Evaluating age-and gender-related changes in brain volumes in normal adult using synthetic magnetic resonance imaging.

OBJECTIVE: Normal aging is associated with brain volume change, and brain segmentation can be performed within an acceptable scan time using synthetic magnetic resonance imaging (MRI). This study aimed to investigate the brain volume changes in healthy adult according to age and gender, and provide age- and gender-specific reference values using synthetic MRI. METHODS: A total of 300 healthy adults (141 males, median age 48; 159 females, median age 50) were underwent synthetic MRI on 3.0 T. Brain parenchymal volume (BPV), gray matter volume (GMV), white matter volume (WMV), myelin volume (MYV), and cerebrospinal fluid volume (CSFV) were calculated using synthetic MRI software. These volumes were normalized by intracranial volume to normalized GMV (nGMV), normalized WMV (nWMV), normalized MYV (nMYV), normalized BPV (nBPV), and normalized CSFV (nCSFV). The normalized brain volumes were plotted against age in both males and females, and a curve fitting model that best explained the age dependence of brain volume was identified. The normalized brain volumes were compared between different age and gender groups. RESULTS: The approximate curves of nGMV, nWMV, nCSFV, nBPV, and nMYV were best fitted by quadratic curves. The nBPV decreased monotonously through all ages in both males and females, while the changes of nCSFV showed the opposite trend. The nWMV and nMYV in both males and females increased gradually and then decrease with age. In early adulthood (20s), nWMV and nMYV in males were lower and peaked later than that in females (p < .005). The nGMV in both males and females decreased in the early adulthood until the 30s and then remains stable. A significant decline in nWMV, nBPV, and nMYV was noted in the 60s (Turkey test, p < .05). CONCLUSIONS: Our study provides age- and gender-specific reference values of brain volumes using synthetic MRI, which could be objective tools for discriminating brain disorders from healthy brains.

Volumetric study on sheep brain using stereology technique.

Three-dimensional morphometric data better show the structural and functional characteristics of the brain. The objective of this study was to estimate the volume of the cerebral structures of the sheep using design-based stereology. The brains of five sheep were used, fixed in formalin 10% and embedded in agar 6%. An average of 10-12 slab was obtained from each brain. All slabs were stained using Mulligan's method and photographs were recorded. The volume of the brain and its structures were estimated using the Cavalieri's estimator and the point counting system. The total volume was 70604.8 ± 132.45 mm3. The volume fractions of the grey and white matters were calculated as 42.55 ± 0.21% and 24.23 ± 0.51% of the whole brain, respectively. The fractional volume of the caudate nucleus and claustrum were estimated at 2.39 ± 0.08% and at 1.008 ± 0.057% of total brain volume. The volumes of corpus callosum, internal capsule and external capsule were 1.24 ± 0.053%, 3.63 ± 0.22% and 0.698 ± 0.049% of total cerebral volume, respectively. These data could help improve the veterinary comparative neuroanatomy knowledge and development of experimental studies in the field.

Neuroanatomical correlates of musicianship in left-handers.

BACKGROUND: Left-handedness is a condition that reverses the typical left cerebral dominance of motor control to an atypical right dominance. The impact of this distinct control - and its associated neuroanatomical peculiarities - on other cognitive functions such as music processing or playing a musical instrument remains unexplored. Previous studies in right-handed population have linked musicianship to a larger volume in the (right) auditory cortex and a larger volume in the (right) arcuate fasciculus. RESULTS: In our study, we reveal that left-handed musicians (n = 55), in comparison to left-handed non-musicians (n = 75), exhibit a larger gray matter volume in both the left and right Heschl's gyrus, critical for auditory processing. They also present a higher number of streamlines across the anterior segment of the right arcuate fasciculus. Importantly, atypical hemispheric lateralization of speech (notably prevalent among left-handers) was associated to a rightward asymmetry of the AF, in contrast to the leftward asymmetry exhibited by the typically lateralized. CONCLUSIONS: These findings suggest that left-handed musicians share similar neuroanatomical characteristics with their right-handed counterparts. However, atypical lateralization of speech might potentiate the right audiomotor pathway, which has been associated with musicianship and better musical skills. This may help explain why musicians are more prevalent among left-handers and shed light on their cognitive advantages.

