White matter microstructure correlates of mathematical giftedness and intelligence quotient

Differences in educational opportunity predict white matter development

Coarse measures of socioeconomic status, such as parental income or parental education, have been linked to differences in white matter development. However, these measures do not provide insight into specific aspects of an individual's environment and how they relate to brain development. On the other hand, educational intervention studies have shown that changes in an individual's educational context can drive measurable changes in their white matter. These studies, however, rarely consider socioeconomic factors in their results. In the present study, we examined the unique relationship between educational opportunity and white matter development, when controlling other known socioeconomic factors. To explore this question, we leveraged the rich demographic and neuroimaging data available in the ABCD study, as well the unique data-crosswalk between ABCD and the Stanford Education Data Archive (SEDA). We find that educational opportunity is related to accelerated white matter development, even when accounting for other socioeconomic factors, and that this relationship is most pronounced in white matter tracts associated with academic skills. These results suggest that the school a child attends has a measurable relationship with brain development for years to come.

Structural-functional brain network coupling predicts human cognitive ability

Individual differences in general cognitive ability (GCA) have a biological basis within the structure and function of the human brain. Network neuroscience investigations revealed neural correlates of GCA in structural as well as in functional brain networks. However, whether the relationship between structural and functional networks, the structural-functional brain network coupling (SC-FC coupling), is related to individual differences in GCA remains an open question. We used data from 1030 adults of the Human Connectome Project, derived structural connectivity from diffusion weighted imaging, functional connectivity from resting-state fMRI, and assessed GCA as a latent g-factor from 12 cognitive tasks. Two similarity measures and six communication measures were used to model possible functional interactions arising from structural brain networks. SC-FC coupling was estimated as the degree to which these measures align with the actual functional connectivity, providing insights into different neural communication strategies. At the whole-brain level, higher GCA was associated with higher SC-FC coupling, but only when considering path transitivity as neural communication strategy. Taking region-specific variations in the SC-FC coupling strategy into account and differentiating between positive and negative associations with GCA, allows for prediction of individual cognitive ability scores in a cross-validated prediction framework (correlation between predicted and observed scores: r = 0.25, p < .001). The same model also predicts GCA scores in a completely independent sample (N = 567, r = 0.19, p < .001). Our results propose structural-functional brain network coupling as a neurobiological correlate of GCA and suggest brain region-specific coupling strategies as neural basis of efficient information processing predictive of cognitive ability.

From gifted to high potential and twice exceptional: A state-of-the-art meta-review

Despite the abundant literature on intelligence and high potential individuals, there is still a lack of international consensus on the terminology and clinical characteristics associated to this population. It has been argued that unstandardized use of diagnosis tools and research methods make comparisons and interpretations of scientific and epidemiological evidence difficult in this field. If multiple cognitive and psychological models have attempted to explain the mechanisms underlying high potentiality, there is a need to confront new scientific evidence with the old, to uproot a global understanding of what constitutes the neurocognitive profile of high-potential in gifted individuals. Another particularly relevant aspect of applied research on high potentiality concerns the challenges faced by individuals referred to as "twice exceptional" in the field of education and in their socio-affective life. Some individuals have demonstrated high forms of intelligence together with learning, affective or neurodevelopmental disorders posing the question as to whether compensating or exacerbating psycho-cognitive mechanisms might underlie their observed behavior. Elucidating same will prove relevant to questions concerning the possible need for differential diagnosis tools, specialized educational and clinical support. A meta-review of the latest findings from neuroscience to developmental psychology, might help in the conception and reviewing of intervention strategies.

Abnormal microstructure of corpus callosum in children with primary nocturnal enuresis: a DTI study

Primary nocturnal enuresis (PNE) is a common childhood disorder with abnormal sleep or arousal. The corpus callosum (CC) continues to develop into adulthood and plays an important role in sleep arousal. This study aimed to evaluate the microstructure of the CC in children with PNE. Diffusion tensor imaging (DTI) indices were extracted throughout the CC and its seven subregions were compared between the children with PNE and healthy children (HC). The correlation between abnormal DTI indices of the CC and cognitive condition was also tested. Compared to HC, decreased fiber number (NF) (F = 8.492, PFDR = 0.032) and fractional anisotropy (FA) value (F = 8.442, PFDR = 0.040) were found in the posterior midbody of the CC, increased RD was found in the posterior midbody (F = 6.888, PFDR = 0.040) and isthmus (F = 7.967, PFDR = 0.040) in children with PNE. The reduction of FA value was more obvious in boys than girls with PNE. In children with PNE, there was a significant positive correlation between the NF of the posterior midbody and full IQ (r = 0.322, P = 0.025) and between the FA value and the general knowledge memory (r = 0.293, P = 0.043). This study provides imaging evidence for abnormalities in the microstructure of the CC in children with PNE, especially in male PNE, which might affect the children's cognitive performance.

The effects of physical activity on white matter microstructure in children with overweight or obesity: The ActiveBrains randomized clinical trial

Background

Emerging research supports the idea that physical activity benefits brain development. However, the body of evidence focused on understanding the effects of physical activity on white matter microstructure during childhood is still in its infancy, and further well-designed randomized clinical trials are needed.

Aim

This study aimed: (i) to investigate the effects of a 20-week physical activity intervention on global white matter microstructure in children with overweight or obesity, and (ii) to explore whether the effect of physical activity on white matter microstructure is global or restricted to a particular set of white matter bundles.

Methods

In total, 109 children aged 8 to 11 years with overweight or obesity were randomized and allocated to either the physical activity program or the control group. Data were collected from November 2014 to June 2016, with diffusion tensor imaging (DTI) data processing and analyses conducted between June 2017 and November 2021. Images were pre-processed using the Functional Magnetic Resonance Imaging (MRI) of the Brain´s Software Library (FSL) and white matter properties were explored by probabilistic fiber tractography and tract-based spatial statistics (TBSS).

Results

Intention-to-treat analyses were performed for all children who completed the pre-test and post-test DTI assessment, with good quality DTI data (N = 89). Of them, 83 children (10.06±1.11 years, 39 % girls, intervention group=44) met the per-protocol criteria (attended at least 70 % of the recommended sessions). Our probabilistic fiber tractography analysis did not show any effects in terms of global and tract-specific fractional anisotropy (FA) and mean diffusivity (MD) in the per-protocol or intention-to-treat analyses. Additionally, we did not observe any effects on the voxel-wise DTI parameters (i.e., FA and MD) using the most restricted TBSS approach (i.e., per protocol analyses and p-corrected image with a statistical threshold of p < 0.05). In the intention-to-treat analysis, we found that our physical activity program had a borderline effect (p-corrected image with a statistical threshold of p < 0.1) on 7 different clusters, including a cluster in the corpus callosum.

Conclusion

We conclude that a 20-week physical activity intervention was not enough to induce changes in global and tract-specific white matter during childhood. The effects of physical activity on white matter microstructure could be restricted to local changes in several white matter tracts (e.g., the body of the corpus callosum). However, our results were not significant, and more interventions are needed to determine whether and how physical activity affects white matter microstructure during childhood.

