Genetics of brain fiber architecture and intellectual performance

White matter correlates of gait and balance dysfunction in essential tremor patients

BACKGROUND

Essential tremor (ET) is a syndrome characterized by both motor (tremor, gait, and balance dysfunction) and non-motor features like cognitive deficits, depression, sleep, mood, and anxiety disorders. The present study was conducted to characterize the clinical dysfunction and brain localization of gait and balance disturbances in ET patients.

METHODS

174 ET patients and 150 matched healthy controls were evaluated. ET was diagnosed using the Consensus Statement on the Classification of Tremors, from the Task Force on Tremors of the Movement Disorder Society criteria. Participants were assessed by using a structured neuropsychological battery and validated gait scores. Diffusion tensor imaging (DTI) data comprising mean diffusivity, radial diffusivity, axial diffusivity, and fractional anisotropy were analyzed for all subjects.

RESULTS

The mean age of essential tremor cases was 45.1 ± 14.08 years. Male: female ratio in ET cases was 2.5:1. Cognitive impairment was observed in a quarter of ET patients. A significant difference was observed in Berg balance scale scores, tandem gait missteps, and tandem stance time between ET cases and controls (p-value < 0.0001). ET patients with higher tremor scores and head tremors were more aged and had poor gait and cognitive scores (p < 0.0001). In our study, we observed poor gait scores significantly correlated with an increase in mean, radial, and axial diffusivities as well as a decrease in fractional anisotropy over various white matter clusters in the brain. No such correlation was observed among the controls.

CONCLUSION

The present study demonstrates a correlation between gait scores and DTI metrics suggesting a neuroanatomic basis for gait impairment in ET patients.

TS-AI: A deep learning pipeline for multimodal subject-specific parcellation with task contrasts synthesis

Accurate mapping of brain functional subregions at an individual level is crucial. Task-based functional MRI (tfMRI) captures subject-specific activation patterns during various functions and behaviors, facilitating the individual localization of functionally distinct subregions. However, acquiring high-quality tfMRI is time-consuming and resource-intensive in both scientific and clinical settings. The present study proposes a two-stage network model, TS-AI, to individualize an atlas on cortical surfaces through the prediction of tfMRI data. TS-AI first synthesizes a battery of task contrast maps for each individual by leveraging tract-wise anatomical connectivity and resting-state networks. These synthesized maps, along with feature maps of tract-wise anatomical connectivity and resting-state networks, are then fed into an end-to-end deep neural network to individualize an atlas. TS-AI enables the synthesized task contrast maps to be used in individual parcellation without the acquisition of actual task fMRI scans. In addition, a novel feature consistency loss is designed to assign vertices with similar features to the same parcel, which increases individual specificity and mitigates overfitting risks caused by the absence of individual parcellation ground truth. The individualized parcellations were validated by assessing test-retest reliability, homogeneity, and cognitive behavior prediction using diverse reference atlases and datasets, demonstrating the superior performance and generalizability of TS-AI. Sensitivity analysis yielded insights into region-specific features influencing individual variation in functional regionalization. Additionally, TS-AI identified accelerated shrinkage in the medial temporal and cingulate parcels during the progression of Alzheimer's disease, suggesting its potential in clinical research and applications.

Unveiling Promising Neuroimaging Biomarkers for Schizophrenia Through Clinical and Genetic Perspectives

Schizophrenia is a complex and serious brain disorder. Neuroscientists have become increasingly interested in using magnetic resonance-based brain imaging-derived phenotypes (IDPs) to investigate the etiology of psychiatric disorders. IDPs capture valuable clinical advantages and hold biological significance in identifying brain abnormalities. In this review, we aim to discuss current and prospective approaches to identify potential biomarkers for schizophrenia using clinical multimodal neuroimaging and imaging genetics. We first described IDPs through their phenotypic classification and neuroimaging genomics. Secondly, we discussed the applications of multimodal neuroimaging by clinical evidence in observational studies and randomized controlled trials. Thirdly, considering the genetic evidence of IDPs, we discussed how can utilize neuroimaging data as an intermediate phenotype to make association inferences by polygenic risk scores and Mendelian randomization. Finally, we discussed machine learning as an optimum approach for validating biomarkers. Together, future research efforts focused on neuroimaging biomarkers aim to enhance our understanding of schizophrenia.

Associations Among Birth Weight, Adrenarche, Brain Morphometry, and Cognitive Function in Preterm Children Ages 9 to 11 Years

BACKGROUND

Preterm infants with low birth weight are at heightened risk of developmental sequelae, including neurological and cognitive dysfunction that can persist into adolescence or adulthood. In addition, preterm birth and low birth weight can provoke changes in endocrine and metabolic processes that likely impact brain health throughout development. However, few studies have examined associations among birth weight, pubertal endocrine processes, and long-term neurological and cognitive development.

METHODS

We investigated the associations between birth weight and brain morphometry, cognitive function, and onset of adrenarche assessed 9 to 11 years later in 3571 preterm and full-term children using the ABCD (Adolescent Brain Cognitive Development) Study dataset.

RESULTS

The preterm children showed lower birth weight and early adrenarche, as expected. Birth weight was positively associated with cognitive function (all Cohen's d > 0.154, p < .005), global brain volumes (all Cohen's d > 0.170, p < .008), and regional volumes in frontal, temporal, and parietal cortices in preterm and full-term children (all Cohen's d > 0.170, p < .0007); cortical volume in the lateral orbitofrontal cortex partially mediated the effect of low birth weight on cognitive function in preterm children. In addition, adrenal score and cortical volume in the lateral orbitofrontal cortex mediated the associations between birth weight and cognitive function only in preterm children.

CONCLUSIONS

These findings highlight the impact of low birth weight on long-term brain structural and cognitive function development and show important associations with early onset of adrenarche during the puberty. This understanding may help with prevention and treatment.

Heritability of white matter in twins: A diffusion neuroimaging review

Diffusion neuroimaging has emerged as an essential non-invasive technique to explore in vivo microstructural characteristics of white matter (WM), whose integrity allows complex behaviors and cognitive abilities. Studying the factors contributing to inter-individual variability in WM microstructure can provide valuable insight into structural and functional differences of brain among individuals. Genetic influence on this variation has been largely investigated in twin studies employing different measures derived from diffusion neuroimaging. In this context, we performed a comprehensive literature search across PubMed, Scopus and Web of Science of original twin studies focused on the heritability of WM. Overall, our results highlighted a consistent heritability of diffusion indices (i.e., fractional anisotropy, mean, axial and radial diffusivity), and network topology among twins. The genetic influence resulted prominent in frontal and occipital regions, in the limbic system, and in commissural fibers. To enhance the understanding of genetic influence on WM microstructure further studies in less heterogeneous experimental settings, encompassing all diffusion indices, are warranted.