Diffusion-tensor-imaging 1-year-old and 2-year-old infant brain atlases with comprehensive gray and white matter labels.

Human infancy is marked by fastest postnatal brain structural changes. It also coincides with the onset of many neurodevelopmental disorders. Atlas-based automated structure labeling has been widely used for analyzing various neuroimaging data. However, the relatively large and nonlinear neuroanatomical differences between infant and adult brains can lead to significant offsets of the labeled structures in infant brains when adult brain atlas is used. Age-specific 1- and 2-year-old brain atlases covering all major gray and white matter (GM and WM) structures with diffusion tensor imaging (DTI) and structural MRI are critical for precision medicine for infant population yet have not been established. In this study, high-quality DTI and structural MRI data were obtained from 50 healthy children to build up three-dimensional age-specific 1- and 2-year-old brain templates and atlases. Age-specific templates include a single-subject template as well as two population-averaged templates from linear and nonlinear transformation, respectively. Each age-specific atlas consists of 124 comprehensively labeled major GM and WM structures, including 52 cerebral cortical, 10 deep GM, 40 WM, and 22 brainstem and cerebellar structures. When combined with appropriate registration methods, the established atlases can be used for highly accurate automatic labeling of any given infant brain MRI. We demonstrated that one can automatically and effectively delineate deep WM microstructural development from 3 to 38 months by using these age-specific atlases. These established 1- and 2-year-old infant brain DTI atlases can advance our understanding of typical brain development and serve as clinical anatomical references for brain disorders during infancy.

Choir singing is associated with enhanced structural connectivity across the adult lifespan.

The global ageing of populations calls for effective, ecologically valid methods to support brain health across adult life. Previous evidence suggests that music can promote white matter (WM) microstructure and grey matter (GM) volume while supporting auditory and cognitive functioning and emotional well-being as well as counteracting age-related cognitive decline. Adding a social component to music training, choir singing is a popular leisure activity among older adults, but a systematic account of its potential to support healthy brain structure, especially with regard to ageing, is currently missing. The present study used quantitative anisotropy (QA)-based diffusion MRI connectometry and voxel-based morphometry to explore the relationship of lifetime choir singing experience and brain structure at the whole-brain level. Cross-sectional multiple regression analyses were carried out in a large, balanced sample (N = 95; age range 21-88) of healthy adults with varying levels of choir singing experience across the whole age range and within subgroups defined by age (young, middle-aged, and older adults). Independent of age, choir singing experience was associated with extensive increases in WM QA in commissural, association, and projection tracts across the brain. Corroborating previous work, these overlapped with language and limbic networks. Enhanced corpus callosum microstructure was associated with choir singing experience across all subgroups. In addition, choir singing experience was selectively associated with enhanced QA in the fornix in older participants. No associations between GM volume and choir singing were found. The present study offers the first systematic account of amateur-level choir singing on brain structure. While no evidence for counteracting GM atrophy was found, the present evidence of enhanced structural connectivity coheres well with age-typical structural changes. Corroborating previous behavioural studies, the present results suggest that regular choir singing holds great promise for supporting brain health across the adult life span.

Multimodal neural correlates of dispositional resilience among healthy individuals.

Resilient individuals are less likely to develop psychiatric disorders despite extreme psychological distress. This study investigated the multimodal structural neural correlates of dispositional resilience among healthy individuals. Participants included 92 healthy individuals. The Korean version of the Connor-Davidson Resilience Scale and other psychological measures were used. Gray matter volumes (GMVs), cortical thickness, local gyrification index (LGI), and white matter (WM) microstructures were analyzed using voxel-based morphometry, FreeSurfer, and tract-based spatial statistics, respectively. Higher resilient individuals showed significantly higher GMVs in the inferior frontal gyrus (IFG), increased LGI in the insula, and lower fractional anisotropy values in the superior longitudinal fasciculus II (SLF II). These resilience's neural correlates were associated with good quality of life in physical functioning or general health and low levels of depression. Therefore, the GMVs in the IFG, LGI in the insula, and WM microstructures in the SLF II can be associated with resilience that contributes to emotional regulation, empathy, and social cognition.