Changes in the superior longitudinal fasciculus and anterior thalamic radiation in the left brain are associated with developmental dyscalculia

Developmental dyscalculia is a neurodevelopmental disorder specific to arithmetic learning even with normal intelligence and age-appropriate education. Difficulties often persist from childhood through adulthood lowering the individual's quality of life. However, the neural correlates of developmental dyscalculia are poorly understood. This study aimed to identify brain structural connectivity alterations in developmental dyscalculia. All participants were recruited from a large scale, non-referred population sample in a longitudinal design. We studied 10 children with developmental dyscalculia (11.3 ± 0.7 years) and 16 typically developing peers (11.2 ± 0.6 years) using diffusion-weighted magnetic resonance imaging. We assessed white matter microstructure with tract-based spatial statistics in regions-of-interest tracts that had previously been related to math ability in children. Then we used global probabilistic tractography for the first time to measure and compare tract length between developmental dyscalculia and typically developing groups. The high angular resolution diffusion-weighted magnetic resonance imaging and crossing-fiber probabilistic tractography allowed us to evaluate the length of the pathways compared to previous studies. The major findings of our study were reduced white matter coherence and shorter tract length of the left superior longitudinal/arcuate fasciculus and left anterior thalamic radiation in the developmental dyscalculia group. Furthermore, the lower white matter coherence and shorter pathways tended to be associated with the lower math performance. These results from the regional analyses indicate that learning, memory and language-related pathways in the left hemisphere might be related to developmental dyscalculia in children.

Identifying the Neural Bases of Math Competence Based on Structural and Functional Properties of the Human Brain

Human populations show large individual differences in math performance and math learning abilities. Early math skill acquisition is critical for providing the foundation for higher quantitative skill acquisition and succeeding in modern society. However, the neural bases underlying individual differences in math competence remain unclear. Modern neuroimaging techniques allow us to not only identify distinct local cortical regions but also investigate large-scale neural networks underlying math competence both structurally and functionally. To gain insights into the neural bases of math competence, this review provides an overview of the structural and functional neural markers for math competence in both typical and atypical populations of children and adults. Although including discussion of arithmetic skills in children, this review primarily focuses on the neural markers associated with complex math skills. Basic number comprehension and number comparison skills are outside the scope of this review. By synthesizing current research findings, we conclude that neural markers related to math competence are not confined to one particular region; rather, they are characterized by a distributed and interconnected network of regions across the brain, primarily focused on frontal and parietal cortices. Given that human brain is a complex network organized to minimize the cost of information processing, an efficient brain is capable of integrating information from different regions and coordinating the activity of various brain regions in a manner that maximizes the overall efficiency of the network to achieve the goal. We end by proposing that frontoparietal network efficiency is critical for math competence, which enables the recruitment of task-relevant neural resources and the engagement of distributed neural circuits in a goal-oriented manner. Thus, it will be important for future studies to not only examine brain activation patterns of discrete regions but also examine distributed network patterns across the brain, both structurally and functionally.

Robust associations between white matter microstructure and general intelligence

Few tract-based spatial statistics (TBSS) studies have investigated the relations between intelligence and white matter microstructure in healthy (young) adults, and those have yielded mixed observations, yet white matter is fundamental for efficient and accurate information transfer throughout the human brain. We used a multicenter approach to identify white matter regions that show replicable structure-function associations, employing data from 4 independent samples comprising over 2000 healthy participants. TBSS indicated 188 voxels exhibited significant positive associations between g factor scores and fractional anisotropy (FA) in all 4 data sets. Replicable voxels formed 3 clusters, located around the left-hemispheric forceps minor, superior longitudinal fasciculus, and cingulum-cingulate gyrus with extensions into their surrounding areas (anterior thalamic radiation, inferior fronto-occipital fasciculus). Our results suggested that individual differences in general intelligence are robustly associated with white matter FA in specific fiber bundles distributed across the brain, consistent with the Parieto-Frontal Integration Theory of intelligence. Three possible reasons higher FA values might create links with higher g are faster information processing due to greater myelination, more direct information processing due to parallel, homogenous fiber orientation distributions, or more parallel information processing due to greater axon density.

Three dimensional development and asymmetry of the corpus callosum in the 0-18 age group: A retrospective magnetic resonance imaging study

Most of the corpus callosum (CC) developmental studies are concerned with its two-dimensional structure. Linear and area measurements do not directly assess the CC size but estimate the overall structure from the cross-sectional image. This study investigated age- and sex-related changes in volumetric development and asymmetry of CC from birth to 18. For this retrospective study, we selected 696 patients (329 [47.27%] females) with both 3D-T1-weighted sequence and normal radiological anatomy from patients 0-18 years of age who had brain magnetic resonance imaging (MRI) between 2012 and 2020. The genu, body, splenium, and total volume of CC were calculated using MRICloud. The measurement results of 23 age groups were analyzed with SPSS (ver.28). Total CC volume was 18740.76 ± 4314.06 mm³ between 0 and 18 years of age, and its ratio to total brain volume (TBV) was 1.70% ± 0.23%. We observed that the total CC volume has six developmental periods 0 years, 1, 2-4, 5-9, 10-16, and 17-18 years. Genu and body grew in five developmental periods, while splenium in seven. There was intermittent sexual dimorphism in the CC volume in the first 4 years of life (p < 0.05). However, sex factor was insignificant in CC ratio to TBV. Total CC was right lateralized on average 1.81% (ranging -0.59% to 4.52%). Genu was 8.70% lateralized to the right, the body was 2.99% to the left, and the splenium was 1.41% to the right. The three-dimensional development of CC agreed with the two-dimensional developmental data of CC except for some differences.

Maternal Cardiovascular Health in Early Pregnancy and Childhood Brain Structure

Background Poor cardiovascular health during pregnancy has been associated with adverse neurocognitive outcomes in the offspring. We examined the associations of maternal cardiovascular health factors with brain structure in 10-year-old children. Methods and Results We included 2797 mother-offspring pairs from the Generation R Study. Maternal body mass index, gestational weight gain, blood pressure, insulin, glucose, and lipid blood concentrations were obtained in early pregnancy. Childhood structural brain measures, including global metrics of brain tissue volumes and white matter microstructure, were quantified by magnetic resonance imaging at 10 years. As compared with offspring of mothers with normal weight, those of mothers with underweight had smaller total brain volume (difference, -28.99 [95% CI -56.55 to -1.45] cm³). Similarly, as compared with offspring of mothers with gestational weight gain between the 25th and 75th percentile, those of mothers with gestational weight loss or no gestational weight gain (<25th percentile), had smaller total brain volume (difference, -13.07 [95% CI, -23.82 to -2.32] cm³). Also, higher maternal diastolic blood pressure in early pregnancy was associated with lower offspring white matter mean diffusivity (difference, -0.07 [95% CI, -0.11 to -0.02] SD score). After multiple testing correction, only the association of maternal diastolic blood pressure with lower offspring white matter mean diffusivity remained statistically significant. No associations were observed of maternal insulin, glucose, and lipid concentrations with childhood brain outcomes. Conclusions Our findings suggest that maternal cardiovascular health during pregnancy might be related to offspring brain development in the long term. Future studies are needed to replicate our findings and to explore the causal nature of the associations.

Sex interaction of white matter microstructure and verbal IQ in corpus callosum in typically developing children and adolescents

BACKGROUND

Childhood is an extremely important time for neural development that has a critical role in human intelligence. Efficient information processing is crucial for higher intelligence, so the intra- or inter-hemispheric interaction is vital. However, the relationship between neuroanatomical connections and intelligence in typically developing children, as well as sex differences in this relationship, remains unknown.

METHODS

Participants were 253 typically developing children (121 boys and 132 girls) aged 5-18. We acquired diffusion tensor imaging data and intelligence using an age-appropriate version of the IQ test; Wechsler Intelligence Scale for Children (WISC) or Wechsler Adult Intelligence Scale (WAIS). We conducted whole-brain multiple regression analysis to investigate the association between fractional anisotropy (FA), which reflects white matter microstructural properties, and each composite score of IQ test (full-scale IQ, performance IQ, and verbal IQ).