Examining the neurostructural architecture of intelligence: The Lothian Birth Cohort 1936 study

Examining underlying neurostructural correlates of specific cognitive abilities is practically and theoretically complicated by the existence of the positive manifold (all cognitive tests positively correlate): if a brain structure is associated with a cognitive task, how much of this is uniquely related to the cognitive domain, and how much is due to covariance with all other tests across domains (captured by general cognitive functioning, also known as general intelligence, or 'g')? We quantitatively address this question by examining associations between brain structural and diffusion MRI measures (global tissue volumes, white matter hyperintensities, global white matter diffusion fractional anisotropy and mean diffusivity, and FreeSurfer processed vertex-wise cortical volumes, smoothed at 20mm fwhm) with g and cognitive domains (processing speed, crystallised ability, memory, visuospatial ability). The cognitive domains were modelled using confirmatory factor analysis to derive both hierarchical and bifactor solutions using 13 cognitive tests in 697 participants from the Lothian Birth Cohort 1936 study (mean age 72.5 years; SD = .7). Associations between the extracted cognitive factor scores for each domain and g were computed for each brain measure covarying for age, sex and intracranial volume, and corrected for false discovery rate. There were a range of significant associations between cognitive domains and global MRI brain structural measures (r range .008 to .269, p < .05). Regions implicated by vertex-wise regional cortical volume included a widespread number of medial and lateral areas of the frontal, temporal and parietal lobes. However, at both global and regional level, much of the domain-MRI associations were shared (statistically accounted for by g). Removing g-related variance from cognitive domains attenuated association magnitudes with global brain MRI measures by 27.9-59.7% (M = 46.2%), with only processing speed retaining all significant associations. At the regional cortical level, g appeared to account for the majority (range 22.1-88.4%; M = 52.8% across cognitive domains) of regional domain-specific associations. Crystallised and memory domains had almost no unique cortical correlates, whereas processing speed and visuospatial ability retained limited cortical volumetric associations. The greatest spatial overlaps across cognitive domains (as denoted by g) were present in the medial and lateral temporal, lateral parietal and lateral frontal areas.

Longitudinal changes in brain asymmetry track lifestyle and disease

Human beings may have evolved the largest asymmetries of brain organization in the animal kingdom. Hemispheric left-vs-right specialization is especially pronounced in our species-unique capacities. Yet, brain asymmetry features appear to be strongly shaped by non-genetic influences. We hence charted the largest longitudinal brain-imaging adult resource, yielding evidence that brain asymmetry changes continuously in a manner suggestive of neural plasticity. In the UK Biobank population cohort, we demonstrate that asymmetry changes show robust associations across 959 distinct phenotypic variables spanning 11 categories. We also find that changes in brain asymmetry over years co-occur with changes among specific lifestyle markers. Finally, we reveal relevance of brain asymmetry changes to major disease categories across thousands of medical diagnoses. Our results challenge the tacit assumption that asymmetrical neural systems are highly conserved throughout adulthood.

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.

Diffusion tensor-based analysis of white matter in dogs with idiopathic epilepsy

Introduction

The understanding of epileptic seizure pathogenesis has evolved over time, and it is now generally accepted that not only are cortical and subcortical areas involved but also the connection of these regions in the white matter (WM). Recent human neuroimaging studies confirmed the involvement of the WM in several epilepsy syndromes. Neuroimaging studies investigating WM integrity with diffusion tensor imaging (DTI) in canine idiopathic epilepsy are lacking. This study aimed to test the hypothesis that WM diffusion changes can be found in dogs affected by idiopathic epilepsy.

Method

Twenty-six dogs with idiopathic epilepsy (15 Border Collies and 11 Greater Swiss Mountain dogs) and 24 healthy controls (11 Beagle dogs, 5 Border Collies, and 8 Greater Swiss Mountain dogs) were prospectively enrolled. Most dogs with idiopathic epilepsy (17/26) were enrolled within 3 months after seizure onset. Diffusion tensor imaging of the brain with 32 diffusion directions (low b value = 0 s/mm2; maximal b value = 800 s/mm2) was performed in a 3 Tesla scanner. Tract-based spatial statistics (TBSS), a voxel-based approach, was used to investigate changes in fractional anisotropy (FA) and mean diffusivity (MD) in the idiopathic epilepsy group compared to the healthy control group. Additionally, FA and MD were investigated in the region of corpus callosum and cingulate white matter in both groups.

Results

We observed subtle changes in WM DTI between the idiopathic epilepsy group and the healthy control group limited to cingulate WM, with a significantly lower FA in the idiopathic epilepsy group compared to the healthy control group in the region of interest (ROI) approach (p = 0.027). No significant changes were found between the idiopathic epilepsy group and the healthy control group in the TBSS analysis and in the corpus callosum in the ROI approach.

Conclusion

This study supports the cingulate area as a target structure in canine epilepsy. The subtle changes only might be explained by the short duration of epilepsy, small sample sizes, and the higher variability in canine brain anatomy. Furthermore, all included dogs showed generalized tonic-clonic seizures, possibly affected by generalized epilepsy syndrome, which are also associated with less pronounced DTI changes in humans than focal epilepsy syndromes.

Longitudinal development of the human white matter structural connectome and its association with brain transcriptomic and cellular architecture

From childhood to adolescence, the spatiotemporal development pattern of the human brain white matter connectome and its underlying transcriptomic and cellular mechanisms remain largely unknown. With a longitudinal diffusion MRI cohort of 604 participants, we map the developmental trajectory of the white matter connectome from global to regional levels and identify that most brain network properties followed a linear developmental trajectory. Importantly, connectome-transcriptomic analysis reveals that the spatial development pattern of white matter connectome is potentially regulated by the transcriptomic architecture, with positively correlated genes involve in ion transport- and development-related pathways expressed in excitatory and inhibitory neurons, and negatively correlated genes enriches in synapse- and development-related pathways expressed in astrocytes, inhibitory neurons and microglia. Additionally, the macroscale developmental pattern is also associated with myelin content and thicknesses of specific laminas. These findings offer insights into the underlying genetics and neural mechanisms of macroscale white matter connectome development from childhood to adolescence.