Dissecting unique and common variance across body and brain health indicators using age prediction.

Ageing is a heterogeneous multisystem process involving different rates of decline in physiological integrity across biological systems. The current study dissects the unique and common variance across body and brain health indicators and parses inter-individual heterogeneity in the multisystem ageing process. Using machine-learning regression models on the UK Biobank data set (N = 32,593, age range 44.6-82.3, mean age 64.1 years), we first estimated tissue-specific brain age for white and gray matter based on diffusion and T1-weighted magnetic resonance imaging (MRI) data, respectively. Next, bodily health traits, including cardiometabolic, anthropometric, and body composition measures of adipose and muscle tissue from bioimpedance and body MRI, were combined to predict 'body age'. The results showed that the body age model demonstrated comparable age prediction accuracy to models trained solely on brain MRI data. The correlation between body age and brain age predictions was 0.62 for the T1 and 0.64 for the diffusion-based model, indicating a degree of unique variance in brain and bodily ageing processes. Bayesian multilevel modelling carried out to quantify the associations between health traits and predicted age discrepancies showed that higher systolic blood pressure and higher muscle-fat infiltration were related to older-appearing body age compared to brain age. Conversely, higher hand-grip strength and muscle volume were related to a younger-appearing body age. Our findings corroborate the common notion of a close connection between somatic and brain health. However, they also suggest that health traits may differentially influence age predictions beyond what is captured by the brain imaging data, potentially contributing to heterogeneous ageing rates across biological systems and individuals.

The Important Role of the Right Dorsolateral Prefrontal Cortex in Conflict Adaptation: A Combined Voxel-Based Morphometry and Continuous Theta Burst Stimulation Study.

Humans can flexibly adjust their executive control to resolve conflicts. Conflict adaptation and conflict resolution are crucial aspects of conflict processing. Functional neuroimaging studies have associated the dorsolateral prefrontal cortex (DLPFC) with conflict processing, but its causal role remains somewhat controversial. Moreover, the neuroanatomical basis of conflict processing has not been thoroughly examined. In this study, the Stroop task, a well-established measure of conflict, was employed to investigate (1) the neuroanatomical basis of conflict resolution and conflict adaptation with the voxel-based morphometry analysis, (2) the causal role of DLPFC in conflict processing with the application of the continuous theta burst stimulation to DLPFC. The results revealed that the Stroop effect was correlated to the gray matter volume of the precuneus, postcentral gyrus, and cerebellum, and the congruency sequence effect was correlated to the gray matter volume of superior frontal gyrus, postcentral gyrus, and lobule paracentral gyrus. These findings indicate the neuroanatomical basis of conflict resolution and adaptation. In addition, the continuous theta burst stimulation over the right DLPFC resulted in a significant reduction in the Stroop effect of RT after congruent trials compared with vertex stimulation and a significant increase in the Stroop effect of accuracy rate after incongruent trials than congruent trials, demonstrating the causal role of right DLPFC in conflict adaptation. Moreover, the DLPFC stimulation did not affect the Stroop effect of RT and accuracy rate. Overall, our study offers further insights into the neural mechanisms underlying conflict resolution and adaptation.

Sex, gender diversity, and brain structure in early adolescence.

There remains little consensus about the relationship between sex and brain structure, particularly in early adolescence. Moreover, few pediatric neuroimaging studies have analyzed both sex and gender as variables of interest-many of which included small sample sizes and relied on binary definitions of gender. The current study examined gender diversity with a continuous felt-gender score and categorized sex based on X and Y allele frequency in a large sample of children ages 9-11 years old (N = 7195). Then, a statistical model-building approach was employed to determine whether gender diversity and sex independently or jointly relate to brain morphology, including subcortical volume, cortical thickness, gyrification, and white matter microstructure. Additional sensitivity analyses found that male versus female differences in gyrification and white matter were largely accounted for by total brain volume, rather than sex per se. The model with sex, but not gender diversity, was the best-fitting model in 60.1% of gray matter regions and 61.9% of white matter regions after adjusting for brain volume. The proportion of variance accounted for by sex was negligible to small in all cases. While models including felt-gender explained a greater amount of variance in a few regions, the felt-gender score alone was not a significant predictor on its own for any white or gray matter regions examined. Overall, these findings demonstrate that at ages 9-11 years old, sex accounts for a small proportion of variance in brain structure, while gender diversity is not directly associated with neurostructural diversity.