RESULTS

FA was positively correlated with full-scale IQ in bilateral inferior occipitofrontal fasciculus, genu, and splenium of corpus callosum (CC). FA in the right superior longitudinal fasciculus, bilateral inferior longitudinal fasciculus, and splenium of CC were also positively correlated with performance IQ. Furthermore, we found significant sex interaction between FA in the CC and verbal IQ. FA was positively correlated in boys, and negatively correlated in girls.

CONCLUSION

Results suggest that efficient anatomical connectivity between parietal and frontal regions is crucial for children's intelligence. Moreover, inter-hemispheric connections play a critical role in verbal abilities in boys.

Investigating the association between variability in sulcal pattern and academic achievement

Investigating how the brain may constrain academic achievement is not only relevant to understanding brain structure but also to providing insight into the origins of individual differences in these academic abilities. In this pre-registered study, we investigated whether the variability of sulcal patterns, a qualitative feature of the brain determined in-utero and not affected by brain maturation and learning, accounted for individual differences in reading and mathematics. Participants were 97 typically developing 10-year-olds. We examined (a) the association between the sulcal pattern of the IntraParietal Sulcus (IPS) and mathematical ability; (b) the association between the sulcal pattern of the Occipito Temporal Sulcus (OTS) and reading ability; and (c) the overlap and specificity of sulcal morphology of IPS and OTS and their associations with mathematics and reading. Despite its large sample, the present study was unable to replicate a previously observed relationship between the IPS sulcal pattern and mathematical ability and a previously observed association between the left posterior OTS sulcal pattern and reading. We found a weak association between right IPS sulcal morphology and symbolic number abilities and a weak association between left posterior OTS and reading. However, both these associations were the opposite of previous reports. We found no evidence for a possible overlap or specificity in the effect of sulcal morphology on mathematics and reading. Possible explanations for this weak association between sulcal morphology and academic achievement and suggestions for future research are discussed.

Graph Empirical Mode Decomposition-Based Data Augmentation Applied to Gifted Children MRI Analysis

Gifted children and normal controls can be distinguished by analyzing the structural connectivity (SC) extracted from MRI data. Previous studies have improved classification accuracy by extracting several features of the brain regions. However, the limited size of the database may lead to degradation when training deep neural networks as classification models. To this end, we propose to use a data augmentation method by adding artificial samples generated using graph empirical mode decomposition (GEMD). We decompose the training samples by GEMD to obtain the intrinsic mode functions (IMFs). Then, the IMFs are randomly recombined to generate the new artificial samples. After that, we use the original training samples and the new artificial samples to enlarge the training set. To evaluate the proposed method, we use a deep neural network architecture called BrainNetCNN to classify the SCs of MRI data with and without data augmentation. The results show that the data augmentation with GEMD can improve the average classification performance from 55.7 to 78%, while we get a state-of-the-art classification accuracy of 93.3% by using GEMD in some cases. Our results demonstrate that the proposed GEMD augmentation method can effectively increase the limited number of samples in the gifted children dataset, improving the classification accuracy. We also found that the classification accuracy is improved when specific features extracted from brain regions are used, achieving 93.1% for some feature selection methods.

Associations Between White Matter Microstructures and Cognitive Functioning in 8-Year-Old Children: A Track-Weighted Imaging Study

PURPOSE

Quantitative tractography using diffusion-weighted magnetic resonance imaging data is widely used in characterizing white matter microstructure throughout childhood, but more studies are still needed to investigate comprehensive brain-behavior relationships between tract-specific white matter measures and multiple cognitive functions in children.

METHODS

In this study, we analyzed diffusion-weighted MRI data of 71 healthy 8-year-old children utilizing white matter tract-specific quantitative measures derived from diffusion-weighted MRI tractography based on a novel track-weighted imaging approach. Track density imaging, average path length map and 4 track-weighted diffusion tensor imaging measures including: mean diffusivity, fractional anisotropy, axial diffusivity, and radial diffusivity were computed for 63 white matter tracts. The track-weighted imaging measures were then correlated with a comprehensive set of neuropsychological test scores in different cognitive domains including intelligence, language, memory, academic skills, and executive functions to identify tract-specific brain-behavior relationships.

RESULTS

Significant correlations (P < .05, false discovery rate corrected; r = 0.27-0.57) were found in multiple white matter tracts, with a total of 40 correlations identified between various track-weighted imaging measures including average path length map, track-weighted imaging-fractional anisotropy, and neuropsychological test scores and subscales. Specifically, track-weighted imaging measures indicative of better white matter connectivity and/or microstructural development significantly correlated with higher IQ and better language abilities.

CONCLUSION

Our findings demonstrate the ability of track-weighted imaging measures in establishing associations between white matter and cognitive functioning in healthy children and can serve as a reference for normal brain/cognition relationships in young school-age children and further aid in identifying imaging biomarkers predictive of adverse neurodevelopmental outcomes.

Neuroanatomical differences in the memory systems of intellectual giftedness and typical development

INTRODUCTION

Studying neuro-structural markers of intellectual giftedness (IG) will inform scientific understanding of the processes helping children excel academically.

METHODS

Structural and diffusion-weighted MRI was used to compare regional brain shape and connectivity of 12 children with average to high average IQ and 18 IG children, defined as having IQ greater than 145.

RESULTS

IG had larger subcortical structures and more robust white matter microstructural organization between those structures in regions associated with explicit memory. TD had more connected, larger subcortical structures in regions associated with implicit memory.

CONCLUSIONS

It was found that the memory systems within brains of children with exceptional intellectual abilities are differently sized and connected compared to the brains of typically developing children. These different neurodevelopmental trajectories suggest different learning strategies. A spectrum of intelligence types is envisioned, facilitated by different ratios of implicit and explicit system, which was validated using a large external dataset.

Development of brain white matter and math computation ability in children born very preterm and full-term

Children born very preterm (VPT; <32 weeks' gestation) have alterations in brain white matter and poorer math ability than full-term (FT) peers. Diffusion-weighted magnetic resonance imaging studies suggest a link between white matter microstructure and math in VPT and FT children, although longitudinal studies using advanced modelling are lacking. In a prospective longitudinal cohort of VPT and FT children we used Fixel-Based Analysis to investigate associations between maturation of white matter fibre density (FD), fibre-bundle cross-section (FC), and combined fibre density and cross-section (FDC) and math computation ability at 7 (n = 136 VPT; n = 32 FT) and 13 (n = 130 VPT; n = 44 FT) years, as well as between change in white matter and math computation ability from 7 to 13 years (n = 103 VPT; n = 21 FT). In both VPT and FT children, higher FD, FC and FDC in visual, sensorimotor and cortico-thalamic/thalamo-cortical white matter tracts were associated with better math computation ability at 7 and 13 years. Longitudinally, accelerated maturation of the posterior body of the corpus callosum (FDC) was associated with greater math computation development. White matter-math associations were similar for VPT and FT children. In conclusion, white matter maturation is associated with math computation ability across late childhood, irrespective of birth group.