Genetic and Environmental Influences on Structural and Diffusion-Based Alzheimer's Disease Neuroimaging Signatures Across Midlife and Early Old Age

BACKGROUND

Composite scores of magnetic resonance imaging-derived metrics in brain regions associated with Alzheimer's disease (AD), commonly termed AD signatures, have been developed to distinguish early AD-related atrophy from normal age-associated changes. Diffusion-based gray matter signatures may be more sensitive to early AD-related changes compared with thickness/volume-based signatures, demonstrating their potential clinical utility. The timing of early (i.e., midlife) changes in AD signatures from different modalities and whether diffusion- and thickness/volume-based signatures each capture unique AD-related phenotypic or genetic information remains unknown.

METHODS

Our validated thickness/volume signature, our novel mean diffusivity (MD) signature, and a magnetic resonance imaging-derived measure of brain age were used in biometrical analyses to examine genetic and environmental influences on the measures as well as phenotypic and genetic relationships between measures over 12 years. Participants were 736 men from 3 waves of the Vietnam Era Twin Study of Aging (VETSA) (baseline/wave 1: mean age [years] = 56.1, SD = 2.6, range = 51.1-60.2). Subsequent waves occurred at approximately 5.7-year intervals.

RESULTS

MD and thickness/volume signatures were highly heritable (56%-72%). Baseline MD signatures predicted thickness/volume signatures over a decade later, but baseline thickness/volume signatures showed a significantly weaker relationship with future MD signatures. AD signatures and brain age were correlated, but each measure captured unique phenotypic and genetic variance.

CONCLUSIONS

Cortical MD and thickness/volume AD signatures are heritable, and each signature captures unique variance that is also not explained by brain age. Moreover, results are in line with changes in MD emerging before changes in cortical thickness, underscoring the utility of MD as a very early predictor of AD risk.

Reduced fractional anisotropy in bipolar disorder v. major depressive disorder independent of current symptoms

BACKGROUND

Patients with bipolar disorder (BD) show reduced fractional anisotropy (FA) compared to patients with major depressive disorder (MDD). Little is known about whether these differences are mood state-independent or influenced by acute symptom severity. Therefore, the aim of this study was (1) to replicate abnormalities in white matter microstructure in BD v. MDD and (2) to investigate whether these vary across depressed, euthymic, and manic mood.

METHODS

In this cross-sectional diffusion tensor imaging study, n = 136 patients with BD were compared to age- and sex-matched MDD patients and healthy controls (HC) (n = 136 each). Differences in FA were investigated using tract-based spatial statistics. Using interaction models, the influence of acute symptom severity and mood state on the differences between patient groups were tested.

RESULTS

Analyses revealed a main effect of diagnosis on FA across all three groups (ptfce-FWE = 0.003). BD patients showed reduced FA compared to both MDD (ptfce-FWE = 0.005) and HC (ptfce-FWE < 0.001) in large bilateral clusters. These consisted of several white matter tracts previously described in the literature, including commissural, association, and projection tracts. There were no significant interaction effects between diagnosis and symptom severity or mood state (all ptfce-FWE > 0.704).

CONCLUSIONS

Results indicated that the difference between BD and MDD was independent of depressive and manic symptom severity and mood state. Disruptions in white matter microstructure in BD might be a trait effect of the disorder. The potential of FA values to be used as a biomarker to differentiate BD from MDD should be further addressed in future studies using longitudinal designs.

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.

Intelligenzdiagnostik der Zukunft

Zusammenfassung. Die menschliche Intelligenz ist eines der am besten erforschten und validierten Konstrukte innerhalb der Psychologie. Dennoch wird die Validität von Intelligenztests im gruppen- und insbesondere kulturvergleichenden Kontext regelmäßig und berechtigterweise kritisch hinterfragt. Obwohl verschiedene Alternativen und Weiterentwicklungen der Intelligenzdiagnostik vorgeschlagen wurden (z. B. kulturfaire Tests), sind fundamentale Probleme in der vergleichenden Intelligenzdiagnostik noch immer ungelöst und die Validitäten entsprechender Verfahren unklar. In dem vorliegenden Positionspapier wird diese Thematik aus der Perspektive der Kognitionspsychologie und der kognitiven Neurowissenschaften beleuchtet und eine prozessorientierte und biologisch inspirierte Form der Intelligenzdiagnostik als potentieller Lösungsansatz vorgeschlagen. Wir zeigen die Bedeutung elementarer kognitiver Prozesse auf (insbesondere Arbeitsgedächtniskapazität, Aufmerksamkeit, Verarbeitungsgeschwindigkeit), die individuellen Leistungsunterschieden zu Grunde liegen, und betonen, dass der Unterscheidung zwischen Inhalten und Prozessen eine zentrale, jedoch oft vernachlässigte Rolle in der Diagnostik allgemeiner kognitiver Leistungsunterschiede zukommt. Während aus kognitions- und neuropsychologischer Sicht davon ausgegangen werden kann, dass sich insbesondere Prozesse für interkulturelle Vergleiche eignen, sollten Inhalte als stärker kulturspezifisch verstanden werden. Darauf aufbauend diskutieren wir drei verschiedene Ansätze zur Verbesserung interkultureller Vergleichbarkeit der Intelligenzdiagnostik sowie deren Grenzen. Wir postulieren, dass sich die Intelligenzforschung im Austausch mit verschiedenen Disziplinen stärker auf die Identifikation von generellen kognitiven Prozessen fokussieren sollte und diskutieren das Potenzial zukünftiger Forschung hin zu einer prozessorientierten und biologisch inspirierten Intelligenzdiagnostik. Schließlich zeigen wir derzeitige Möglichkeiten auf, gehen aber auch auf etwaige Herausforderungen ein und beleuchten Implikationen für die zukünftige Intelligenzdiagnostik und -forschung.

The Impaired Subcortical Pathway From Superior Colliculus to the Amygdala in Boys With Autism Spectrum Disorder

Objective

Increasing evidence suggests that a subcortical pathway from the superior colliculus (SC) through the pulvinar to the amygdala plays a crucial role in mediating non-conscious processing in response to emotional visual stimuli. Given the atypical eye gaze and response patterns to visual affective stimuli in autism, we examined the functional and white matter structural difference of the pathway in boys with autism spectrum disorder (ASD) and typically developing (TD) boys.