The anatomical structure of sex differences in trust propensity: A voxel-based morphometry study.

Trust is a key component of human relationships. Sex differences in trust behavior have been elucidated by parental investment theory and social role theory, attributing men's higher trust propensity to their increased engagement in physically and socially risky activities aimed at securing additional resources. Although sex differences in trust behavior exist and the neuropsychological signatures of trust are known, the underlying anatomical structure of sex differences is still unexplored. Our study aimed to investigate the anatomical structure of sex differences in trust behavior toward strangers (i.e., trust propensity, TP) by employing voxel-based morphometry (VBM) in a sample of healthy young adults. We collected behavioral data for TP as measured with participants in the role of trustors completing the one-shot trust game (TG) with anonymous partners as trustees. We conducted primary region of interest (ROI) and exploratory whole-brain (WB) VBM analyses of high-resolution structural images to test for the association between TP and regional gray matter volume (GMV) associated with sex differences. Confirming previous studies, our behavioral results demonstrated that men trusted more than women during the one-shot TG. Our WB analysis showed a greater GMV related to TP in men than women in the precuneus (PreC), whereas our ROI analysis in regions of the default-mode network (dorsomedial prefrontal cortex [dmPFC], PreC, superior temporal gyrus) to simulate the partner's trustworthiness, central-executive network (ventrolateral PFC) to implement a calculus-based trust strategy, and action-perception network (precentral gyrus) to performance cost-benefit calculations, as proposed by a neuropsychoeconomic model of trust. Our findings advance the neuropsychological understanding of sex differences in TP, which has implications for interpersonal partnerships, financial transactions, and societal engagements.

Narcissus reflected: Grey and white matter features joint contribution to the default mode network in predicting narcissistic personality traits.

Despite the clinical significance of narcissistic personality, its neural bases have not been clarified yet, primarily because of methodological limitations of the previous studies, such as the low sample size, the use of univariate techniques and the focus on only one brain modality. In this study, we employed for the first time a combination of unsupervised and supervised machine learning methods, to identify the joint contributions of grey matter (GM) and white matter (WM) to narcissistic personality traits (NPT). After preprocessing, the brain scans of 135 participants were decomposed into eight independent networks of covarying GM and WM via parallel ICA. Subsequently, stepwise regression and Random Forest were used to predict NPT. We hypothesized that a fronto-temporo parietal network, mainly related to the default mode network, may be involved in NPT and associated WM regions. Results demonstrated a distributed network that included GM alterations in fronto-temporal regions, the insula and the cingulate cortex, along with WM alterations in cerebellar and thalamic regions. To assess the specificity of our findings, we also examined whether the brain network predicting narcissism could also predict other personality traits (i.e., histrionic, paranoid and avoidant personalities). Notably, this network did not predict such personality traits. Additionally, a supervised machine learning model (Random Forest) was used to extract a predictive model for generalization to new cases. Results confirmed that the same network could predict new cases. These findings hold promise for advancing our understanding of personality traits and potentially uncovering brain biomarkers associated with narcissism.

Challenges in replication: Does amygdala gray matter volume relate to social network size?

