Sex Differences in the Adult Human Brain: Evidence from 5216 UK Biobank Participants

Convergent structural network and gene signatures for MRgFUS thalamotomy in patients with Parkinson's disease

MRgFUS has just been made available for the 1.7 million Parkinson's disease patients in China. Despite its non-invasive and rapid therapeutic advantages for involuntary tremor, some concerns have emerged about outcomes variability, non-specificity, and side-effects, as little is known about its impact on the long-term plasticity of brain structure. We sought to dissect the characteristics of long-term changes in brain structure caused by MRgFUS lesion and explored potential biological mechanisms. One-year multimodal imaging follow-ups were conducted for nine tremor-dominant Parkinson's disease patients undergoing unilateral MRgFUS thalamotomy. A structural connectivity map was generated for each patient to analyze dynamic changes in brain structure. The human brain transcriptome was extracted and spatially registered for connectivity vulnerability. Genetic functional enrichment analysis was performed and further clarified using in vivo emission computed tomography data. MRgFUS not only abolished tremors but also significantly disrupted the brain network topology. Network-based statistics identified a U-shape MRgFUS-sensitive subnetwork reflective of hand tremor recovery and surgical process, accompanied by relevant cerebral blood flow and gray matter alteration. Using human brain gene expression data, we observed that dopaminergic signatures were responsible for the preferential vulnerability associated with these architectural alterations. Additional PET/SPECT data not only validated these gene signatures, but also suggested that structural alteration was significantly correlated with D1 and D2 receptors, DAT, and F-DOPA measures. There was a long-term dynamic loop between structural alteration and dopaminergic signature for MRgFUS thalamotomy, which may be closely related to the long-term improvements in clinical tremor.

Evaluating effects of sex and age on white matter microstructural alterations in alcohol use disorder: A diffusion tensor imaging study

BACKGROUND

Alterations in white matter microstructure associated with chronic alcohol use have been demonstrated in previous diffusion tensor imaging (DTI) research. However, there is conflicting evidence as to whether such differences are influenced by an individual's biological sex. The purpose of the present study was to investigate the prevalence of sex differences in the white matter microstructure of the brains of individuals with alcohol use disorder (AUD) and healthy controls.

METHODS

One hundred participants with AUD (38 female, aged 21 to 68) participating in the National Institute on Alcohol Abuse and Alcoholism's inpatient treatment program and 98 healthy control participants (52 female) underwent a diffusion-weighted scan. Images collected were processed for each subject individually, and voxelwise, tract-based spatial statistics analysis was conducted to test for differences in the DTI measures of fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD).

RESULTS

A 2-way, between-subjects ANCOVA that tested for differences by group and sex revealed widespread differences between AUD and control subjects, but no interaction between group and sex. Additional analyses exploring demographic and alcohol use variables showed significant impacts of age on white matter microstructure that were more pronounced in individuals with AUD. Plots of FA by age, sex, and group in major white matter tracts suggest a need to explore higher order interactions in larger samples.

CONCLUSIONS

These results bolster recent findings of similar microstructural properties in men and women with AUD but provide a rationale for the consideration of age when investigating the impacts of chronic alcohol use on the brain's white matter.

X-chromosome influences on neuroanatomical variation in humans

The X-chromosome has long been hypothesized to have a disproportionate influence on the brain based on its enrichment for genes that are expressed in the brain and associated with intellectual disability. Here, we verify this hypothesis through partitioned heritability analysis of X-chromosome influences (XIs) on human brain anatomy in 32,256 individuals from the UK Biobank. We first establish evidence for dosage compensation in XIs on brain anatomy-reflecting larger XIs in males compared to females, which correlate with regional sex-biases in neuroanatomical variance. XIs are significantly larger than would be predicted from X-chromosome size for the relative surface area of cortical systems supporting attention, decision-making and motor control. Follow-up association analyses implicate X-linked genes with pleiotropic effects on cognition. Our study reveals a privileged role for the X-chromosome in human neurodevelopment and urges greater inclusion of this chromosome in future genome-wide association studies.

Quantitative imaging features predict spinal tap response in normal pressure hydrocephalus

PURPOSE

Gait improvement following high-volume lumbar puncture (HVLP) and continuous lumbar drain (cLD) is widely used to predict shunt response in patients with suspected normal pressure hydrocephalus (NPH). Here, we investigate differences in MRI volumetric and traditional measures between HVLP/cLD responders and non-responders to identify imaging features that may help predict HVLP/cLD response.

METHODS

Eighty-two patients with suspected NPH were studied retrospectively. Gait testing was performed before and immediately/24 h/72 h after HVLP/cLD. A positive response was defined as improvement in gait post-procedure. Thirty-six responders (26 men; mean age 79.3 ± 6.3) and 46 non-responders (25 men; mean age 77.2 ± 6.1) underwent pre-procedure brain MRI including a 3D T1-weighted sequence. Subcortical regional volumes were segmented using FreeSurfer. After normalizing for total intracranial volume, two-way type III ANCOVA test and chi-square test were used to characterize statistical group differences. Evans' index, callosal angle (CA), and disproportionately enlarged subarachnoid space hydrocephalus were assessed. Multivariable logistic regression models were tested using Akaike information criterion to determine which combination of metrics most accurately predicts HVLP/cLD response.

RESULTS

Responders and non-responders demonstrated no differences in total ventricular and white/gray matter volumes. CA (men only) and third and fourth ventricular volumes were smaller; and hippocampal volume was larger in responders (p < 0.05). Temporal horns volume correlated with degree of improvement in gait velocity in responders (p = 0.0006). The regression model was 76.8% accurate for HVLP/cLD response.