Acute Diffusion Tensor and Kurtosis Imaging and Outcome following Mild Traumatic Brain Injury

In this prospective cohort study, we investigated associations between acute diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) metrics and persistent post-concussion symptoms (PPCS) 3 months after mild traumatic brain injury (mTBI). Adult patients with mTBI (n = 176) and community controls (n = 78) underwent 3 Tesla magnetic resonance imaging (MRI) within 72 h post-injury, estimation of cognitive reserve at 2 weeks, and PPCS assessment at 3 months. Eight DTI and DKI metrics were examined with Tract-Based Spatial Statistics. Analyses were performed in the total sample in uncomplicated mTBI only (i.e., without lesions on clinical MRI), and with cognitive reserve both controlled for and not. Patients with PPCS (n = 35) had lower fractional anisotropy (in 2.7% of all voxels) and kurtosis fractional anisotropy (in 6.9% of all voxels), and higher radial diffusivity (in 0.3% of all voxels), than patients without PPCS (n = 141). In uncomplicated mTBI, only fractional anisotropy was significantly lower in patients with PPCS. Compared with controls, patients with PPCS had widespread deviations in all diffusion metrics. When including cognitive reserve as a covariate, no significant differences in diffusion metrics between patients with and without PPCS were present, but patients with PPCS still had significantly higher mean, radial, and axial diffusivity than controls. In conclusion, patients who developed PPCS had poorer white matter microstructural integrity acutely after the injury, compared with patients who recovered and healthy controls. Differences became less pronounced when cognitive reserve was controlled for, suggesting that pre-existing individual differences in axonal integrity accounted for some of the observed differences.

Directed Connectivity Analysis of the Brain Network in Mathematically Gifted Adolescents

The neurocognitive characteristics of mathematically gifted adolescents are characterized by highly developed functional interactions between the right hemisphere and excellent cognitive control of the prefrontal cortex, enhanced frontoparietal cortex, and posterior parietal cortex. However, it is still unclear when and how these cortical interactions occur. In this paper, we used directional coherence analysis based on Granger causality to study the interactions between the frontal brain area and the posterior brain area in the mathematical frontoparietal network system during deductive reasoning tasks. Specifically, the scalp electroencephalography (EEG) signal was first converted into a cortical dipole source signal to construct a Granger causality network over the θ-band and γ-band ranges. We constructed the binary Granger causality network at the 40 pairs of cortical nodes in the frontal lobe and parietal lobe across the θ-band and the γ-band, which were selected as regions of interest (ROI). We then used graph theory to analyze the network differences. It was found that, in the process of reasoning tasks, the frontoparietal regions of the mathematically gifted show stronger working memory information processing at the θ-band. Additionally, in the middle and late stages of the conclusion period, the mathematically talented individuals have less information flow in the anterior and posterior parietal regions of the brain than the normal subjects. We draw the conclusion that the mathematically gifted brain frontoparietal network appears to have more “automated” information processing during reasoning tasks.

Bridging Brain and Cognition: A Multilayer Network Analysis of Brain Structural Covariance and General Intelligence in a Developmental Sample of Struggling Learners

Network analytic methods that are ubiquitous in other areas, such as systems neuroscience, have recently been used to test network theories in psychology, including intelligence research. The network or mutualism theory of intelligence proposes that the statistical associations among cognitive abilities (e.g., specific abilities such as vocabulary or memory) stem from causal relations among them throughout development. In this study, we used network models (specifically LASSO) of cognitive abilities and brain structural covariance (grey and white matter) to simultaneously model brain-behavior relationships essential for general intelligence in a large (behavioral, N = 805; cortical volume, N = 246; fractional anisotropy, N = 165) developmental (ages 5-18) cohort of struggling learners (CALM). We found that mostly positive, small partial correlations pervade our cognitive, neural, and multilayer networks. Moreover, using community detection (Walktrap algorithm) and calculating node centrality (absolute strength and bridge strength), we found convergent evidence that subsets of both cognitive and neural nodes play an intermediary role 'between' brain and behavior. We discuss implications and possible avenues for future studies.

Linking Brain Biology to Intellectual Endowment: A Review on the Associations of Human Intelligence With Neuroimaging Data

Human intelligence has always been a fascinating subject for scientists. Since the inception of Spearman's general intelligence in the early 1900s, there has been significant progress towards characterizing different aspects of intelligence and its relationship with structural and functional features of the brain. In recent years, the invention of sophisticated brain imaging devices using Diffusion-Weighted Imaging (DWI) and functional Magnetic Resonance Imaging (fMRI) has allowed researchers to test hypotheses about neural correlates of intelligence in humans.This review summarizes recent findings on the associations of human intelligence with neuroimaging data. To this end, first, we review the literature that has related brain morphometry to intelligence. Next, we elaborate on the applications of DWI and restingstate fMRI on the investigation of intelligence. Then, we provide a survey of literature that has used multimodal DWI-fMRI to shed light on intelligence. Finally, we discuss the state-of-the-art of individualized prediction of intelligence from neuroimaging data and point out future strategies. Future studies hold promising outcomes for machine learning-based predictive frameworks using neuroimaging features to estimate human intelligence.

Aberrant white matter microstructure in treatment-resistant schizophrenia✰

Treatment response in schizophrenia divides into three subcategories: treatment-responsive (first-line responders; FLR), treatment-resistant (TRS), and ultra-treatment-resistant schizophrenia (UTRS). White matter abnormalities could drive antipsychotic resistance but little work has investigated differences between TRS and UTRS. The current study aimed to establish whether differences in white matter structure are present across both treatment-resistant subtypes or if UTRS is distinct from TRS. Diffusion-weighted images were acquired for 18 individuals with TRS, 14 with UTRS, 18 FLR and 20 healthy controls. Measures of fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AD) were obtained using tract-based spatial statistics. Analysis of variance and post-hoc t-tests were conducted for each measure. Those with TRS had lower FA than healthy controls in superior longitudinal fasciculus, corpus callosum, thalamic radiation, corticospinal tract, internal capsule, corona radiata and fronto-occipital fasciculus (p<.05 FWE-corrected). Lower FA was also observed in TRS compared with UTRS in the superior longitudinal fasciculus (p<.05 FWE-corrected). No post-hoc tests survived corrections for multiple comparisons and no differences in MD, AD or RD were observed. These data suggest that microstructural deficits in white matter could contribute to TRS but suggest that other mechanisms may be more relevant for UTRS.

White matter microarchitecture and structural network integrity correlate with children intelligence quotient

The neural substrate of high intelligence performances remains not well understood. Based on diffusion tensor imaging (DTI) which provides microstructural information of white matter fibers, we proposed in this work to investigate the relationship between structural brain connectivity and intelligence quotient (IQ) scores. Fifty-seven children (8–12 y.o.) underwent a MRI examination, including conventional T1-weighted and DTI sequences, and neuropsychological testing using the fourth edition of Wechsler Intelligence Scale for Children (WISC-IV), providing an estimation of the Full-Scale Intelligence Quotient (FSIQ) based on four subscales: verbal comprehension index (VCI), perceptual reasoning index (PRI), working memory index (WMI), and processing speed index (PSI). Correlations between the IQ scores and both graphs and diffusivity metrics were explored. First, we found significant correlations between the increased integrity of WM fiber-bundles and high intelligence scores. Second, the graph theory analysis showed that integration and segregation graph metrics were positively and negatively correlated with WISC-IV scores, respectively. These results were mainly driven by significant correlations between FSIQ, VCI, and PRI and graph metrics in the temporal and parietal lobes. In conclusion, these findings demonstrated that intelligence performances are related to the integrity of WM fiber-bundles as well as the density and homogeneity of WM brain networks.

Association between white matter impairment and cognitive dysfunction in patients with ischemic Moyamoya disease

Background

Ischemic Moyamoya disease is one of the important causes of stroke, which leads to severe impairment in cognitive functions. This cognitive impairment occurs prior to stroke. However, the cognitive functions that are impaired and the mechanisms of these impairments have not been determined.

Methods

We analyzed 12 patients with Moyamoya disease and 12 controls. All participants underwent cognitive tests and magnetic resonance imaging (MRI) scans. The diffusion tensor imaging (DTI) data was processed using Tract-Based Spatial Statistics (TBSS). Significantly different white matter areas were correlated with different cognitive functions.