In this work, we tried to replicate and extend prior research on the relationship between social network size and the volume of the amygdala. We focused on the earliest evidence for this relationship (Bickart et al., Nature Neuroscience 14(2), 163-164, 2011) and another methodologically unique study that often is cited as a replication (Kanai et al., Proceedings of the Royal Society B: Biological Sciences, 279(1732), 1327-1334, 2012). Despite their tight link in the literature, we argue that Kanai et al. (Proceedings of the Royal Society B: Biological Sciences, 279(1732), 1327-1334, 2012) is not a replication of Bickart et al. Nature Neuroscience 14(2), 163-164 (2011), because it uses different morphometric measurements. We collected data from 128 participants on a 7-Tesla MRI and examined variations in gray matter volume (GMV) in the amygdala and its nuclei. We found inconclusive support for a correlation between measures of real-world social network and amygdala GMV, with small effect sizes and only anecdotal evidence for a positive relationship. We found support for the absence of a correlation between measures of online social network and amygdala GMV. We discuss different challenges faced in replication attempts for small effects, as initially reported in these two studies, and suggest that the results would be most helpful in the context of estimation and future meta-analytical efforts. Our findings underscore the value of a narrow approach in replication of brain-behavior relationships, one that is focused enough to investigate the specifics of what is measured. This approach can provide a complementary perspective to the more popular "thematic" alternative, in which conclusions are often broader but where conclusions may become disconnected from the evidence.

Normative spatiotemporal fetal brain maturation with satisfactory development at 2 years.

Maturation of the human fetal brain should follow precisely scheduled structural growth and folding of the cerebral cortex for optimal postnatal function1. We present a normative digital atlas of fetal brain maturation based on a prospective international cohort of healthy pregnant women2, selected using World Health Organization recommendations for growth standards3. Their fetuses were accurately dated in the first trimester, with satisfactory growth and neurodevelopment from early pregnancy to 2 years of age4,5. The atlas was produced using 1,059 optimal quality, three-dimensional ultrasound brain volumes from 899 of the fetuses and an automated analysis pipeline6-8. The atlas corresponds structurally to published magnetic resonance images9, but with finer anatomical details in deep grey matter. The between-study site variability represented less than 8.0% of the total variance of all brain measures, supporting pooling data from the eight study sites to produce patterns of normative maturation. We have thereby generated an average representation of each cerebral hemisphere between 14 and 31 weeks' gestation with quantification of intracranial volume variability and growth patterns. Emergent asymmetries were detectable from as early as 14 weeks, with peak asymmetries in regions associated with language development and functional lateralization between 20 and 26 weeks' gestation. These patterns were validated in 1,487 three-dimensional brain volumes from 1,295 different fetuses in the same cohort. We provide a unique spatiotemporal benchmark of fetal brain maturation from a large cohort with normative postnatal growth and neurodevelopment.

Texture-based brain networks for characterization of healthy subjects from MRI.

Brain networks have been widely used to study the relationships between brain regions based on their dynamics using, e.g. fMRI or EEG, and to characterize their real physical connections using DTI. However, few studies have investigated brain networks derived from structural properties; and those have been based on cortical thickness or gray matter volume. The main objective of this work was to investigate the feasibility of obtaining useful information from brain networks derived from structural MRI, using texture features. We also wanted to verify if texture brain networks had any relation with established functional networks. T1-MR images were segmented using AAL and texture parameters from the gray-level co-occurrence matrix were computed for each region, for 760 subjects. Individual texture networks were used to evaluate the structural connections between regions of well-established functional networks; assess possible gender differences; investigate the dependence of texture network measures with age; and single out brain regions with different texture-network characteristics. Although around 70% of texture connections between regions belonging to the default mode, attention, and visual network were greater than the mean connection value, this effect was small (only between 7 and 15% of these connections were larger than one standard deviation), implying that texture-based morphology does not seem to subside function. This differs from cortical thickness-based morphology, which has been shown to relate to functional networks. Seventy-five out of 86 evaluated regions showed significant (ANCOVA, p < 0.05) differences between genders. Forty-four out of 86 regions showed significant (ANCOVA, p < 0.05) dependence with age; however, the R2 indicates that this is not a linear relation. Thalamus and putamen showed a very unique texture-wise structure compared to other analyzed regions. Texture networks were able to provide useful information regarding gender and age-related differences, as well as for singling out specific brain regions. We did not find a morphological texture-based subsidy for the evaluated functional brain networks. In the future, this approach will be extended to neurological patients to investigate the possibility of extracting biomarkers to help monitor disease evolution or treatment effectiveness.

Neuroanatomical asymmetry in the canine brain.