Methods

A total of 38 boys with ASD and 38 TD boys were included. We reconstructed the SC-pulvinar-amygdala pathway in boys with ASD and TD using tractography and analyzed tract-specific measurements to compare the white matter difference between the two groups. A region of interest-based functional analysis was also applied among the key nodes of the pathway to explore the functional connectivity network.

Results

Diffusion tensor imaging analysis showed decreased fractional anisotropy (FA) in pathways for boys with ASD compared to TD. The FA change was significantly associated with the atypical communication pattern in boys with ASD. In addition, compared to TD, we found that the ASD group was associated with increased functional connectivity between the right pulvinar and the left SC.

Conclusion

Our results indicated that the functional and white matter microstructure of the subcortical route to the amygdala might be altered in individuals with autism. This atypical structural change of the SC-pulvinar-amygdala pathway may be related to the abnormal communication patterns in boys with ASD.

Individual variability in the nonlinear development of the corpus callosum during infancy and toddlerhood: a longitudinal MRI analysis

The human brain spends several years bootstrapping itself through intrinsic and extrinsic modulation, thus gradually developing both spatial organization and functions. Based on previous studies on developmental patterns and inter-individual variability of the corpus callosum (CC), we hypothesized that inherent variations of CC shape among infants emerge, depending on the position within the CC, along the developmental timeline. Here we used longitudinal magnetic resonance imaging data from infancy to toddlerhood and investigated the area, thickness, and shape of the midsagittal plane of the CC by applying multilevel modeling. The shape characteristics were extracted using the Procrustes method. We found nonlinearity, region-dependency, and inter-individual variability, as well as intra-individual consistencies, in CC development. Overall, the growth rate is faster in the first year than in the second year, and the trajectory differs between infants; the direction of CC formation in individual infants was determined within six months and maintained to two years. The anterior and posterior subregions increase in area and thickness faster than other subregions. Moreover, we clarified that the growth rate of the middle part of the CC is faster in the second year than in the first year in some individuals. Since the division of regions exhibiting different tendencies coincides with previously reported divisions based on the diameter of axons that make up the region, our results suggest that subregion-dependent individual variability occurs due to the increase in the diameter of the axon caliber, myelination partly due to experience and axon elimination during the early developmental period.

Heritable anisotropy associated with cognitive impairments among patients with schizophrenia and their non-psychotic relatives in multiplex families

BACKGROUND

To test the functional implications of impaired white matter (WM) connectivity among patients with schizophrenia and their relatives, we examined the heritability of fractional anisotropy (FA) measured on diffusion tensor imaging data acquired in Pittsburgh and Philadelphia, and its association with cognitive performance in a unique sample of 175 multigenerational non-psychotic relatives of 23 multiplex schizophrenia families and 240 unrelated controls (total = 438).

METHODS

We examined polygenic inheritance (h2r) of FA in 24 WM tracts bilaterally, and also pleiotropy to test whether heritability of FA in multiple WM tracts is secondary to genetic correlation among tracts using the Sequential Oligogenic Linkage Analysis Routines. Partial correlation tests examined the correlation of FA with performance on eight cognitive domains on the Penn Computerized Neurocognitive Battery, controlling for age, sex, site and mother's education, followed by multiple comparison corrections.

RESULTS

Significant total additive genetic heritability of FA was observed in all three-categories of WM tracts (association, commissural and projection fibers), in total 33/48 tracts. There were significant genetic correlations in 40% of tracts. Diagnostic group main effects were observed only in tracts with significantly heritable FA. Correlation of FA with neurocognitive impairments was observed mainly in heritable tracts.

CONCLUSIONS

Our data show significant heritability of all three-types of tracts among relatives of schizophrenia. Significant heritability of FA of multiple tracts was not entirely due to genetic correlations among the tracts. Diagnostic group main effect and correlation with neurocognitive performance were mainly restricted to tracts with heritable FA suggesting shared genetic effects on these traits.

Lower fractional anisotropy of the corticothalamic tract and increased response time variability in adult patients with ADHD

BACKGROUND

Intraindividual intertrial variability has been suggested as an endophenotype of attention-deficit/hyperactivity disorder (ADHD). It is usually evaluated as response time variability (RTV) in reaction time tasks, and RTV has emerged as a robust and stable feature of ADHD. Among attempts to elucidate the neurobiological underpinnings of RTV, it has been suggested that alterations in white matter microstructure may explain RTV.

METHODS

We used diffusion tensor imaging (DTI) in a group of 53 adults with ADHD and 50 healthy controls. We obtained RTV parameters from a simple reaction-time task, in which participants were asked to respond to the appearance of white crosses on a screen using button presses.

RESULTS

We observed significant between-group differences for the ex-Gaussian parameter τ, indicating that the mean of extremely slow responses was greater for adults with ADHD than controls. Fractional anisotropy (FA) derived from DTI was significantly different between groups in 2 clusters of the corticothalamic tract. In the ADHD group, relatively decreased FA values were significantly associated with the parameter τ, such that lower FA values in the corticothalamic tract predicted greater τ as an index of RTV. We did not observe this association in healthy controls.

LIMITATIONS

For comparison with previous studies, we used FA as a dependent variable of interest. However, although this metric is sensitive to white matter structural properties, there are ambiguities in its interpretation.

CONCLUSION

Even in a simple reaction-time task, RTV proved again to be a stable feature of ADHD. It was associated with altered white matter structural properties of the corticothalamic tract in adults with ADHD.

Genetic and environmental influences of variation in diffusion MRI measures of white matter microstructure

Quantitative neuroimaging studies in twin samples can investigate genetic contributions to brain structure and microstructure. Diffusion tensor imaging (DTI) studies with twin samples have shown moderate to high heritability in white matter microstructure. This study investigates the genetic and environmental contributions of another widely used diffusion MRI model not yet applied to twin studies, neurite orientation dispersion and density imaging (NODDI). The NODDI model is a multicompartment model of the diffusion-weighted MRI signal, providing estimates of neurite density (ND) and the orientation dispersion index (ODI). A cohort of monozygotic (MZ) and same-sex dizygotic (DZ) twins (N = 460 individuals) between 13 and 24 years of age were scanned with a multi-shell diffusion weighted imaging protocol. Select white matter (WM) regions of interest (ROI) were extracted. Biometric structural equation modeling estimated the relative contributions from additive genetic (A) and common (C) and unique environmental (E) factors. Genetic factors for the NODDI measures accounted for 91% and 65% of the variation of global ND and ODI, respectively, compared with 83% for FA. We observed higher heritability for ND than both FA and ODI in 25 of 30 discrete white matter regions that we examined, suggesting ND may be more sensitive to underlying genetic sources of variation. This study demonstrated that genetic factors play a key role in the development of white matter microstructure using both DTI and NODDI.

