readers (mean age: 6.2 years, SD: 3.2 months; 33 males) and 28 adolescents (mean age: 14.7 years, SD: 3.3 months; 11 males). Half of the pre-readers and adolescents had a familial risk for dyslexia. In both pre-readers and adolescents, group comparisons of left and right planum temporale surface area showed a significant interaction between hemisphere and family history of dyslexia, with participants who had no family risk for dyslexia showing greater leftward asymmetry of the planum temporale. This effect was confirmed when analyses were restricted to normal reading participants. Altered planum temporale asymmetry thus seems to be related to family history of dyslexia.

Brain basis of cognitive resilience: Prefrontal cortex predicts better reading comprehension in relation to decoding

OBJECTIVE

The ultimate goal of reading is to understand written text. To accomplish this, children must first master decoding, the ability to translate printed words into sounds. Although decoding and reading comprehension are highly interdependent, some children struggle to decode but comprehend well, whereas others with good decoding skills fail to comprehend. The neural basis underlying individual differences in this discrepancy between decoding and comprehension abilities is virtually unknown.

METHODS

We investigated the neural basis underlying reading discrepancy, defined as the difference between reading comprehension and decoding skills, in a three-part study: 1) The neuroanatomical basis of reading discrepancy in a cross-sectional sample of school-age children with a wide range of reading abilities (Experiment-1; n = 55); 2) Whether a discrepancy-related neural signature is present in beginning readers and predictive of future discrepancy (Experiment-2; n = 43); and 3) Whether discrepancy-related regions are part of a domain-general or a language specialized network, utilizing the 1000 Functional Connectome data and large-scale reverse inference from Neurosynth.org (Experiment-3).

RESULTS

Results converged onto the left dorsolateral prefrontal cortex (DLPFC), as related to having discrepantly higher reading comprehension relative to decoding ability. Increased gray matter volume (GMV) was associated with greater discrepancy (Experiment-1). Region-of-interest (ROI) analyses based on the left DLPFC cluster identified in Experiment-1 revealed that regional GMV within this ROI in beginning readers predicted discrepancy three years later (Experiment-2). This region was associated with the fronto-parietal network that is considered fundamental for working memory and cognitive control (Experiment-3).

INTERPRETATION

Processes related to the prefrontal cortex might be linked to reading discrepancy. The findings may be important for understanding cognitive resilience, which we operationalize as those individuals with greater higher-order reading skills such as reading comprehension compared to lower-order reading skills such as decoding skills. Our study provides insights into reading development, existing theories of reading, and cognitive processes that are potentially significant to a wide range of reading disorders.

Brain's functional network clustering coefficient changes in response to instruction (RTI) in students with and without reading disabilities: Multi-leveled reading brain's RTI

In students in grades 4 to 9 (22 males, 20 females), two reading disability groups-dyslexia (n = 20) or oral and written language learning disability (OWL LD) (n = 6)-were compared to each other and two kinds of control groups-typical readers (n = 6) or dysgraphia (n = 10) on word reading/spelling skills and fMRI imaging before and after completing 18 computerized reading lessons. Mixed ANOVAs showed significant time effects on repeated measures within participants and between groups effects on three behavioral markers of reading disabilities-word reading/spelling: All groups improved on the three behavioral measures, but those without disabilities remained higher than those with reading disabilities. On fMRI reading tasks, analyzed for graph theory derived clustering coefficients within a neural network involved in cognitive control functions, on a word level task the time × group interaction was significant in right medial cingulate; on a syntax level task the time × group interaction was significant in left superior frontal and left inferior frontal gyri; and on a multi-sentence text level task the time × group interaction was significant in right middle frontal gyrus. Three white matter-gray matter correlations became significant only after reading instruction: axial diffusivity in left superior frontal region with right inferior frontal gyrus during word reading judgments; mean diffusivity in left superior corona radiata with left middle frontal gyrus during sentence reading judgments; and mean diffusivity in left anterior corona radiata with right middle frontal gyrus during multi-sentence reading judgments. Significance of results for behavioral and brain response to reading instruction (RTI) is discussed.

Graph theory analysis of cortical thickness networks in adolescents with d-transposition of the great arteries

Objective

Adolescents with d-transposition of the great arteries (d-TGA) who had the arterial switch operation in infancy have been found to have structural brain differences compared to healthy controls. We used cortical thickness measurements obtained from structural brain MRI to determine group differences in global brain organization using a graph theoretical approach.