The brains of humans and non-human primates exhibit left/right asymmetries in grey matter morphology, white matter connections, and functional responses. These asymmetries have been implicated in specialized behavioral adaptations such as language, tool use, and handedness. Left/right asymmetries are also observed in behavioral tendencies across the animal kingdom, suggesting a deep evolutionary origin for the neural mechanisms underlying lateralized behavior. However, it is still unclear to what extent brain asymmetries supporting lateralized behaviors are present in other large-brained animals outside the primate order. Canids and other carnivorans evolved large, complex brains independently and convergently with primates, and exhibit lateralized behaviors. Therefore, domestic dogs offer an opportunity to address this question. We examined T2-weighted MRI images of 62 dogs from 33 breeds, opportunistically collected from a veterinary MRI scanner from dogs who were referred for neurological examination but were not found to show any neuropathology. Volumetrically asymmetric regions of gray matter included portions of the temporal and frontal cortex, in addition to portions of the cerebellum, brainstem, and other subcortical regions. These results are consistent with the perspective that asymmetry may be a common feature underlying the evolution of complex brains and behavior across clades, and provide neuro-organizational information that is likely relevant to the growing field of canine behavioral neuroscience.

Neuroanatomical substrates of maximizing tendency in decision-making: a voxel-based morphometric study.

Maximizing tendency is a central decision-making concept that has increasingly drawn attention from the scientific community. It refers to individuals' predisposition to look for the best option instead of settling for something that merely passes an internal threshold of acceptability. Although this maximizing strategy intuitively increases individual benefits, it also has been linked to various negative outcomes, including decreased well-being and low life satisfaction, and it varies considerably across populations. However, the neuroanatomical characteristics underlying this heterogeneity remain poorly understood. To address this knowledge gap, a 13-item Maximization Scale and magnetic resonance imaging technique were respectively used in this study to estimate individual maximizing tendency and structural morphological information on a sample of healthy adults (n = 69). Furthermore, voxel-based morphometry (VBM) analysis was conducted to investigate the associations between gray matter volume (GMV) and maximizing tendency through univariate and multivariate pattern analysis (MVPA). Univariate analysis did not determine an association between maximizing tendency and whole-brain GMV; by contrast, MVPA revealed that maximizing tendency could be successfully predicted by the GMVs of the right inferior frontal gyrus (IFG), right insula, and right cerebellum. These findings suggest the critical role of the morphological characteristics of the cortical-subcortical circuitry in individuals' maximizing tendency.

Cerebral Cortex Changes in Basketball Players.

BACKGROUND: Plastic changes to brain structure and function have been reported in elite athletes of various sports. Interestingly, different regions of the brain were engaged according to the type of sports analyzed. Our laboratory reported no difference in total cerebellar volume of basketball players compared to that in the control group using the manual segmentation method. Further detailed analyses showed that elite basketball players had increased volume of the striatum and vermian lobules VI-VII of the cerebellum. We analyzed the brain magnetic resonance imaging (MRI) of basketball players to understand their cerebral cortical plasticity through automatic analysis tools for MRI. METHODS: Brain MRI data were collected from 19 male university basketball players and 20 age-, sex-, and height-matched control groups. In order to understand the changes in the cerebral cortices of basketball players, we employed automated MRI brain analysis techniques, including voxel-based morphometry (VBM) and surface-based morphometry (SBM). RESULTS: VBM showed increased gray and white matter volume in both precentral gyri, paracentral lobules and increased gray matter volume in the right anterior superior temporal gyrus. SBM revealed a left dominant increase in both pericentral gyri. Fractal dimensional analysis showed an increase in the area of both precentral gyri, the left subcallosal gyrus, and the right posterior cingulate gyrus. These results suggest a significant role not only for the primary motor cortex, but also for the cingulate gyrus during basketball. CONCLUSION: Plastic changes of both precentral gyri, the pericentral area, paracentral lobules, and the right superior temporal gyrus were observed in elite basketball players. There was a strong increase of fractal complexity in both precentral gyri and a weak increase in the right posterior cingulate gyrus and left collateral gyrus. In this study, plastic regions linked to functional neuroanatomy were related to the competence required to play basketball.

Long-term association of pregnancy and maternal brain structure: the Rotterdam Study.