CONCLUSION

CA and third and fourth ventricular volumes and hippocampal volume may serve as potentially useful imaging features that may help predict spinal tap response and hence potentially shunt response.

Regional White Matter Scaling in the Human Brain

Anatomical organization of the primate cortex varies as a function of total brain size, where possession of a larger brain is accompanied by disproportionate expansion of associative cortices alongside a relative contraction of sensorimotor systems. However, equivalent scaling maps are not yet available for regional white matter anatomy. Here, we use three large-scale neuroimaging datasets to examine how regional white matter volume (WMV) scales with interindividual variation in brain volume among typically developing humans (combined N = 2391: 1247 females, 1144 males). We show that WMV scaling is regionally heterogeneous: larger brains have relatively greater WMV in anterior and posterior regions of cortical white matter, as well as the genu and splenium of the corpus callosum, but relatively less WMV in most subcortical regions. Furthermore, regions of positive WMV scaling tend to connect previously-defined regions of positive gray matter scaling in the cortex, revealing a coordinated coupling of regional gray and white matter organization with naturally occurring variations in human brain size. However, we also show that two commonly studied measures of white matter microstructure, fractional anisotropy (FA) and magnetization transfer (MT), scale negatively with brain size, and do so in a manner that is spatially unlike WMV scaling. Collectively, these findings provide a more complete view of anatomic scaling in the human brain, and offer new contexts for the interpretation of regional white matter variation in health and disease.SIGNIFICANCE STATEMENT Recent work has shown that, in humans, regional cortical and subcortical anatomy show systematic changes as a function of brain size variation. Here, we show that regional white matter structures also show brain-size related changes in humans. Specifically, white matter regions connecting higher-order cortical systems are relatively expanded in larger human brains, while subcortical and cerebellar white matter tracts responsible for unimodal sensory or motor functions are relatively contracted. This regional scaling of white matter volume (WMV) is coordinated with regional scaling of cortical anatomy, but is distinct from scaling of white matter microstructure. These findings provide a more complete view of anatomic scaling of the human brain, with relevance for evolutionary, basic, and clinical neuroscience.

Sex differences in brain atrophy and cognitive impairment in Parkinson's disease patients with and without probable rapid eye movement sleep behavior disorder

Background

The presence of rapid eye movement sleep behavior disorder (RBD) contributes to increase cognitive impairment and brain atrophy in Parkinson’s disease (PD), but the impact of sex is unclear. We aimed to investigate sex differences in cognition and brain atrophy in PD patients with and without probable RBD (pRBD).

Methods

Magnetic resonance imaging and cognition data were obtained for 274 participants from the Parkinson's Progression Marker Initiative database: 79 PD with pRBD (PD-pRBD; male/female, 54/25), 126 PD without pRBD (PD-non pRBD; male/female, 73/53), and 69 healthy controls (male/female, 40/29). FreeSurfer was used to obtain volumetric and cortical thickness data.

Results

Males showed greater global cortical and subcortical gray matter atrophy than females in the PD-pRBD group. Significant group-by-sex interactions were found in the pallidum. Structures showing a within-group sex effect in the deep gray matter differed, with significant volume reductions for males in one structure in in PD-non pRBD (brainstem), and three in PD-pRBD (caudate, pallidum and brainstem). Significant group-by-sex interactions were found in Montreal Cognitive Assessment (MoCA) and Symbol Digits Modalities Test (SDMT). Males performed worse than females in MoCA, phonemic fluency and SDMT in the PD-pRBD group.

Conclusion

Male sex is related to increased cognitive impairment and subcortical atrophy in de novo PD-pRBD. Accordingly, we suggest that sex differences are relevant and should be considered in future clinical and translational research.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00415-021-10728-x.

Genetic control of variability in subcortical and intracranial volumes

Sensitivity to external demands is essential for adaptation to dynamic environments, but comes at the cost of increased risk of adverse outcomes when facing poor environmental conditions. Here, we apply a novel methodology to perform genome-wide association analysis of mean and variance in ten key brain features (accumbens, amygdala, caudate, hippocampus, pallidum, putamen, thalamus, intracranial volume, cortical surface area, and cortical thickness), integrating genetic and neuroanatomical data from a large lifespan sample (n = 25,575 individuals; 8-89 years, mean age 51.9 years). We identify genetic loci associated with phenotypic variability in thalamus volume and cortical thickness. The variance-controlling loci involved genes with a documented role in brain and mental health and were not associated with the mean anatomical volumes. This proof-of-principle of the hypothesis of a genetic regulation of brain volume variability contributes to establishing the genetic basis of phenotypic variance (i.e., heritability), allows identifying different degrees of brain robustness across individuals, and opens new research avenues in the search for mechanisms controlling brain and mental health.

Are Sex Differences in Human Brain Structure Associated With Sex Differences in Behavior?

On average, men and women differ in brain structure and behavior, raising the possibility of a link between sex differences in brain and behavior. But women and men are also subject to different societal and cultural norms. We navigated this challenge by investigating variability of sex-differentiated brain structure within each sex. Using data from the Queensland Twin IMaging study (n = 1,040) and Human Connectome Project (n = 1,113), we obtained data-driven measures of individual differences along a male-female dimension for brain and behavior based on average sex differences in brain structure and behavior, respectively. We found a weak association between these brain and behavioral differences, driven by brain size. These brain and behavioral differences were moderately heritable. Our findings suggest that behavioral sex differences are, to some extent, related to sex differences in brain structure but that this is mainly driven by differences in brain size, and causality should be interpreted cautiously.