Methods

Ninety-two d-TGA subjects and 49 controls were scanned using one of two identical 1.5-Tesla MRI systems. Mean cortical thickness was obtained from 34 regions per hemisphere using Freesurfer. A linear model was used for each brain region to adjust for subject age, sex, and scanning location. Structural connectivity for each group was inferred based on the presence of high inter-regional correlations of the linear model residuals, and binary connectivity matrices were created by thresholding over a range of correlation values for each group. Graph theory analysis was performed using packages in R. Permutation tests were performed to determine significance of between-group differences in global network measures.

Results

Within-group connectivity patterns were qualitatively different between groups. At lower network densities, controls had significantly more long-range connections. The location and number of hub regions differed between groups: controls had a greater number of hubs at most network densities. The control network had a significant rightward asymmetry compared to the d-TGA group at all network densities.

Conclusions

Using graph theory analysis of cortical thickness correlations, we found differences in brain structural network organization among d-TGA adolescents compared to controls. These may be related to the white matter and gray matter differences previously found in this cohort, and in turn may be related to the cognitive deficits this cohort presents.

Altered Integration of Structural Covariance Networks in Young Children With Type 1 Diabetes

Type 1 diabetes mellitus (T1D), one of the most frequent chronic diseases in children, is associated with glucose dysregulation that contributes to an increased risk for neurocognitive deficits. While there is a bulk of evidence regarding neurocognitive deficits in adults with T1D, little is known about how early-onset T1D affects neural networks in young children. Recent data demonstrated widespread alterations in regional gray matter and white matter associated with T1D in young children. These widespread neuroanatomical changes might impact the organization of large-scale brain networks. In the present study, we applied graph-theoretical analysis to test whether the organization of structural covariance networks in the brain for a cohort of young children with T1D (N = 141) is altered compared to healthy controls (HC; N = 69). While the networks in both groups followed a small world organization-an architecture that is simultaneously highly segregated and integrated-the T1D network showed significantly longer path length compared with HC, suggesting reduced global integration of brain networks in young children with T1D. In addition, network robustness analysis revealed that the T1D network model showed more vulnerability to neural insult compared with HC. These results suggest that early-onset T1D negatively impacts the global organization of structural covariance networks and influences the trajectory of brain development in childhood. This is the first study to examine structural covariance networks in young children with T1D. Improving glycemic control for young children with T1D might help prevent alterations in brain networks in this population. Hum Brain Mapp 37:4034-4046, 2016. © 2016 Wiley Periodicals, Inc.

Neurobiological Bases of Reading Disorder Part II: The Importance of Developmental Considerations in Typical and Atypical Reading

Decoding-based reading disorder (RD; aka developmental dyslexia) is one of the most common neurodevelopmental disorders, affecting approximately 5-10% of school-aged children across languages. Even though neuroimaging studies suggest an impairment of the left reading network in RD, the onset of this deficit and its developmental course, which may include constancy and change, is largely unknown. There is now growing evidence that the recruitment of brain networks underlying perceptual, cognitive and linguistic processes relevant to reading acquisition varies with age. These age-dependent changes may in turn impact the neurocognitive characteristics of RD observed at specific developmental stages. Here we synthesize findings from functional and structural magnetic resonance imaging (MRI) studies to increase our understanding of the developmental time course of the neural bases underlying (a)typical reading. We first provide an overview of the brain bases of typical and atypical (impaired) reading. Next we describe how the understanding of RD can be deepened through scientific attention to age effects, for example, by integrating findings from cross-sectional studies of RD at various ages. Finally, we accent findings from extant longitudinal studies that directly examine developmental reading trajectories beginning in the preliterate stage at both group and individual levels. Although science is at the very early stage of understanding developmental aspects of neural deficits in RD, evidence to date characterizes RD by atypical brain maturation. We know that reading impairment may adversely impact multiple life domains such as academic achievement and social relationships, and unfortunately, that these negative outcomes can persist and compound into adulthood. We contend that exploring the developmental trajectories of RD will contribute to a greater understanding of how neural systems support reading acquisition. Further, we propose and cite evidence that the etiology of RD can be better investigated by distinguishing primary deficits from secondary impairments unfolding along development. These exciting and modern investigatory efforts can also indirectly contribute to a centered practice of early and accurate identification and optimal intervention to support the development of foundational pre-literacy skills and fluent reading. In sum, integrating a developmental understanding into the science and practice of reading acquisition and intervention is both possible and necessary.