Results

There were significant differences in intelligence and subtraction between the patients and controls (p < 0.05). The parameters of DTI such as fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) have different changes in anterior thalamic radiation, inferior fronto-occipital fasciculus (IFO), superior longitudinal fasciculus (SLF), uncinate fasciculus (UF), inferior longitudinal fasciculus, forceps minor, and other regions between the two groups.

Conclusion

Left UF and IFO may be the key brain regions affecting arithmetic function, while bilateral IFO has an effect on intelligence. RD and AD may be better indicators for early prediction of chronic white matter damage than FA, while MD tends to have a comprehensive indirect change. There is cognitive impairment in ischemic MMD, which is closely related to white matter impairment.

Trial registration

Clinical Trial Registration, Unique identifier: ChiCTR1900023610. Registered 4 June 2019 – Prospective study registered.

Physical fitness and white matter microstructure in children with overweight or obesity: the ActiveBrains project

Recent studies investigated the association of cardiorespiratory fitness with white matter microstructure in children, yet little work has explored to what extent other components of physical fitness (i.e., muscular or motor fitness) are associated with white matter microstructure. Indeed, this association has not been previously explored in children with overweight/obesity who present a different white matter development. Therefore, we aimed to examine associations between physical fitness components and white matter microstructure in children with overweight/obesity. In total, 104 (10.04 ± 1.15 years old; 43 girls) children were included in this cross-sectional study. Physical fitness was assessed using the ALPHA-fitness test battery. Fractional anisotropy (FA) and mean diffusivity were derived from diffusion tensor imaging (DTI). No association was found between physical fitness and global DTI metrics (all P > 0.082). Within individual tracts, all associations became non-significant when analyses were adjusted for multiple comparisons. Using the voxel-wise approach, we identified a small cluster in the left lateral frontal lobe where children with greater upper-body muscular fitness showed higher FA (P_{FWE-corrected} = 0.042). Although our results cannot conclude physical fitness is related to white matter microstructure in children with overweight/obesity; those findings indicate that the association of muscular fitness with white matter microstructure might be more focal on frontal areas of the brain, as opposed to global differences.

EEG source-space synchrostate transitions and Markov modeling in the math-gifted brain during a long-chain reasoning task

To reveal transition dynamics of global neuronal networks of math-gifted adolescents in handling long-chain reasoning, this study explores momentary phase-synchronized patterns, that is, electroencephalogram (EEG) synchrostates, of intracerebral sources sustained in successive 50 ms time windows during a reasoning task and non-task idle process. Through agglomerative hierarchical clustering for functional connectivity graphs and nested iterative cosine similarity tests, this study identifies seven general and one reasoning-specific prototypical functional connectivity patterns from all synchrostates. Markov modeling is performed for the time-sequential synchrostates of each trial to characterize the interstate transitions. The analysis reveals that default mode network, central executive network (CEN), dorsal attention network, cingulo-opercular network, left/right ventral frontoparietal network, and ventral visual network aperiodically recur over non-task or reasoning process, exhibiting high predictability in interactively reachable transitions. Compared to non-gifted subjects, math-gifted adolescents show higher fractional occupancy and mean duration in CEN and reasoning-triggered transient right frontotemporal network (rFTN) in the time course of the reasoning process. Statistical modeling of Markov chains reveals that there are more self-loops in CEN and rFTN of the math-gifted brain, suggesting robust state durability in temporally maintaining the topological structures. Besides, math-gifted subjects show higher probabilities in switching from the other types of synchrostates to CEN and rFTN, which represents more adaptive reconfiguration of connectivity pattern in the large-scale cortical network for focused task-related information processing, which underlies superior executive functions in controlling goal-directed persistence and high predictability of implementing imagination and creative thinking during long-chain reasoning.

Diffusion tensor imaging point to ongoing functional impairment in HIV-infected children at age 5, undetectable using standard neurodevelopmental assessments

Background

Perinatal HIV infection negatively impacts cognitive functioning of children, main domains affected are working memory, processing speed and executive function. Early ART, even when interrupted, improves neurodevelopmental outcomes. Diffusion tension imaging (DTI) is a sensitive tool assessing white matter damage. We hypothesised that white matter measures in regions showing HIV-related alterations will be associated with lower neurodevelopmental scores in specific domains related to the functionality of the affected tracts.

Methods

DTI was performed on children in a neurodevelopmental sub study from the Children with HIV Early Antiretroviral (CHER) trial. Voxel-based group comparisons to determine regions where fractional anisotropy and mean diffusion differed between HIV+ and uninfected children were done. Locations of clusters showing group differences were identified using the Harvard–Oxford cortical and subcortical and John Hopkins University WM tractography atlases provided in FSL. This is a second review of DTI data in this cohort, which was reported in a previous study. Neurodevelopmental assessments including GMDS and Beery-Buktenica tests were performed and correlated with DTI parameters in abnormal white matter.

Results

38 HIV+ children (14 male, mean age 64.7 months) and 11 controls (4 male, mean age 67.7 months) were imaged. Two clusters with lower fractional anisotropy and 7 clusters with increased mean diffusion were identified in the HIV+ group. The only neurodevelopmental domain with a trend of difference between the HIV+ children and controls (p = 0.08), was Personal Social Quotient which correlated to improved myelination of the forceps minor in the control group. As a combined group there was a negative correlation between visual perception and radial diffusion in the right superior longitudinal fasciculus and left inferior longitudinal fasciculus, which may be related to the fact that these tracts, forming part of the visual perception pathway, are at a crucial state of development at age 5.

Conclusion

Even directed neurodevelopmental tests will underestimate the degree of microstructural white matter damage detected by DTI. The visual perception deficit detected in the entire study population should be further examined in a larger study.

Safety and Tolerability of the Anxiolytic and Nootropic Drug Phenibut: A Systematic Review of Clinical Trials and Case Reports

Phenibut is a nootropic drug that exerts anxiolytic and antinociceptive effects by acting on the GABA_B receptor and the α₂-δ subunit of voltage-dependent calcium channels. An increased number of reports of dependence to and intoxication by phenibut purchased online on the one hand and the wide prescription of phenibut in Eastern Europe for more than half a century on the other hand have resulted in a number of controversies regarding its use. In this review, we have summarized currently available information from case reports of phenibut dependence and intoxication and safety data from clinical trials. We included 14 dependence and intoxication case reports (16 patients) and reviewed 11 phenibut clinical trials (583 patients). The clinical symptoms in the case reports included cardiovascular effects, insomnia, anxiety and agitation, hallucinations, and depressed level of consciousness. In addition, the doses used (0.5-100 g/day) were much higher than the recommended daily dose (0.25-2 g/day). An analysis of phenibut side effects described in the clinical trials showed adverse events in only 5.66% of patients, and the most reported side effect was somnolence (1.89%). There are discrepancies in the reported side effects of phenibut in clinical trials compared to those reported in cases of online-purchased phenibut dependence and intoxication. The current systematic review provides evidence that, at therapeutic doses, phenibut is safe and well tolerated with minor adverse effects, but questions regarding the quality of phenibut obtained online and the contribution of alcohol and other drug abuse to phenibut dependence and intoxication remain open.