The peripartum period is the highest risk interval for the onset or exacerbation of psychiatric illness in women's lives. Notably, pregnancy and childbirth have been associated with short-term structural and functional changes in the maternal human brain. Yet the long-term effects of pregnancy on maternal brain structure remain unknown. We investigated a large population-based cohort to examine the association between parity and brain structure. In total, 2,835 women (mean age 65.2 years; all free from dementia, stroke, and cortical brain infarcts) from the Rotterdam Study underwent magnetic resonance imaging (1.5 T) between 2005 and 2015. Associations of parity with global and lobar brain tissue volumes, white matter microstructure, and markers of vascular brain disease were examined using regression models. We found that parity was associated with a larger global gray matter volume (ß = 0.14, 95% CI = 0.09-0.19), a finding that persisted following adjustment for sociodemographic factors. A non-significant dose-dependent relationship was observed between a higher number of childbirths and larger gray matter volume. The gray matter volume association with parity was globally proportional across lobes. No associations were found regarding white matter volume or integrity, nor with markers of cerebral small vessel disease. The current findings suggest that pregnancy and childbirth are associated with robust long-term changes in brain structure involving a larger global gray matter volume that persists for decades. Future studies are warranted to further investigate the mechanism and physiological relevance of these differences in brain morphology.

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

BACKGROUND: Substantial evidence acknowledges the complex gene-environment interplay impacting brain development and learning. Intergenerational neuroimaging allows the assessment of familial transfer effects on brain structure, function and behavior by investigating neural similarity in caregiver-child dyads. METHODS: Neural similarity in the human reading network was assessed through well-used measures of brain structure (i.e., surface area (SA), gyrification (lG), sulcal morphology, gray matter volume (GMV) and cortical thickness (CT)) in 69 mother-child dyads (children's age~11 y). Regions of interest for the reading network included left-hemispheric inferior frontal gyrus, inferior parietal lobe and fusiform gyrus. Mother-child similarity was quantified by correlation coefficients and familial specificity was tested by comparison to random adult-child dyads. Sulcal morphology analyses focused on occipitotemporal sulcus interruptions and similarity was assessed by chi-square goodness of fit. RESULTS: Significant structural brain similarity was observed for mother-child dyads in the reading network for lG, SA and GMV (r = 0.349/0.534/0.542, respectively), but not CT. Sulcal morphology associations were non-significant. Structural brain similarity in lG, SA and GMV were specific to mother-child pairs. Furthermore, structural brain similarity for SA and GMV was higher compared to CT. CONCLUSION: Intergenerational neuroimaging techniques promise to enhance our knowledge of familial transfer effects on brain development and disorders.

Mapping brain asymmetry in health and disease through the ENIGMA consortium.

Left-right asymmetry of the human brain is one of its cardinal features, and also a complex, multivariate trait. Decades of research have suggested that brain asymmetry may be altered in psychiatric disorders. However, findings have been inconsistent and often based on small sample sizes. There are also open questions surrounding which structures are asymmetrical on average in the healthy population, and how variability in brain asymmetry relates to basic biological variables such as age and sex. Over the last 4 years, the ENIGMA-Laterality Working Group has published six studies of gray matter morphological asymmetry based on total sample sizes from roughly 3,500 to 17,000 individuals, which were between one and two orders of magnitude larger than those published in previous decades. A population-level mapping of average asymmetry was achieved, including an intriguing fronto-occipital gradient of cortical thickness asymmetry in healthy brains. ENIGMA's multi-dataset approach also supported an empirical illustration of reproducibility of hemispheric differences across datasets. Effect sizes were estimated for gray matter asymmetry based on large, international, samples in relation to age, sex, handedness, and brain volume, as well as for three psychiatric disorders: autism spectrum disorder was associated with subtly reduced asymmetry of cortical thickness at regions spread widely over the cortex; pediatric obsessive-compulsive disorder was associated with altered subcortical asymmetry; major depressive disorder was not significantly associated with changes of asymmetry. Ongoing studies are examining brain asymmetry in other disorders. Moreover, a groundwork has been laid for possibly identifying shared genetic contributions to brain asymmetry and disorders.