Where the genome meets the connectome: Understanding how genes shape human brain connectivity

The integration of modern neuroimaging methods with genetically informative designs and data can shed light on the molecular mechanisms underlying the structural and functional organization of the human connectome. Here, we review studies that have investigated the genetic basis of human brain network structure and function through three complementary frameworks: (1) the quantification of phenotypic heritability through classical twin designs; (2) the identification of specific DNA variants linked to phenotypic variation through association and related studies; and (3) the analysis of correlations between spatial variations in imaging phenotypes and gene expression profiles through the integration of neuroimaging and transcriptional atlas data. We consider the basic foundations, strengths, limitations, and discoveries associated with each approach. We present converging evidence to indicate that anatomical connectivity is under stronger genetic influence than functional connectivity and that genetic influences are not uniformly distributed throughout the brain, with phenotypic variation in certain regions and connections being under stronger genetic control than others. We also consider how the combination of imaging and genetics can be used to understand the ways in which genes may drive brain dysfunction in different clinical disorders.

Development of white matter microstructure and executive functions during childhood and adolescence: a review of diffusion MRI studies

Diffusion magnetic resonance imaging (dMRI) provides indirect measures of white matter microstructure that can be used to make inferences about structural connectivity within the brain. Over the last decade, a growing literature of cross-sectional and longitudinal studies have documented relationships between dMRI indices and cognitive development. In this review, we provide a brief overview of dMRI methods and how they can be used to study white matter and connectivity and review the extant literature examining the links between dMRI indices and executive functions during development. We explore the links between white matter microstructure and specific executive functions: inhibition, working memory and cognitive shifting, as well as performance on complex executive function tasks. Concordance in findings across studies are highlighted, and potential explanations for discrepancies between results, together with challenges with using dMRI in child and adolescent populations, are discussed. Finally, we explore future directions that are necessary to better understand the links between child and adolescent development of structural connectivity of the brain and executive functions.

Understanding Sensitive Period Effects in Musical Training

Adult ability in complex cognitive domains, including music, is commonly thought of as the product of gene-environment interactions, where genetic predispositions influence and are modulated by experience, resulting in the final phenotypic expression. Recently, however, the important contribution of maturation to gene-environment interactions has become better understood. Thus, the timing of exposure to specific experience, such as music training, has been shown to produce long-term impacts on adult behaviour and the brain. Work from our lab and others shows that musical training before the ages of 7-9 enhances performance on musical tasks and modifies brain structure and function, sometimes in unexpected ways. The goal of this paper is to present current evidence for sensitive period effects for musical training in the context of what is known about brain maturation and to present a framework that integrates genetic, environmental and maturational influences on the development of musical skill. We believe that this framework can also be applied more broadly to understanding how predispositions, brain development and experience interact.

Widespread Disruptions of White Matter in Familial Multiple Sclerosis: DTI and NODDI Study

Diffusion tensor imaging (DTI) is a noninvasive, quantitative MRI technique that measures white matter (WM) integrity. Many brain dimensions are heritable, including white matter integrity measured with DTI. Family studies are valuable to provide insights into the interactive effects of non-environmental factors on multiple sclerosis (MS). To examine the contribution of familial factors to the diffusion signals across WM microstructure, we performed DTI and calculated neurite orientation dispersion plus density imaging (NODDI) diffusion parameters in two patient groups comprising familial and sporadic forms of multiple sclerosis and their unaffected relatives. We divided 111 subjects (49 men and 62 women: age range 19-60) into three groups conforming to their MS history. The familial MS group included 30 participants (patients; n = 16, healthy relatives; n = 14). The sporadic group included 41 participants (patients; n = 10, healthy relatives; n = 31). Forty age-matched subjects with no history of MS in their families were defined as the control group. To study white matter integrity, two methods were employed: one for calculating the mean of DTI, FA, and MD parameters on 18 tracts using Tracts Constrained by Underlying Anatomy (TRACULA) and the other for whole brain voxel-based analysis using tract-based spatial statistics (TBSS) on NDI and ODI parameters derived from NODDI and DTI parameters. Voxel-based analysis showed considerable changes in FA, MD, NDI, and ODI in the familial group when compared with the control group, reflecting widespread impairment of white matter in this group. The analysis of 18 tracts with TRACULA revealed increased MD and FA reduction in more tracts (left and right ILF, UNC, and SLFT, forceps major and minor) in familial MS patients vs. the control group. There were no significant differences between the patient groups. We found no consequential changes in healthy relatives of both patient groups in voxel-based and tract analyses. Considering the multifactorial etiology of MS, familial studies are of great importance to clarify the effects of certain predisposing factors on demyelinating brain pathology.

Stem-Cell Therapy as a Potential Strategy for Radiation-Induced Brain Injury

Radiation therapy is a standard and effective non-surgical treatment for primary brain tumors and metastases. However, this strategy inevitably results in damage of normal brain tissue, causing severe complications, especially the late-delayed cognitive impairment. Due to the multifactorial and complex pathological effects of radiation, there is a lack of effective preventative and restorative treatments for the irradiated brain. Stem-cell therapy has held considerable promise for decades in the treatment of central nervous system (CNS) disorders because of its unique capacity for tissue repair and functional integrity. Currently, there is growing interest in using stem cells as a novel option to attenuate the adverse effects of irradiation. In the present review, we discuss recent studies evaluating stem-cell therapies for the irradiated brain and their therapeutic effects on ameliorating radiation-related brain injury as well as their potential challenges in clinical applications. We discuss these works in context of the pathogenesis of radiation-induced injury to CNS tissue in an attempt to elucidate the potential mechanisms of engrafted stem cells to reverse radiation-induced degenerative processes.