Gender Differences in Connectome-based Predictions of Individualized Intelligence Quotient and Sub-domain Scores

Scores on intelligence tests are strongly predictive of various important life outcomes. However, the gender discrepancy on intelligence quotient (IQ) prediction using brain imaging variables has not been studied. To this aim, we predicted individual IQ scores for males and females separately using whole-brain functional connectivity (FC). Robust predictions of intellectual capabilities were achieved across three independent data sets (680 subjects) and two intelligence measurements (IQ and fluid intelligence) using the same model within each gender. Interestingly, we found that intelligence of males and females were underpinned by different neurobiological correlates, which are consistent with their respective superiority in cognitive domains (visuospatial vs verbal ability). In addition, the identified FC patterns are uniquely predictive on IQ and its sub-domain scores only within the same gender but neither for the opposite gender nor on the IQ-irrelevant measures such as temperament traits. Moreover, females exhibit significantly higher IQ predictability than males in the discovery cohort. This findings facilitate our understanding of the biological basis of intelligence by demonstrating that intelligence is underpinned by a variety of complex neural mechanisms that engage an interacting network of regions-particularly prefrontal-parietal and basal ganglia-whereas the network pattern differs between genders.

Crystallized and fluid intelligence are predicted by microstructure of specific white-matter tracts

Studies of the neural basis of intelligence have focused on comparing brain imaging variables with global scales instead of the cognitive domains integrating these scales or quotients. Here, the relation between mean tract-based fractional anisotropy (mTBFA) and intelligence indices was explored. Deterministic tractography was performed using a regions of interest approach for 10 white-matter fascicles along which the mTBFA was calculated. The study sample included 83 healthy individuals from the second wave of the Cuban Human Brain Mapping Project, whose WAIS-III intelligence quotients and indices were obtained. Inspired by the "Watershed model" of intelligence, we employed a regularized hierarchical Multiple Indicator, Multiple Causes model (MIMIC), to assess the association of mTBFA with intelligence scores, as mediated by latent variables summarizing the indices. Regularized MIMIC, used due to the limited sample size, selected relevant mTBFA by means of an elastic net penalty and achieved good fits to the data. Two latent variables were necessary to describe the indices: Fluid intelligence (Perceptual Organization and Processing Speed indices) and Crystallized Intelligence (Verbal Comprehension and Working Memory indices). Regularized MIMIC revealed effects of the forceps minor tract on crystallized intelligence and of the superior longitudinal fasciculus on fluid intelligence. The model also detected the significant effect of age on both latent variables.

Reduced White Matter Integrity and Deficits in Neuropsychological Functioning in Adults With Autism Spectrum Disorder

Autism spectrum disorder (ASD) is currently viewed as a disorder of cortical systems connectivity, with a heavy emphasis being on the structural integrity of white matter tracts. However, the majority of the literature to date has focused on children with ASD. Understanding the integrity of white matter tracts in adults may help reveal the nature of ASD pathology in adulthood and the potential contributors to cognitive impairment. This study examined white matter water diffusion using diffusion tensor imaging in relation to neuropsychological measures of cognition in a sample of 45 adults with ASD compared to 20 age, gender, and full-scale-IQ-matched healthy volunteers. Tract-based spatial statistics were used to assess differences in diffusion along white matter tracts between groups using permutation testing. The following neuropsychological measures of cognition were assessed: processing speed, attention vigilance, working memory, verbal learning, visual learning, reasoning and problem solving, and social cognition. Results indicated that fractional anisotropy (FA) was significantly reduced in adults with ASD in the anterior thalamic radiation (P = 0.022) and the right cingulum (P = 0.008). All neuropsychological measures were worse in the ASD group, but none of the measures significantly correlated with reduced FA in either tract in the adults with ASD or in the healthy volunteers. Together, this indicates that the tracts that are the most impacted in autism may not be (at least directly) responsible for the behavioral deficits in ASD. Autism Res 2020, 13: 702-714. © 2020 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: White matter tracts are the data cables in the brain that efficiently transfer information, and damage to these tracts could be the cause for the abnormal behaviors that are associated with autism. We found that two long-range tracts (the anterior thalamic radiation and the cingulum) were both impaired in autism but were not directly related to the impairments in behavior. This suggests that the abnormal tracts and behavior are the effects of another underlying mechanism.

Neurocognitive reorganization between crystallized intelligence, fluid intelligence and white matter microstructure in two age-heterogeneous developmental cohorts

Despite the reliability of intelligence measures in predicting important life outcomes such as educational achievement and mortality, the exact configuration and neural correlates of cognitive abilities remain poorly understood, especially in childhood and adolescence. Therefore, we sought to elucidate the factorial structure and neural substrates of child and adolescent intelligence using two cross-sectional, developmental samples (CALM: N = 551 (N = 165 imaging), age range: 5-18 years, NKI-Rockland: N = 337 (N = 65 imaging), age range: 6-18 years). In a preregistered analysis, we used structural equation modelling (SEM) to examine the neurocognitive architecture of individual differences in childhood and adolescent cognitive ability. In both samples, we found that cognitive ability in lower and typical-ability cohorts is best understood as two separable constructs, crystallized and fluid intelligence, which became more distinct across development, in line with the age differentiation hypothesis. Further analyses revealed that white matter microstructure, most prominently the superior longitudinal fasciculus, was strongly associated with crystallized (gc) and fluid (gf) abilities. Finally, we used SEM trees to demonstrate evidence for developmental reorganization of gc and gf and their white matter substrates such that the relationships among these factors dropped between 7-8 years before increasing around age 10. Together, our results suggest that shortly before puberty marks a pivotal phase of change in the neurocognitive architecture of intelligence.

Changes of brain DTI in healthy human subjects after 520 days isolation and confinement on a simulated mission to Mars

INTRODUCTION

Long-term confinement is known to be a stressful experience with multiple psycho-physiological effects. In the MARS500 project, a real-time simulation of a space-flight to Mars conducted in a hermetically isolated habitat, effects of long-term confinement could be investigated in a unique manner. The aim of this study was to evaluate effects of long-term-confinement on brain cytoarchitecture.

MATERIAL & METHODS

The participants of the MARS500 project underwent 3T-MR imaging including a dedicated DTI-sequence before the isolation, right after ending of confinement and 6 months after the experiment. Voxelwise statistical analysis of the DTI data was carried out using tract-based-spatial statistics, comparing an age-matched control group.

RESULTS

At all three sessions, significant lower fractional anisotropy (FA) than in controls was found in the anterior parts of the callosal body of the participants. Furthermore, after ending of confinement a wide-spread FA reduction could be seen in the right hemisphere culminating in the temporo-parietal-junction-zone. All these areas with decreased FA predominantly showed an elevated radial diffusivity and mean diffusivity while axial diffusivity was less correlated.

DISCUSSION

Long-term confinement does have measurable effects on the microstructure of the brain white matter. We assume effects of sensory deprivation to account for the regional FA reductions seen in the right TPJ. The differences in the Corpus callosum were interpreted as due to preliminary conditions, e.g. personality traits or training effects. FA and radial diffusivity were the predominant DTI parameters with significant changes, suggesting underlying processes of myelin plasticity.

Childhood sleep disturbances and white matter microstructure in preadolescence

BACKGROUND

Sleep problems occur in up to 30% of children and have been associated with adverse developmental outcomes. However, due to a lack of longitudinal neuroimaging studies, the neurobiological changes that may underlie some of these associations have remained unclear. This study explored the association between sleep problems during childhood and white matter (WM) microstructure in preadolescence.

METHODS

Children from the population-based birth cohort, the Generation R Study, who had repeatedly assessed sleep problems between 1.5 and 10 years of age and a MRI scan at age 10 (N = 2,449), were included. Mothers reported on their child's sleep problems using the Child Behavior Checklist (CBCL 1.5-5) when children were 1.5, 3, and 6 years of age. At age 2, mothers completed very similar questions. At age 10, both children and their mothers reported on sleep problems. We used whole-brain and tract-specific fractional anisotropy (FA) and mean diffusivity (MD) values obtained through diffusion tensor imaging as measures of WM microstructure.