Deep learning for sex classification in resting-state and task functional brain networks from the UK Biobank

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Applied deep learning to sex classification in UK BioBank fMRI connectomes.

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Deep learning classifies sex better in resting-state than in task fMRI.

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Algorithm to balance out multiple confounds from an fMRI dataset.

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Adapted two deep learning visualization methods to fMRI connectome classification.

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Analyzed role of three brain a priori networks in sex classification.

Classification of whole-brain functional connectivity MRI data with convolutional neural networks (CNNs) has shown promise, but the complexity of these models impedes understanding of which aspects of brain activity contribute to classification. While visualization techniques have been developed to interpret CNNs, bias inherent in the method of encoding abstract input data, as well as the natural variance of deep learning models, detract from the accuracy of these techniques. We introduce a stochastic encoding method in an ensemble of CNNs to classify functional connectomes by sex. We applied our method to resting-state and task data from the UK BioBank, using two visualization techniques to measure the salience of three brain networks involved in task- and resting-states, and their interaction. To regress confounding factors such as head motion, age, and intracranial volume, we introduced a multivariate balancing algorithm to ensure equal distributions of such covariates between classes in our data. We achieved a final AUROC of 0.8459. We found that resting-state data classifies more accurately than task data, with the inner salience network playing the most important role of the three networks overall in classification of resting-state data and connections to the central executive network in task data.

The MRi-Share database: brain imaging in a cross-sectional cohort of 1870 university students

We report on MRi-Share, a multi-modal brain MRI database acquired in a unique sample of 1870 young healthy adults, aged 18-35 years, while undergoing university-level education. MRi-Share contains structural (T1 and FLAIR), diffusion (multispectral), susceptibility-weighted (SWI), and resting-state functional imaging modalities. Here, we described the contents of these different neuroimaging datasets and the processing pipelines used to derive brain phenotypes, as well as how quality control was assessed. In addition, we present preliminary results on associations of some of these brain image-derived phenotypes at the whole brain level with both age and sex, in the subsample of 1722 individuals aged less than 26 years. We demonstrate that the post-adolescence period is characterized by changes in both structural and microstructural brain phenotypes. Grey matter cortical thickness, surface area and volume were found to decrease with age, while white matter volume shows increase. Diffusivity, either radial or axial, was found to robustly decrease with age whereas fractional anisotropy only slightly increased. As for the neurite orientation dispersion and densities, both were found to increase with age. The isotropic volume fraction also showed a slight increase with age. These preliminary findings emphasize the complexity of changes in brain structure and function occurring in this critical period at the interface of late maturation and early ageing.

Neuroanatomical norms in the UK Biobank: The impact of allometric scaling, sex, and age

Few neuroimaging studies are sufficiently large to adequately describe population‐wide variations. This study's primary aim was to generate neuroanatomical norms and individual markers that consider age, sex, and brain size, from 629 cerebral measures in the UK Biobank (N = 40,028). The secondary aim was to examine the effects and interactions of sex, age, and brain allometry—the nonlinear scaling relationship between a region and brain size (e.g., total brain volume)—across cerebral measures. Allometry was a common property of brain volumes, thicknesses, and surface areas (83%) and was largely stable across age and sex. Sex differences occurred in 67% of cerebral measures (median |β| = .13): 37% of regions were larger in males and 30% in females. Brain measures (49%) generally decreased with age, although aging effects varied across regions and sexes. While models with an allometric or linear covariate adjustment for brain size yielded similar significant effects, omitting brain allometry influenced reported sex differences in variance. Finally, we contribute to the reproducibility of research on sex differences in the brain by replicating previous studies examining cerebral sex differences. This large‐scale study advances our understanding of age, sex, and brain allometry's impact on brain structure and provides data for future UK Biobank studies to identify the cerebral regions that covary with specific phenotypes, independently of sex, age, and brain size.

Right-left asymmetry in corticospinal tract microstructure and dexterity are uncoupled in late adulthood

Ageing leads to a decline in white matter microstructure and dexterous function of the hand. In adolescents, it has previously been shown that the degree of right-left asymmetry in the corticospinal tract (CST) is linearly related with right-left asymmetry in dexterity. Here, we tested whether this association is also expressed in older adults. Participants completed a simple circle drawing task with their right and left hand as a measure of dexterity and underwent whole-brain diffusion weighted imaging at 3 Tesla (n = 199; aged 60-72 years). Fractional anisotropy and mean diffusivity of right and left CST were extracted from a manually defined region-of-interest. Linear regression analyses were computed to replicate the analyses in adolescents. Frequentist analyses were complemented with a Bayesian analytical framework. Outcome measures were compared with those previously reported in adolescents (aged 11-16 years). Asymmetries in white matter microstructure of the CST were evident and comparable to the degree of lateralisation observed in adolescence. Similarly, asymmetries in dexterity were evident, but to a lesser degree than in adolescents. Unlike in adolescents, we found no evidence of a linear relationship between asymmetries in CST microstructure and dexterity. Complementary Bayesian regression analysis provided moderate evidence in favour of the null hypothesis, pointing towards a lack of association between the structural and functional measures of right-left asymmetry. Our findings are compatible with the notion that, by late adulthood, a diverging impact of age on white matter structure and dexterous hand function dilutes the structure-function relationship between CST microstructure and manual proficiency that has been reported in adolescents.

Resting-State Functional Connectivity of the Ageing Female Brain-Differences Between Young and Elderly Female Adults on Multislice Short TR rs-fMRI

Introduction: Age-related brain changes are one of the most important world health problems due to the rising lifespan and size of the elderly populations. The aim of the study was to assess the effect of ageing in women on coordinated brain activity between eight resting-state networks.