Increased Resting-State Interhemispheric Functional Connectivity of Posterior Superior Temporal Gyrus and Posterior Cingulate Cortex in Congenital Amusia

Interhemispheric connectivity of the two cerebral hemispheres is crucial for a broad repertoire of cognitive functions including music and language. Congenital amusia has been reported as a neurodevelopment disorder characterized by impaired music perception and production. However, little is known about the characteristics of the interhemispheric functional connectivity (FC) in amusia. In the present study, we used a newly developed voxel-mirrored homotopic connectivity (VMHC) method to investigate the interhemispheric FC of the whole brain in amusia at resting-state. Thirty amusics and 29 matched participants underwent a resting-state functional magnetic resonance imaging (fMRI) scanning. An automated VMHC approach was used to analyze the fMRI data. Compared to the control group, amusics showed increased VMHC within the posterior part of the default mode network (DMN) mainly in the posterior superior temporal gyrus (pSTG) and posterior cingulate cortex (PCC). Correlation analyses revealed negative correlations between the VMHC value in pSTG/PCC and the music perception ability among amusics. Further ROC analyses showed that the VMHC value of pSTG/PCC showed a good sensibility/specificity to differentiate the amusics from the controls. These findings provide a new perspective for understanding the neural basis of congenital amusia and imply the immature state of DMN may be a credible neural marker of amusia.

A structural enriched functional network: An application to predict brain cognitive performance

The structure-function coupling in brain networks has emerged as an important research topic in modern neuroscience. The structural network could provide the backbone of the functional network. The integration of the functional network with structural information can help us better understand functional communication in the brain. This paper proposed a method to accurately estimate the brain functional network enriched by the structural network from diffusion magnetic resonance imaging. First, we adopted a simplex regression model with graph-constrained Elastic Net to construct the functional networks enriched by the structural network. Then, we compared the constructed network characteristics of this approach with several state-of-the-art competing functional network models. Furthermore, we evaluated whether the structural enriched functional network model improves the performance for predicting the cognitive-behavioral outcomes. The experiments have been performed on 218 participants from the Human Connectome Project database. The results demonstrated that our network model improves network consistency and its predictive performance compared with several state-of-the-art competing functional network models.

White matter microstructure correlates of age, sex, handedness and motor ability in a population-based sample of 3031 school-age children

Understanding the development of white matter microstructure in the general population is an imperative precursor to identifying its involvement in psychopathology. Previous studies have reported changes in white matter microstructure associated with age and different developmental patterns between boys and girls. Handedness has also been related to white matter in adults. Motor performance, tightly dependent on overall neuronal myelination, has been related to the corpus callosum. However, the association between motor performance and global white matter microstructure has not been reported in the literature. In general, these age, sex, handedness, and motor performance associations have been observed using small and poorly representative samples. We examined the relationships between age, sex, handedness, and motor performance, measured with a finger tapping task, and white matter microstructure in the forceps major and minor and in 5 tracts bilaterally (cingulum, corticospinal, inferior and superior longitudinal fasciculi, and uncinate) in a population-based sample of 3031 children between 8 and 12 years of age. Diffusion tensor imaging (DTI) data were acquired using a single, study-dedicated 3 Tesla scanner. We extracted and quantified features of white matter microstructure for each tract. We computed global DTI metrics by combining scalar values across multiple tracts into single latent factors using a confirmatory factor analysis. The adjusted linear regression models indicated that age was associated with global fractional anisotropy (FA), global mean diffusivity (MD), and almost all the tracts. Further, girls showed lower global MD than boys, while FA values differed by tract, and no age-sex interactions were found. No differences were observed in white matter microstructure between right- and left-handed children. We observed that FA in forceps major was associated with right-hand finger tapping performance. White matter FA in association tracts was only related to motor function before multiple testing correction. Our findings do not provide evidence for a relationship between finger tapping task performance and global white matter microstructure.

DNA methylation changes in genes involved in inflammation and depression in fibromyalgia: a pilot study

OBJECTIVES

The present pilot study aims to investigate DNA methylation changes of genes related to fibromyalgia (FM) development and its main comorbid symptoms, including sleep impairment, inflammation, depression and other psychiatric disorders. Epigenetic modifications might trigger or perpetuate complex interplay between pain transduction/transmission, central pain processing and experienced stressors in vulnerable individuals.

METHODS

We conducted DNA methylation analysis by targeted bisulfite NGS sequencing testing differential methylation in 112 genomic regions from leukocytes of eight women with FM and their eight healthy sisters as controls.

RESULTS

Tests for differentially methylated regions and cytosines brought focus on the GRM2 gene, encoding the metabotropic glutamate receptor2. The slightly increased DNA methylation observed in the GRM2 region of FM patients may confirm the involvement of the glutamate pathway in this pathological condition. Logistic regression highlighted the simultaneous association of methylation levels of depression and inflammation-related genes with FM.

CONCLUSIONS

Altogether, the results evidence the glutamate pathway involvement in FM and support the idea that a combination of methylated and unmethylated genes could represent a risk factor to FM or its consequence, more than single genes. Further studies on the identified biomarkers could contribute to unravel the causative underlying FM mechanisms, giving reliable directions to research, improving the diagnosis and effective therapies.

Microstructural alterations in medial forebrain bundle are associated with interindividual pain sensitivity

The perception of pain to noxious stimuli, also known as pain sensitivity, varies among individuals. The comprised brain structures and their white matter pathways are complex and elusive. Here, we aimed to investigate whether variation of microstructure of the medial forebrain bundle (MFB), a tract connecting the basal forebrain with the brain stem, is associated with interindividual pain sensitivity. We assessed interindividual pain sensitivity as a rating of pain intensity to heat stimuli (45, 47, and 48.9°C) in 38 healthy men (age: 27.05 ± 5.7 years). We also reconstructed the MFB using multitensor tractography from diffusion magnetic resonance imaging (dMRI) and calculated free‐water corrected dMRI measures of fractional anisotropy (FA_t), radial diffusivity (RD_t), and axial diffusivity (AD_t). Lower ratings of interindividual pain intensity correlated with higher FA_t and lower RD_t of the MFB. As changes in FA_t and RD_t may reflect abnormalities in myelination, the results might be interpreted as that a lower pain rating is associated with higher degree of myelination of the MFB and could represent an inhibitory pathway of pain. Our results suggest that alteration of microstructure in the MFB contributes to the interindividual variation of pain perception.