RESULTS

Childhood sleep problems at 1.5, 2, and 6 years of age were associated with less WM microstructural integrity (approximately 0.05 SD lower global FA score per 1-SD sleep problems). In repeated-measures analyses, children with more sleep problems (per 1-SD) at baseline had lower FA values at age 10 in particular in the corticospinal tract (-0.12 SD, 95% CI:-0.20;-0.05), the uncinate fasciculus (-0.12 SD, 95% CI:-0.19;-0.05), and the forceps major (-0.11 SD, 95% CI:-0.18;-0.03), although effect estimates across the tracts did not differ substantially.

CONCLUSIONS

Childhood sleep disturbances are associated with less WM microstructural integrity in preadolescence. Our results show that early neurodevelopment may be a period of particular vulnerability to sleep problems. This study cannot demonstrate causality but suggests that preventive interventions addressing sleep problems should be further explored to test whether they impact adverse neurodevelopment.

Dopaminergic gene analysis indicates influence of inattention but not IQ in executive dysfunction of Indian ADHD probands

Organizational inefficiency and inattention are speculated to be the reason for executive deficit (ED) of ADHD probands. Even with average IQ, probands often perform poorly due to higher inattention. Pharmacotherapy, cognitive behavioural therapy, and counselling provide only symptomatic relief. Several candidate genes showed involvement with ADHD; the most consistent are dopamine receptor 4 (DRD4) and solute carrier family 6 member 3 (SLC6A3). We analyzed association of rarely investigated DRD4 and SLC6A3 variants with ADHD core traits in Indo-Caucasoid probands. ED, inattention, organizational efficiency, and IQ were measured by Barkley Deficit in Executive Functioning-Child & Adolescent scale, DSM-IV-TR, Conners' Parent Rating Scale-revised, and WISC respectively. Target sites were analyzed by PCR, RFLP, and/or Sanger sequencing of genomic DNA. DRD4 variants mostly affected inattention while SLC6A3 variants showed association with IQ. Few DRD4 and SLC6A3 variants showed dichotomous association with IQ and inattention. DRD4 Exon3 VNTR >4R showed negative impact on all traits excepting IQ. Inattention showed correlation with attention span, organizational efficiency, and ED, while IQ failed to do so. We infer that IQ and attention could be differentially regulated by dopaminergic gene variants affecting functional efficiency in ADHD and the two traits should be considered together for providing better rehabilitation.

The neural code of intelligence: From correlation to causation

Research into the neural underpinning of intelligence has mainly adopted a construct perspective: trying to find structural and functional brain characteristics that would accommodate the psychological concept of g. Few attempts have been made to explain intelligence exclusively based on brain characteristics - the brain perspective. From a methodological viewpoint the brain intelligence relation has been studied by means of correlational and interventional studies. The later providing a causal elucidation of the brain - intelligence relation. The best neuro-anatomical predictor of intelligence is brain volume showing a modest positive correlation with g, explaining between 9 to 16% of variance. The most likely explanation was that larger brains, containing more neurons, have a greater computational power and in that way allow more complex cognitive processing. Correlations with brain surface, thickness, convolution and callosal shape showed less consistent patterns. The development of diffusion tensor imaging has allowed researchers to look also into the microstructure of brain tissue. Consistently observed was a positively correlation between white matter integrity and intelligence, supporting the idea that efficient information transfer between hemispheres and brain areas is crucial for higher intellectual competence. Based on functional studies of the brain intelligence relationship three theories have been put forward: the neural efficiency, the P-FIT and the multi demand (MD) system theory. On the other hand, The Network Neuroscience Theory of g, based on methods from mathematics, physics, and computer science, is an example for the brain perspective on neurobiological underpinning of intelligence. In this framework network flexibility and dynamics provide the foundation for general intelligence. With respect to intervention studies the most promising results have been achieved with noninvasive brain stimulation and behavioral training providing tentative support for findings put forward by the correlational approach. To date the best consensus based on the diversity of results reported would be that g is predominantly determined by lateral prefrontal attentional control of structured sensory episodes in posterior brain areas. The capacity of flexible transitions between these network states represents the essence of intelligence - g.

White matter microstructure correlates with mathematics but not word reading performance in 13-year-old children born very preterm and full-term

Individuals born very preterm (VPT; <32 weeks' gestational age) are at increased risk of impaired mathematics and word reading performance, as well as widespread white matter microstructural alterations compared with individuals born full term (FT; ≥37 weeks' gestational age). To date, the link between academic performance and white matter microstructure is not well understood. This study aimed to investigate the associations between mathematics and reading performance with white matter microstructure in 114 VPT and 36 FT 13-year-old children. Additionally, we aimed to investigate whether the association of mathematics and reading performance with white matter microstructure in VPT children varied as a function of impairment. To do this, we used diffusion tensor imaging and advanced diffusion modelling techniques (Neurite Orientation Dispersion and Density Imaging and the Spherical Mean Technique), combined with a whole-brain analysis approach (Tract-Based Spatial Statistics). Mathematics performance across VPT and FT groups was positively associated with white matter microstructural measurements of fractional anisotropy and neurite density, and negatively associated with radial and mean diffusivities in widespread, bilateral regions. Furthermore, VPT children with a mathematics impairment (>1 standard deviation below FT mean) had significantly reduced neurite density compared with VPT children without an impairment. Reading performance was not significantly associated with any of the white matter microstructure parameters. Additionally, the associations between white matter microstructure and mathematics and reading performance did not differ significantly between VPT and FT groups. Our findings suggest that alterations in white matter microstructure, and more specifically lower neurite density, are associated with poorer mathematics performance in 13-year-old VPT and FT children. More research is required to understand the association between reading performance and white matter microstructure in 13-year-old children.

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Diffusion tensor and neurite density metrics were associated with mathematics.

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Associations were present in very preterm and full-term children.

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Associations were widespread throughout the white matter microstructure.

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Decreased neurite density was evident in children with a mathematics impairment.

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Limited evidence of associations between white matter microstructure and reading.

Mathematical expertise modulates the architecture of dorsal and cortico-thalamic white matter tracts

To what extent are levels of cognitive expertise reflected in differential structural connectivity of the brain? We addressed this question by analyzing the white matter brain structure of experts (mathematicians) versus non-experts (non-mathematicians) using probabilistic tractography. Having mathematicians and non-mathematicians as participant groups enabled us to directly compare profiles of structural connectivity arising from individual levels of expertise in mathematics. Tracking from functional seed regions activated during the processing of complex arithmetic formulas revealed an involvement of various fiber bundles such the inferior fronto-occipital fascicle, arcuate fasciculus/superior longitudinal fasciculus (AF/SLF), cross-hemispheric connections of frontal lobe areas through the corpus callosum and cortico-subcortical connectivity via the bilateral thalamic radiation. With the aim of investigating expertise-dependent structural connectivity, the streamline density was correlated with the level of expertise, defined by automaticity of processing complex mathematics. The results showed that structural integrity of the AF/SLF was higher in individuals with higher automaticity, while stronger cortico-thalamic connectivity was associated with lower levels of automaticity. Therefore, we suggest that expertise in the domain of mathematics is reflected in plastic changes of the brain's white matter structure, possibly reflecting a general principle of cognitive expertise.