Material and Methods: The study group comprised 60 healthy female volunteers who were divided into two age groups: younger women (aged 20–30 n = 30) and older women (aged 55–80 n = 30). Resting-state data were collected during a 15 min scan in the eyes-closed condition using a 3T MR scanner. Data were preprocessed and analysed using the CONN toolbox version 19.c. The large-scale network analysis included a priori selected regions of interest of the default mode, the sensorimotor, the visual, the salience, the dorsal attention, the fronto-parietal, the language, and the cerebellar network.

Results: Within the visual, the default mode, the salience, and the sensorimotor network, the intra-network resting-state functional connectivity (RSFC) was significantly higher with increasing age. There was also a significant increase in the inter-network RSFC in older females compared to young females found in the following networks: sensorimotor lateral and salience, salience and language, salience and fronto-parietal, cerebellar anterior and default mode, cerebellar posterior and default mode, visual and sensorimotor lateral, visual and sensorimotor, visual lateral and default mode, language and cerebellar anterior, language and cerebellar posterior, fronto-parietal and cerebellar anterior, dorsal attention and sensorimotor, dorsal attention and default mode, sensorimotor superior, and salience. Compared to young females, elderly women presented bilaterally significantly lower inter-network RSFC of the salience supramarginal gyrus and cerebellar posterior, sensorimotor lateral, and cerebellar anterior network, and sensorimotor lateral and cerebellar posterior as well as sensorimotor superior and cerebellar posterior network.

Conclusion: Increased RSFC between some brain networks including the visual, the default mode, the salience, the sensorimotor, the language, the fronto-parietal, the dorsal attention, and the cerebellar networks in elderly females may function as a compensation mechanism during the ageing process of the brain. To the best of our knowledge, this study is the first to report the importance of increase of cerebellar networks RSFC during healthy female ageing.

Cerebral White Matter Myelination and Relations to Age, Gender, and Cognition: A Selective Review

White matter makes up about fifty percent of the human brain. Maturation of white matter accompanies biological development and undergoes the most dramatic changes during childhood and adolescence. Despite the advances in neuroimaging techniques, controversy concerning spatial, and temporal patterns of myelination, as well as the degree to which the microstructural characteristics of white matter can vary in a healthy brain as a function of age, gender and cognitive abilities still exists. In a selective review we describe methods of assessing myelination and evaluate effects of age and gender in nine major fiber tracts, highlighting their role in higher-order cognitive functions. Our findings suggests that myelination indices vary by age, fiber tract, and hemisphere. Effects of gender were also identified, although some attribute differences to methodological factors or social and learning opportunities. Findings point to further directions of research that will improve our understanding of the complex myelination-behavior relation across development that may have implications for educational and clinical practice.

Associations between long-term psychosis risk, probabilistic category learning, and attenuated psychotic symptoms with cortical surface morphometry

Neuroimaging studies have consistently found structural cortical abnormalities in individuals with schizophrenia, especially in structural hubs. However, it is unclear what abnormalities predate psychosis onset and whether abnormalities are related to behavioral performance and symptoms associated with psychosis risk. Using surface-based morphometry, we examined cortical volume, gyrification, and thickness in a psychosis risk group at long-term risk for developing a psychotic disorder (n = 18; i.e., extreme positive schizotypy plus interview-rated attenuated psychotic symptoms [APS]) and control group (n = 19). Overall, the psychosis risk group exhibited cortical abnormalities in multiple structural hub regions, with abnormalities associated with poorer probabilistic category learning, a behavioral measure strongly associated with psychosis risk. For instance, the psychosis risk group had hypogyria in a right posterior midcingulate cortical hub and left superior parietal cortical hub, as well as decreased volume in a right pericalcarine hub. Morphometric measures in all of these regions were also associated with poorer probabilistic category learning. In addition to decreased right pericalcarine volume, the psychosis risk group exhibited a number of other structural abnormalities in visual network structural hub regions, consistent with previous evidence of visual perception deficits in psychosis risk. Further, severity of APS hallucinations, delusional ideation, and suspiciousness/persecutory ideas were associated with gyrification abnormalities, with all domains associated with hypogyria of the right lateral orbitofrontal cortex. Thus, current results suggest that structural abnormalities, especially in structural hubs, are present in psychosis risk and are associated both with poor learning on a psychosis risk-related task and with APS severity.

Cortical thickness and resting-state cardiac function across the lifespan: A cross-sectional pooled mega-analysis

Understanding the association between autonomic nervous system [ANS] function and brain morphology across the lifespan provides important insights into neurovisceral mechanisms underlying health and disease. Resting-state ANS activity, indexed by measures of heart rate [HR] and its variability [HRV] has been associated with brain morphology, particularly cortical thickness [CT]. While findings have been mixed regarding the anatomical distribution and direction of the associations, these inconsistencies may be due to sex and age differences in HR/HRV and CT. Previous studies have been limited by small sample sizes, which impede the assessment of sex differences and aging effects on the association between ANS function and CT. To overcome these limitations, 20 groups worldwide contributed data collected under similar protocols of CT assessment and HR/HRV recording to be pooled in a mega-analysis (N = 1,218 (50.5% female), mean age 36.7 years (range: 12-87)). Findings suggest a decline in HRV as well as CT with increasing age. CT, particularly in the orbitofrontal cortex, explained additional variance in HRV, beyond the effects of aging. This pattern of results may suggest that the decline in HRV with increasing age is related to a decline in orbitofrontal CT. These effects were independent of sex and specific to HRV; with no significant association between CT and HR. Greater CT across the adult lifespan may be vital for the maintenance of healthy cardiac regulation via the ANS-or greater cardiac vagal activity as indirectly reflected in HRV may slow brain atrophy. Findings reveal an important association between CT and cardiac parasympathetic activity with implications for healthy aging and longevity that should be studied further in longitudinal research.