The role of the corpus callosum in language network connectivity in children

The specific role of the corpus callosum (CC) in language network organization remains unclear, two contrasting models have been proposed: inhibition of homotopic areas allowing for independent functioning of the hemispheres versus integration of information from both hemispheres. This study aimed to add to this discussion with the first investigation of language network connectivity in combination with CC volume measures. In 38 healthy children aged 6–12, we performed task‐based functional magnetic resonance imaging to measure language network connectivity, used structural magnetic resonance imaging to quantify CC subsection volumes, and administered various language tests to examine language abilities. We found an increase in left intrahemispheric and bilateral language network connectivity and a decrease in right intrahemispheric connectivity associated with larger volumes of the posterior, mid‐posterior, and central subsections of the CC. Consistent with that, larger volumes of the posterior parts of the CC were significantly associated with better verbal fluency and vocabulary, the anterior CC volume was positively correlated with verbal span. Thus, children with larger volumes of CC subsections showed increased interhemispheric language network connectivity and were better in different language domains. This study presents the first evidence that the CC is directly linked to language network connectivity and underlines the excitatory role of the CC in the integration of information from both hemispheres.

Lifespan trajectories of relative corpus callosum thickness: Regional differences and cognitive relevance

The cerebral hemispheres are specialized for different cognitive functions and receive divergent information from the sensory organs, so that the interaction between the hemispheres is a crucial aspect of perception and cognition. At the same time, the major fiber tract responsible for this interaction, the corpus callosum, shows a structural development across the lifespan which is over-proportional. That is, compared to changes in overall forebrain volume, the corpus callosum shows an accentuated growth during childhood, adolescence, and early adulthood, as well as pronounced decline in older age. However, this over-proportionality of growth and decline along with potential consequences for cognition, have been largely overlooked in empirical research. In the present study we systematically address the proportionality of callosal development in a large mixed cross-sectional and longitudinal sample (1867 datasets from 1014 unique participants), covering the human lifespan (age range 4-93 years), and examine the cognitive consequences of the observed changes. Relative corpus callosum thickness was measured at 60 segments along the midsagittal surface, and lifespan trajectories were clustered to identify callosal subsections of comparable lifespan development. While confirming the expected inverted u-shaped lifespan trajectories, we also found substantial regional variation. Compared with anterior clusters, the most posterior sections exhibited an accentuated growth during development which extends well into the third decade of life, and a protracted decline in older age which is delayed by about 10 years (starting mid to late 50s). We further showed that the observed longitudinal changes in relative thickness of the mid splenium significantly mediates age-related changes in tests assessing verbal knowledge and non-verbal visual-spatial abilities across the lifespan. In summary, we demonstrate that analyzing the proportionality of callosal growth and decline offers valuable insight into lifespan development of structural connectivity between the hemispheres, and suggests consequences for the cognitive development of perception and cognition.

Learning-Challenged Youth Show an Abnormal Relationship Between Fronto-Parietal Myelination and Mathematical Ability

BACKGROUND AND PURPOSE

Differences in the microstructure of fronto-parietal white matter tracts have been associated with mathematical achievement. However, much of the supporting evidence relies on nonspecific diffusion-weighted magnetic resonance imaging, making it difficult to isolate the role of myelin in math ability.

METHODS

We used myelin water imaging to measure brain myelin. We related myelin water fraction (MWF) to Woodcock-Johnson III (WJ-III) basic math scores using region of interest (ROI) and tract-based spatial statistics (TBSS) analyses, in 14 typically developing and 36 learning challenged youth aged 9-17 years.

RESULTS

The ROI analysis found a positive relationship between fronto-parietal MWF and math in typically developing youth, but not in learning challenged youth. The relationship between fronto-parietal MWF and math observed in typically developing youth was fully mediated by age. No group differences in fronto-parietal MWF were found between typically developing and learning challenged youth. TBSS also found no group differences in MWF values. TBSS indicated math-MWF relationships extend beyond fronto-parietal tracts to descending and ascending projection tracts in typically developing youth. TBSS identified math-MWF relationships in the cerebral peduncles of learning challenged youth.

CONCLUSIONS

Our results suggest that in typically developing youth, brain myelination contributes to individual differences in basic math achievement. In contrast, youth with learning challenges appear to have less capacity to leverage myelin to improve math achievement.

Late drug-resistance in mild MTLE: Can it be influenced by preexisting white matter alterations?

OBJECTIVE

To identify early structural alterations preceding the development of drug-resistance in mild mesial temporal lobe epilepsy (mMTLE), a drug-responsive syndrome ideal for investigating epilepsy pathophysiology and potential prognostic markers of long-term clinical outcome, using magnetic resonance imaging (MRI) at baseline and after 12-year follow-up.

METHODS

Since 2002, a total of 55 participants with a baseline diagnosis of mMTLE underwent three-dimensional (3D) T1 1.5T MRI. Based on long-term outcome (follow-up 12 ± 3 years), we identified 39 patients with stable mMTLE (smMTLE) and 16 patients who had developed drug-resistance overtime (refractory MTLE [rMTLE]). At follow-up, 21 smMTLE and 13 rMTLE patients underwent 3T-MRI including diffusion-weighted scans. Structural images were processed using longitudinal voxel-based morphometry and standard Freesurfer analysis. Statistical analyses were carried out accounting for age, age at onset, gender, hippocampal volume, and hippocampal sclerosis (Hs).

RESULTS

Patients presented similar demographic, clinical, and Hs features. White matter volume of the arcuate fasciculi, corticospinal tracts, left retrosplenial cingulum, and left inferior longitudinal fasciculus was reduced only in rMTLE patients before the development of drug-resistance. At follow-up, rMTLE showed decreased fractional anisotropy in the corpus callosum, superior longitudinal fasciculi, and major bundles of the right hemisphere.

SIGNIFICANCE

White matter temporal and extratemporal abnormalities are preexisting in patients with mild MTLE who will develop drug-resistance, independently from the presence of Hs. Thus, these changes might be due to an inherited genetic alteration rather than a subordinate worsening after repeated seizures, multiple antiepileptic drugs, or initial precipitating factors.

Evidence accumulation during perceptual decisions in humans varies as a function of dorsal frontoparietal organization

Animal neurophysiological studies have identified neural signals within dorsal frontoparietal areas that trace a perceptual decision by accumulating sensory evidence over time and trigger action upon reaching a threshold. Although analogous accumulation-to-bound signals are identifiable on extracranial human electroencephalography, their cortical origins remain unknown. Here neural metrics of human evidence accumulation, predictive of the speed of perceptual reports, were isolated using electroencephalography and related to dorsal frontoparietal network (dFPN) connectivity using diffusion and resting-state functional magnetic resonance imaging. The build-up rate of evidence accumulation mediated the relationship between the white matter macrostructure of dFPN pathways and the efficiency of perceptual reports. This association between steeper build-up rates of evidence accumulation and the dFPN was recapitulated in the resting-state networks. Stronger connectivity between dFPN regions is thus associated with faster evidence accumulation and speeded perceptual decisions. Our findings identify an integrated network for perceptual decisions that may be targeted for neurorehabilitation in cognitive disorders.