Relationships among stress, emotional intelligence, cognitive intelligence, and cytokines

The brain has multiple functions, and its structures are very closely related to one another. Thus, the brain areas associated with stress, emotion, and intelligence are closely connected. The purpose of this study was to investigate the multiple associations between stress and emotional intelligence (EI), between EI and intelligence quotient (IQ), between cytokines and stress, and between cytokines and IQ. We measured the stress, EI, cognitive intelligence using IQ, and cytokine levels of 70 healthy subjects. We also analyzed the association of cytokines with IQ according to hemispheric dominance using the brain preference indicator (BPI). We found significant negative correlations between stress and the components of EI, such as emotional awareness and expression, emotional thinking, and emotional regulation. High levels of anger, which is a component of stress, were significantly related to poor emotional regulation. Additionally, emotional application was positively correlated with full-scale IQ scores and scores on the vocabulary, picture arrangement, and block design subtests of the IQ test. High IL-10 levels were significantly associated with low stress levels only in the right-brain-dominant group. High IL-10 and IFN-gamma levels have been associated with high scores of arithmetic intelligence. TNF-alpha and IL-6 were negatively associated with vocabulary scores and full-scale IQ, but IL-10 and IFN-gamma were positively associated with scores on the arithmetic subtest in left-brain-dominant subjects. On the other hand, IL-10 showed positive correlations with scores for vocabulary and for vocabulary and arithmetic in right-brain-dominant subjects. Furthermore, we found significant linear regression models which can show integrative associations and contribution on emotional and cognitive intelligence. Thus, we demonstrated that cytokines, stress, and emotional and cognitive intelligence are closely connected one another related to brain structure and functions. Also, the pro-inflammatory cytokines TNF-alpha and IL-6 had negative effects, whereas the anti-inflammatory cytokines (e.g., IL-10 and IFN-gamma) showed beneficial effects, on stress levels, and multiple dimensions of emotional and cognitive intelligence. Additionally, these relationships among cytokines, stress, and emotional and cognitive intelligence differed depending on right and left hemispheric dominance.

Learning Unicycling Evokes Manifold Changes in Gray and White Matter Networks Related to Motor and Cognitive Functions

A three-week unicycling training was associated with (1) reductions of gray matter volume in regions closely linked to visuospatial processes such as spatial awareness, (2) increases in fractional anisotropy primarily in the right corticospinal tract and in the right forceps major of the corpus callosum, and (3) a slowly evolving increase in cortical thickness in the left motor cortex. Intriguingly, five weeks later, during which participants were no longer regularly engaged in unicycling, a re-increase in gray matter was found in the very same region of the rSTG. These changes in gray and white matter morphology were paralleled by increases in unicycling performance, and by improvements in postural control, which diminished until the follow-up assessments. Learning to ride a unicycle results in reorganization of different types of brain tissue facilitating more automated postural control, clearly demonstrating that learning a complex balance task modulates brain structure in manifold and highly dynamic ways.

The brain-structural correlates of mathematical expertise

Studies in several domains of expertise have established that experience-dependent plasticity brings about both functional and anatomical changes. However, little is known about how such changes come to shape the brain in the case of expertise acquired by professional mathematicians. Here, we aimed to identify cognitive and brain-structural (grey and white matter) characteristics of mathematicians as compared to non-mathematicians. Mathematicians and non-mathematician academics from the University of Oxford underwent structural and diffusion MRI scans, and were tested on a cognitive battery assessing working memory, attention, IQ, numerical and social skills. At the behavioural level, mathematical expertise was associated with better performance in domain-general and domain-specific dimensions. At the grey matter level, in a whole-brain analysis, behavioural performance correlated with grey matter density in left superior frontal gyrus – positively for mathematicians but negatively for non-mathematicians; in a region of interest analysis, we found in mathematicians higher grey matter density in the right superior parietal lobule, but lower grey matter density in the right intraparietal sulcus and in the left inferior frontal gyrus. In terms of white matter, there were no significant group differences in fractional anisotropy or mean diffusivity. These results reveal new insights into the relationship between mathematical expertise and grey matter metrics in brain regions previously implicated in numerical cognition, as well as in regions that have so far received less attention in this field. Further studies, based on longitudinal designs and cognitive training, could examine the conjecture that such cross-sectional findings arise from a bidirectional link between experience and structural brain changes that is itself subject to change across the lifespan.

Relating individual differences in white matter pathways to children's arithmetic fluency: a spherical deconvolution study

Connectivity between brain regions is integral to efficient complex cognitive processing, making the study of white matter pathways in clarifying the neural mechanisms of individual differences in arithmetic abilities critical. This white matter connectivity underlying arithmetic has only been investigated through classic diffusion tensor imaging, which, due to methodological limitations, might lead to an oversimplification of the underlying anatomy. More complex non-tensor models, such as spherical deconvolution, however, allow a much more fine-grained delineation of the underlying brain anatomy. Against this background, the current study is the first to use spherical deconvolution to investigate white matter tracts and their relation to individual differences in arithmetic fluency in typically developing children. Participants were 48 typically developing 9-10-year-olds, who were all in grade 4, and who underwent structural diffusion-weighted magnetic resonance imaging scanning. Theoretically relevant white matter tracts were manually delineated with a region of interest approach, after which the hindrance modulated orientational anisotropy (HMOA) index, which provides information on the structural integrity of the tract at hand, was derived for each tract. These HMOA indices were correlated with measures of arithmetic fluency, using frequentist and Bayesian approaches. Our results point towards an association between the HMOA of the right inferior longitudinal fasciculus and individual differences in arithmetic fluency. This might reflect the efficiency with which children process Arabic numerals. Other previously found associations between white matter and individual differences in arithmetic fluency were not observed.

Rapid and widespread white matter plasticity during an intensive reading intervention

White matter tissue properties are known to correlate with performance across domains ranging from reading to math, to executive function. Here, we use a longitudinal intervention design to examine experience-dependent growth in reading skills and white matter in grade school-aged, struggling readers. Diffusion MRI data were collected at regular intervals during an 8-week, intensive reading intervention. These measurements reveal large-scale changes throughout a collection of white matter tracts, in concert with growth in reading skill. Additionally, we identify tracts whose properties predict reading skill but remain fixed throughout the intervention, suggesting that some anatomical properties stably predict the ease with which a child learns to read, while others dynamically reflect the effects of experience. These results underscore the importance of considering recent experience when interpreting cross-sectional anatomy–behavior correlations. Widespread changes throughout the white matter may be a hallmark of rapid plasticity associated with an intensive learning experience.

White matter properties correlate with cognitive performance in a number of domains. Here the authors show that altering a child’s educational environment though a targeted intervention program induces rapid, large-scale changes in the white matter, and that these changes track the learning process.

White matter disruptions in patients with bipolar disorder

Bipolar disorder (BD) patients show aberrant white matter microstructure compared to healthy controls but little is known about the relation with clinical characteristics. We therefore investigated the relation of white matter microstructure with the main pharmacological treatments as well its relation with IQ. Patients with BD (N = 257) and controls (N = 167) underwent diffusion tensor imaging (DTI) and comprehensive clinically assessments including IQ estimates. DTI images were analyzed using tract-based spatial statistics. Fractional anisotropy (FA) and Mean Diffusivity (MD) were determined. Patients had significantly lower FA and higher MD values throughout the white matter skeleton compared to controls. Within the BD patients, lithium use was associated with higher FA and lower MD. Antipsychotic medication use in the BD patients was not associated with FA but, in contrast to lithium, was associated with higher MD. IQ was significantly positively correlated with FA and negatively with MD in patients as well as in controls. In this large DTI study we found evidence for marked differences in FA and MD particularly in (but not restricted to) corpus callosum, between BD patients and controls. This effect was most pronounced in lithium-free patients, implicating that lithium affects white matter microstructure and attenuates differences associated with bipolar disorder. Effects of antipsychotic medication intake were absent in FA and only subtle in MD relative to those of lithium. The abnormal white matter microstructure was associated with IQ but not specifically for either group.