The Impact of Stress Within and Across Generations: Neuroscientific and Epigenetic Considerations

The impact of stress and trauma on biological systems in humans can be substantial. They can result in epigenetic changes, accelerated brain development and sexual maturation, and predisposition to psychopathology. Such modifications may be accompanied by behavioral, emotional, and cognitive overtones during one's lifetime. Exposure during sensitive periods of neural development may lead to long-lasting effects that may not be affected by subsequent environmental interventions. The cumulative effects of life stressors in an individual may affect offspring's methylome makeup and epigenetic clocks, neurohormonal modulation and stress reactivity, and physiological and reproductive development. While offspring may suffer deleterious effects from parental stress and their own early-life adversity, these factors may also confer traits that prove beneficial and enhance fitness to their own environment. This article synthesizes the data on how stress shapes biological and behavioral dimensions, drawing from preclinical and human models. Advances in this field of knowledge should potentially allow for an improved understanding of how interventions may be increasingly tailored according to individual biomarkers and developmental history.

Associations of perceived adverse lifetime experiences with brain structure in UK Biobank participants

BACKGROUND

Adversity experiences (AEs) are major risk factors for psychiatric illness, and ample evidence suggests that adversity-related changes in brain structure enhance this vulnerability. To achieve greater understanding of the underlying biological pathways, increased convergence among findings is needed. Suggested future directions may benefit from the use of large population samples which may contribute to achieving this goal. We addressed mechanistic pathways by investigating the associations between multiple brain phenotypes and retrospectively reported AEs in early life (child adversity) and adulthood (partner abuse) in a large population sample, using a cross-sectional approach.

METHODS

The UK Biobank resource was used to access imaging-derived phenotypes (IDPs) from 6,751 participants (aged: M = 62.1, SD = 7.2, range = 45-80), together with selected reports of childhood AEs and adult partner abuse. Principal component analysis was used to reduce the dimensionality of the data prior to multivariate tests.

RESULTS

The data showed that participants who reported experiences of childhood emotional abuse ('felt hated by family member as a child') had smaller cerebellar and ventral striatum volumes. This result was also depicted in a random subset of participants; however, we note small effect sizes ( ηp2  < .01), suggestive of modest biological changes.

CONCLUSIONS

Using a large population cohort, this study demonstrates the value of big datasets in the study of adversity and using automatically preprocessed neuroimaging phenotypes. While retrospective and cross-sectional characteristics limit interpretation, this study demonstrates that self-perceived adversity reports, however nonspecific, may still expose neural consequences, identifiable with increased statistical power.

Differential Age Trajectories of White Matter Changes Between Sexes Correlate with Cognitive Performances

Background: Aging is accompanied by a gradual deterioration in multiple cognitive abilities and brain structures. Both cognitive function and white matter (WM) structure are found to be associated with neurodegeneration diseases and correlated with sex during aging. However, it is still unclear whether the brain structural change could be attributable to sex, and how sex would affect cognitive performances during aging. Materials and Methods: Diffusion magnetic resonance imaging (MRI) scans were performed on 1127 healthy participants (age range: 21-89) at a single site. The age trajectories of the WM tract microstructure were delineated to estimate the turning age and changing rate between sexes. The canonical correlation analysis and moderated mediation analysis were used to examine the relationship between sex-linked WM tracts and cognitive performances. Results: The axon intactness and demyelination of sex-linked tracts during aging were multifaceted. Sex-linked tracts in females peak around 5 years later than those in males but change significantly faster after the turning age. Projection and association tracts (e.g., corticospinal tracts and parahippocampal cingulum) contributed to a significant decrease in visuospatial functions (VS) and executive functions (E). We discovered that there is a stronger indirect effect of sex-linked tracts on cognitive functions in females than in males. Conclusion: Our findings suggest that the vulnerable projection and association tracts in females may induce negative impacts on integrating multiple functions, which results in a faster decrease in VS and E.

Sex Differences in Lifespan Trajectories and Variability of Human Sulcal and Gyral Morphology

Sex differences in the development and aging of human sulcal morphology have been understudied. We charted sex differences in trajectories and inter-individual variability of global sulcal depth, width, and length, pial surface area, exposed (hull) gyral surface area, unexposed sulcal surface area, cortical thickness, gyral span, and cortex volume across the lifespan in a longitudinal sample (700 scans, 194 participants 2 scans, 104 three scans, age range: 16-70 years) of neurotypical males and females. After adjusting for brain volume, females had thicker cortex and steeper thickness decline until age 40 years; trajectories converged thereafter. Across sexes, sulcal shortening was faster before age 40, while sulcal shallowing and widening were faster thereafter. Although hull area remained stable, sulcal surface area declined and was more strongly associated with sulcal shortening than with sulcal shallowing and widening. Males showed greater variability for cortex volume and lower variability for sulcal width. Our findings highlight the association between loss of sulcal area, notably through sulcal shortening, with cortex volume loss. Studying sex differences in lifespan trajectories may improve knowledge of individual differences in brain development and the pathophysiology of neuropsychiatric conditions.