Educational attainment polygenic scores are associated with cortical total surface area and regions important for language and memory

It is well established that higher cognitive ability is associated with larger brain size. However, individual variation in intelligence exists despite brain size and recent studies have shown that a simple unifactorial view of the neurobiology underpinning cognitive ability is probably unrealistic. Educational attainment (EA) is often used as a proxy for cognitive ability since it is easily measured, resulting in large sample sizes and, consequently, sufficient statistical power to detect small associations. This study investigates the association between three global (total surface area (TSA), intra-cranial volume (ICV) and average cortical thickness) and 34 regional cortical measures with educational attainment using a polygenic scoring (PGS) approach. Analyses were conducted on two independent target samples of young twin adults with neuroimaging data, from Australia (N ​= ​1097) and the USA (N ​= ​723), and found that higher EA-PGS were significantly associated with larger global brain size measures, ICV and TSA (R² ​= ​0.006 and 0.016 respectively, p ​< ​0.001) but not average thickness. At the regional level, we identified seven cortical regions-in the frontal and temporal lobes-that showed variation in surface area and average cortical thickness over-and-above the global effect. These regions have been robustly implicated in language, memory, visual recognition and cognitive processing. Additionally, we demonstrate that these identified brain regions partly mediate the association between EA-PGS and cognitive test performance. Altogether, these findings advance our understanding of the neurobiology that underpins educational attainment and cognitive ability, providing focus points for future research.

The genetics of cortical myelination in young adults and its relationships to cerebral surface area, cortical thickness, and intelligence: A magnetic resonance imaging study of twins and families

The cerebral cortex contains a significant quantity of intracortical myelin, but the genetics of cortical myelination (CM) in humans is not well understood. Relatively novel MRI-derived measures now enable the investigation of cortical myelination in large samples. In this study, we use a genetically-informative neuroimaging sample of 1096 young adult subjects from the Human Connectome Project in order to investigate genetic and environmental variation in CM and its relationships with cerebral surface area (SA) and cortical thickness (CT). We found that genetic factors account for approximately 50% of the observed individual differences in mean cortical myelin, 75% of the variation in total SA, and 85% of the variance in global mean CT. Although significant genetic influences were found throughout the cortex, both CM and SA demonstrated a posterior predominance, with disproportionately strong effects in the parietal and occipital lobes and significantly overlapping heritability maps (p < 0.001). Yet despite showing similar spatial heritability patterns, we found evidence that CM is genetically independent from SA at both global and vertex levels; genetically-mediated relationships between CM and CT were similarly small in magnitude. We also found small but statistically significant genetic associations between NIH Toolbox Total Cognition score and CM in the temporal lobe and insula. SA-cognition and CT-cognition correlations were less widespread compared to CM and both patterns were similar to those reported in prior studies.

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.

Age-Related Differences in Brain Morphology and the Modifiers in Middle-Aged and Older Adults

Brain structural morphology differs with age. This study examined age-differences in surface-based morphometric measures of cortical thickness, volume, and surface area in a well-defined sample of 8137 generally healthy UK Biobank participants aged 45-79 years. We illustrate that the complexity of age-related brain morphological differences may be related to the laminar organization and regional evolutionary history of the cortex, and age of about 60 is a break point for increasing negative associations between age and brain morphology in Alzheimer's disease (AD)-prone areas. We also report novel relationships of age-related cortical differences with individual factors of sex, cognitive functions of fluid intelligence, reaction time and prospective memory, cigarette smoking, alcohol consumption, sleep disruption, genetic markers of apolipoprotein E, brain-derived neurotrophic factor, catechol-O-methyltransferase, and several genome-wide association study loci for AD and further reveal joint effects of cognitive functions, lifestyle behaviors, and education on age-related cortical differences. These findings provide one of the most extensive characterizations of age associations with major brain morphological measures and improve our understanding of normal structural brain aging and its potential modifiers.

Genetic Complexity of Cortical Structure: Differences in Genetic and Environmental Factors Influencing Cortical Surface Area and Thickness

Quantifying the genetic architecture of the cerebral cortex is necessary for understanding disease and changes to the brain across the lifespan. Prior work shows that both surface area (SA) and cortical thickness (CT) are heritable. However, we do not yet understand the extent to which region-specific genetic factors (i.e., independent of global effects) play a dominant role in the regional patterning or inter-regional associations across the cortex. Using a population sample of young adult twins (N = 923), we show that the heritability of SA and CT varies widely across regions, generally independent of measurement error. When global effects are controlled for, we detected a complex pattern of genetically mediated clusters of inter-regional associations, which varied between hemispheres. There were generally weak associations between the SA of different regions, except within the occipital lobe, whereas CT was positively correlated within lobar divisions and negatively correlated across lobes, mostly due to genetic covariation. These findings were replicated in an independent sample of twins and siblings (N = 698) from the Human Connectome Project. The different genetic contributions to SA and CT across regions reveal the value of quantifying sources of covariation to appreciate the genetic complexity of cortical structures.

A review on neuroimaging studies of genetic and environmental influences on early brain development

The past decades witnessed a surge of interest in neuroimaging study of normal and abnormal early brain development. Structural and functional studies of normal early brain development revealed massive structural maturation as well as sequential, coordinated, and hierarchical emergence of functional networks during the infancy period, providing a great foundation for the investigation of abnormal early brain development mechanisms. Indeed, studies of altered brain development associated with either genetic or environmental risks emerged and thrived. In this paper, we will review selected studies of genetic and environmental risks that have been relatively more extensively investigated-familial risks, candidate risk genes, and genome-wide association studies (GWAS) on the genetic side; maternal mood disorders and prenatal drug exposures on the environmental side. Emerging studies on environment-gene interactions will also be reviewed. Our goal was not to perform an exhaustive review of all studies in the field but to leverage some representative ones to summarize the current state, point out potential limitations, and elicit discussions on important future directions.

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.