White matter pathways mediate parental effects on children's reading precursors

Previous studies have shown that the link between parental and offspring's reading is mediated by the cognitive system of the offspring, yet information about the mediating role of the neurobiological system is missing. This family study includes cognitive and diffusion MRI (dMRI) data collected in 71 pre-readers as well as parental reading and environmental data. Using sequential path analyses, which take into account the interrelationships between the different components, we observed mediating effects of the neurobiological system. More specifically, fathers' reading skills predicted reading of the child by operating through a child's left ventral white matter pathway. For mothers no clear mediating role of the neural system was observed. Given that our study involves children who have not yet learned to read and that environmental measures were taken into account, the paternal effect on a child's white matter pathway is unlikely to be only driven by environmental factors. Future intergenerational studies focusing on the genetic, neurobiological and cognitive level of parents and offspring will provide more insight in the relative contribution of parental environment and genes.

Genetic transmission of reading ability

Reading is the processing of written language. Family resemblance for reading (dis)ability might be due to transmission of a genetic liability or due to family environment, including cultural transmission from parents to offspring. Familial-risk studies exploring neurobehavioral precursors for dyslexia and twin studies can only speak to some of these issues, but a combined twin-family study can resolve the nature of the transmitted risk. Word-reading fluency scores of 1100 participants from 431 families (with twins, siblings and their parents) were analyzed to estimate genetic and environmental sources of variance, and to test the presence of assortative mating and cultural transmission. Results show that variation in reading ability is mainly caused by additive and non-additive genetic factors (64%). The substantial assortative mating (r_{father-mother}=0.38) has scientific and clinical implications. We conclude that parents and offspring tend to resemble each other for genetic reasons, and not due to cultural transmission.

The Effects of Long-term Abacus Training on Topological Properties of Brain Functional Networks

Previous studies in the field of abacus-based mental calculation (AMC) training have shown that this training has the potential to enhance a wide variety of cognitive abilities. It can also generate specific changes in brain structure and function. However, there is lack of studies investigating the impact of AMC training on the characteristics of brain networks. In this study, utilizing graph-based network analysis, we compared topological properties of brain functional networks between an AMC group and a matched control group. Relative to the control group, the AMC group exhibited higher nodal degrees in bilateral calcarine sulcus and increased local efficiency in bilateral superior occipital gyrus and right cuneus. The AMC group also showed higher nodal local efficiency in right fusiform gyrus, which was associated with better math ability. However, no relationship was significant in the control group. These findings provide evidence that long-term AMC training may improve information processing efficiency in visual-spatial related regions, which extend our understanding of training plasticity at the brain network level.

Neuroanatomy of developmental dyslexia: Pitfalls and promise

Investigations into the neuroanatomical bases of developmental dyslexia have now spanned more than 40 years, starting with the post-mortem examination of a few individual brains in the 60s and 70s, and exploding in the 90s with the widespread use of MRI. The time is now ripe to reappraise the considerable amount of data gathered with MRI using different types of sequences (T1, diffusion, spectroscopy) and analysed using different methods (manual, voxel-based or surface-based morphometry, fractional anisotropy and tractography, multivariate analyses…). While selective reviews of mostly small-scale studies seem to provide a coherent view of the brain disruptions that are typical of dyslexia, involving left perisylvian and occipito-temporal regions, we argue that this view may be deceptive and that meta-analyses and large-scale studies rather highlight many inconsistencies and limitations. We discuss problems inherent to small sample size as well as methodological difficulties that still undermine the discovery of reliable neuroanatomical bases of dyslexia, and we outline some recommendations to further improve this research area.

Altered Brain Network Segregation in Fragile X Syndrome Revealed by Structural Connectomics

Fragile X syndrome (FXS), the most common inherited cause of intellectual disability and autism spectrum disorder, is associated with significant behavioral, social, and neurocognitive deficits. Understanding structural brain network topology in FXS provides an important link between neurobiological and behavioral/cognitive symptoms of this disorder. We investigated the connectome via whole-brain structural networks created from group-level morphological correlations. Participants included 100 individuals: 50 with FXS and 50 with typical development, age 11-23 years. Results indicated alterations in topological properties of structural brain networks in individuals with FXS. Significantly reduced small-world index indicates a shift in the balance between network segregation and integration and significantly reduced clustering coefficient suggests that reduced local segregation shifted this balance. Caudate and amygdala were less interactive in the FXS network further highlighting the importance of subcortical region alterations in the neurobiological signature of FXS. Modularity analysis indicates that FXS and typically developing groups' networks decompose into different sets of interconnected sub networks, potentially indicative of aberrant local interconnectivity in individuals with FXS. These findings advance our understanding of the effects of fragile X mental retardation protein on large-scale brain networks and could be used to develop a connectome-level biological signature for FXS.