[A review on the application of UK Biobank in neuroimaging]

UK Biobank (UKB) is a forward-looking epidemiological project with over 500, 000 people aged 40 to 69, whose image extension project plans to re-invite 100, 000 participants from UKB to perform multimodal brain magnetic resonance imaging. Large-scale multimodal neuroimaging combined with large amounts of phenotypic and genetic data provides great resources to conduct brain health-related research. This article provides an in-depth overview of UKB in the field of neuroimaging. Firstly, neuroimage collection and imaging-derived phenotypes are summarized. Secondly, typical studies of UKB in neuroimaging areas are introduced, which include cardiovascular risk factors, regulatory factors, brain age prediction, normality, successful and morbid brain aging, environmental and genetic factors, cognitive ability and gender. Lastly, the open challenges and future directions of UKB are discussed. This article has the potential to open up a new research field for the prevention and treatment of neurological diseases.

Population variability in social brain morphology for social support, household size and friendship satisfaction

The social brain hypothesis proposes that the complexity of human brains has coevolved with increasing complexity of social interactions in primate societies. The present study explored the possible relationships between brain morphology and the richness of more intimate 'inner' and wider 'outer' social circles by integrating Bayesian hierarchical modeling with a large cohort sample from the UK Biobank resource (n = 10 000). In this way, we examined population volume effects in 36 regions of the 'social brain', ranging from lower sensory to higher associative cortices. We observed strong volume effects in the visual sensory network for the group of individuals with satisfying friendships. Further, the limbic network displayed several brain regions with substantial volume variations in individuals with a lack of social support. Our population neuroscience approach thus showed that distinct networks of the social brain show different patterns of volume variations linked to the examined social indices.

Association Between Visceral Fat and Brain Cortical Thickness in the Elderly: A Neuroimaging Study

Background

Despite emerging evidence suggesting that visceral fat may play a major role in obesity-induced neurodegeneration, little evidence exists on the association between visceral fat and brain cortical thickness in the elderly.

Purpose

We aimed to examine the association between abdominal fat and brain cortical thickness in a Korean elderly population.

Methods

This cross-sectional study included elderly individuals without dementia (n = 316). Areas of visceral fat and subcutaneous fat (cm²) were estimated from computed tomography scans. Regional cortical thicknesses (mm) were obtained by analyzing brain magnetic resonance images. Given the inverted U-shaped relationship between visceral fat area and global cortical thickness (examined using a generalized additive model), visceral fat area was categorized into quintiles, with the middle quintile being the reference group. A generalized linear model was built to explore brain regions associated with visceral fat. The same approach was used for subcutaneous fat.

Results

The mean (standard deviation) age was 67.6 (5.0) years. The highest quintile (vs. the middle quintile) group of visceral fat area had reduced cortical thicknesses in the global [β = -0.04 mm, standard error (SE) = 0.02 mm, p = 0.004], parietal (β = -0.04 mm, SE = 0.02 mm, p = 0.01), temporal (β = -0.05 mm, SE = 0.02 mm, p = 0.002), cingulate (β = -0.06 mm, SE = 0.02 mm, p = 0.01), and insula lobes (β = -0.06 mm, SE = 0.03 mm, p = 0.02). None of the regional cortical thicknesses significantly differed between the highest and the middle quintile groups of subcutaneous fat area.

Conclusion

The findings suggest that a high level of visceral fat, but not subcutaneous fat, is associated with a reduced cortical thickness in the elderly.

New insights into the dynamic development of the cerebral cortex in childhood and adolescence: Integrating macro- and microstructural MRI findings

Through dynamic transactional processes between genetic and environmental factors, childhood and adolescence involve reorganization and optimization of the cerebral cortex. The cortex and its development plays a crucial role for prototypical human cognitive abilities. At the same time, many common mental disorders appear during these critical phases of neurodevelopment. Magnetic resonance imaging (MRI) can indirectly capture several multifaceted changes of cortical macro- and microstructure, of high relevance to further our understanding of the neural foundation of cognition and mental health. Great progress has been made recently in mapping the typical development of cortical morphology. Moreover, newer less explored MRI signal intensity and specialized quantitative T2 measures have been applied to assess microstructural cortical development. We review recent findings of typical postnatal macro- and microstructural development of the cerebral cortex from early childhood to young adulthood. We cover studies of cortical volume, thickness, area, gyrification, T1-weighted (T1w) tissue contrasts such a grey/white matter contrast, T1w/T2w ratio, magnetization transfer and myelin water fraction. Finally, we integrate imaging studies with cortical gene expression findings to further our understanding of the underlying neurobiology of the developmental changes, bridging the gap between ex vivo histological- and in vivo MRI studies.

Pathway-Specific Genetic Risk for Alzheimer's Disease Differentiates Regional Patterns of Cortical Atrophy in Older Adults

Brain aging is highly variable and represents a challenge to delimit aging from disease processes. Moreover, genetic factors may influence both aging and disease. Here we focused on this issue and investigated effects of multiple genetic loci previously identified to be associated with late-onset Alzheimer's disease (AD) on brain structure of older adults from a population sample. We calculated a genetic risk score (GRS) using genome-wide significant single-nucleotide polymorphisms from genome-wide association studies of AD and tested its effect on cortical thickness (CT). We observed a common pattern of cortical thinning (right inferior frontal, left posterior temporal, medial occipital cortex). To identify CT changes by specific biological processes, we subdivided the GRS effect according to AD-associated pathways and performed follow-up analyses. The common pattern from the main analysis was further differentiated by pathway-specific effects yielding a more bilateral pattern. Further findings were located in the superior parietal and mid/anterior cingulate regions representing 2 unique pathway-specific patterns. All patterns, except the superior parietal pattern, were influenced by apolipoprotein E. Our step-wise approach revealed atrophy patterns that partially resembled imaging findings in early stages of AD. Our study provides evidence that genetic burden for AD contributes to structural brain variability in normal aging.

Sex Chromosome Dosage Effects on White Matter Structure in the Human Brain

Sex chromosome aneuploidies, a group of neurogenetic conditions characterized by aberrant sex chromosome dosage (SCD), are associated with increased risks for psychopathology as well as alterations in gray matter structure. However, we still lack a comprehensive understanding of potential SCD-associated changes in white matter structure, or knowledge of how these changes might relate to known alterations in gray matter anatomy. Thus, here, we use voxel-based morphometry on structural neuroimaging data to provide the first comprehensive maps of regional white matter volume (WMV) changes across individuals with varying SCD (n = 306). We show that mounting X- and Y-chromosome dosage are both associated with widespread WMV decreases, including in cortical, subcortical, and cerebellar tracts, as well as WMV increases in the genu of the corpus callosum and posterior thalamic radiation. We also correlate X- and Y-chromosome-linked WMV changes in certain regions to measures of internalizing and externalizing psychopathology. Finally, we demonstrate that SCD-driven WMV changes show a coordinated coupling with SCD-driven gray matter volume changes. These findings represent the most complete maps of X- and Y-chromosome effects on human white matter to date, and show how such changes connect to psychopathological symptoms and gray matter anatomy.

Brain-based sex differences in autism spectrum disorder across the lifespan: A systematic review of structural MRI, fMRI, and DTI findings

Females with autism spectrum disorder (ASD) have been long overlooked in neuroscience research, but emerging evidence suggests they show distinct phenotypic trajectories and age-related brain differences. Sex-related biological factors (e.g., hormones, genes) may play a role in ASD etiology and have been shown to influence neurodevelopmental trajectories. Thus, a lifespan approach is warranted to understand brain-based sex differences in ASD. This systematic review on MRI-based sex differences in ASD was conducted to elucidate variations across the lifespan and inform biomarker discovery of ASD in females We identified articles through two database searches. Fifty studies met criteria and underwent integrative review. We found that regions expressing replicable sex-by-diagnosis differences across studies overlapped with regions showing sex differences in neurotypical cohorts. Furthermore, studies investigating age-related brain differences across a broad age-span suggest distinct neurodevelopmental patterns in females with ASD. Qualitative comparison across youth and adult studies also supported this hypothesis. However, many studies collapsed across age, which may mask differences. Furthermore, accumulating evidence supports the female protective effect in ASD, although only one study examined brain circuits implicated in "protection." When synthesized with the broader literature, brain-based sex differences in ASD may come from various sources, including genetic and endocrine processes involved in brain "masculinization" and "feminization" across early development, puberty, and other lifespan windows of hormonal transition. Furthermore, sex-related biology may interact with peripheral processes, in particular the stress axis and brain arousal system, to produce distinct neurodevelopmental patterns in males and females with ASD. Future research on neuroimaging-based sex differences in ASD would benefit from a lifespan approach in well-controlled and multivariate studies. Possible relationships between behavior, sex hormones, and brain development in ASD remain largely unexamined.

Sex Matters: A Multivariate Pattern Analysis of Sex- and Gender-Related Neuroanatomical Differences in Cis- and Transgender Individuals Using Structural Magnetic Resonance Imaging

Univariate analyses of structural neuroimaging data have produced heterogeneous results regarding anatomical sex- and gender-related differences. The current study aimed at delineating and cross-validating brain volumetric surrogates of sex and gender by comparing the structural magnetic resonance imaging data of cis- and transgender subjects using multivariate pattern analysis. Gray matter (GM) tissue maps of 29 transgender men, 23 transgender women, 35 cisgender women, and 34 cisgender men were created using voxel-based morphometry and analyzed using support vector classification. Generalizability of the models was estimated using repeated nested cross-validation. For external validation, significant models were applied to hormone-treated transgender subjects (n = 32) and individuals diagnosed with depression (n = 27). Sex was identified with a balanced accuracy (BAC) of 82.6% (false discovery rate [pFDR] < 0.001) in cisgender, but only with 67.5% (pFDR = 0.04) in transgender participants indicating differences in the neuroanatomical patterns associated with sex in transgender despite the major effect of sex on GM volume irrespective of the self-identification as a woman or man. Gender identity and gender incongruence could not be reliably identified (all pFDR > 0.05). The neuroanatomical signature of sex in cisgender did not interact with depressive features (BAC = 74.7%) but was affected by hormone therapy when applied in transgender women (P < 0.001).

Intra- and interhemispheric symmetry of subcortical brain structures: a volumetric analysis in the aging human brain

Here, we address the hemispheric interdependency of subcortical structures in the aging human brain. In particular, we investigated whether subcortical volume variations can be explained by the adjacency of structures in the same hemisphere or are due to the interhemispheric development of mirror subcortical structures in the brain. Seven subcortical structures in each hemisphere were automatically segmented in a large sample of 3312 magnetic resonance imaging (MRI) studies of elderly individuals in their 70s and 80s. We performed Eigenvalue analysis, and found that anatomic volumes in the limbic system and basal ganglia show similar statistical dependency whether considered in the same hemisphere (intrahemispherically) or different hemispheres (interhemispherically). Our results indicate that anatomic bilaterality of subcortical volumes is preserved in the aging human brain, supporting the hypothesis that coupling between non-adjacent subcortical structures might act as a mechanism to compensate for the deleterious effects of aging.

Structural volume and cortical thickness differences between males and females in cognitively normal, cognitively impaired and Alzheimer's dementia population

We investigated differences due to sex in brain structural volume and cortical thickness in older cognitively normal (N=742), cognitively impaired (MCI; N=540) and Alzheimer's Dementia (AD; N=402) individuals from the ADNI and AIBL datasets (861 Males and 823 Females). General linear models were used to control the effect of relevant covariates including age, intracranial volume, magnetic resonance imaging (MRI) scanner field strength and scanner types. Significant volumetric differences due to sex were observed within different cortical and subcortical regions of the cognitively normal group. The number of significantly different regions was reduced in the MCI group, and no region remained different in the AD group. Cortical thickness was overall thinner in males than females in the cognitively normal group, and likewise, the differences due to sex were reduced in the MCI and AD groups. These findings were sustained after including cerebrospinal fluid (CSF) Tau and phosphorylated tau (pTau) as additional covariates.

Classification-Biased Apparent Brain Age for the Prediction of Alzheimer's Disease

Machine Learning methods are often adopted to infer useful biomarkers for the early diagnosis of many neurodegenerative diseases and, in general, of neuroanatomical ageing. Some of these methods estimate the subject age from morphological brain data, which is then indicated as “brain age”. The difference between such a predicted brain age and the actual chronological age of a subject can be used as an indication of a pathological deviation from normal brain ageing. An important use of the brain age model as biomarker is the prediction of Alzheimer's disease (AD) from structural Magnetic Resonance Imaging (MRI). Many different machine learning approaches have been applied to this specific predictive task, some of which have achieved high accuracy at the expense of the descriptiveness of the model. This work investigates an appropriate combination of data science techniques and linear models to provide, at the same time, high accuracy and good descriptiveness. The proposed method is based on a data workflow that include typical data science methods, such as outliers detection, feature selection, linear regression, and logistic regression. In particular, a novel inductive bias is introduced in the regression model, which is aimed at improving the accuracy and the specificity of the classification task. The method is compared to other machine learning approaches for AD classification based on morphological brain data with and without the use of the brain age, including Support Vector Machines and Deep Neural Networks. This study adopts brain MRI scans of 1, 901 subjects which have been acquired from three repositories (ADNI, AIBL, and IXI). A predictive model based only on the proposed apparent brain age and the chronological age has an accuracy of 88% and 92%, respectively, for male and female subjects, in a repeated cross-validation analysis, thus achieving a comparable or superior performance than state of the art machine learning methods. The advantage of the proposed method is that it maintains the morphological semantics of the input space throughout the regression and classification tasks. The accurate predictive model is also highly descriptive and can be used to generate potentially useful insights on the predictions.

Considering Sex as a Biological Variable in Basic and Clinical Studies: An Endocrine Society Scientific Statement

In May 2014, the National Institutes of Health (NIH) stated its intent to "require applicants to consider sex as a biological variable (SABV) in the design and analysis of NIH-funded research involving animals and cells." Since then, proposed research plans that include animals routinely state that both sexes/genders will be used; however, in many instances, researchers and reviewers are at a loss about the issue of sex differences. Moreover, the terms sex and gender are used interchangeably by many researchers, further complicating the issue. In addition, the sex or gender of the researcher might influence study outcomes, especially those concerning behavioral studies, in both animals and humans. The act of observation may change the outcome (the "observer effect") and any experimental manipulation, no matter how well-controlled, is subject to it. This is nowhere more applicable than in physiology and behavior. The sex of established cultured cell lines is another issue, in addition to aneuploidy; chromosomal numbers can change as cells are passaged. Additionally, culture medium contains steroids, growth hormone, and insulin that might influence expression of various genes. These issues often are not taken into account, determined, or even considered. Issues pertaining to the "sex" of cultured cells are beyond the scope of this Statement. However, we will discuss the factors that influence sex and gender in both basic research (that using animal models) and clinical research (that involving human subjects), as well as in some areas of science where sex differences are routinely studied. Sex differences in baseline physiology and associated mechanisms form the foundation for understanding sex differences in diseases pathology, treatments, and outcomes. The purpose of this Statement is to highlight lessons learned, caveats, and what to consider when evaluating data pertaining to sex differences, using 3 areas of research as examples; it is not intended to serve as a guideline for research design.

Customization of Diet May Promote Exercise and Improve Mental Wellbeing in Mature Adults: The Role of Exercise as a Mediator

Diet, dietary practices and exercise are modifiable risk factors for individuals living with mental distress. However, these relationships are intricate and multilayered in such a way that individual factors may influence mental health differently when combined within a pattern. Additionally, two important factors that need to be considered are gender and level of brain maturity. Therefore, it is essential to assess these modifiable risk factors based on gender and age group. The purpose of the study was to explore the combined and individual relationships between food groups, dietary practices and exercise to appreciate their association with mental distress in mature men and women. Adults 30 years and older were invited to complete the food–mood questionnaire. The anonymous questionnaire link was circulated on several social media platforms. A multi-analyses approach was used. A combination of data mining techniques, namely, a mediation regression analysis, the K-means clustering and principal component analysis as well as Spearman’s rank–order correlation were used to explore these research questions. The results suggest that women’s mental health has a higher association with dietary factors than men. Mental distress and exercise frequency were associated with different dietary and lifestyle patterns, which support the concept of customizing diet and lifestyle factors to improve mental wellbeing.

Sex differences in brain modular organization in chronic pain

ABSTRACT

Men and women can exhibit different pain sensitivities, and many chronic pain conditions are more prevalent in one sex. Although there is evidence of sex differences in the brain, it is not known whether there are sex differences in the organization of large-scale functional brain networks in chronic pain. Here, we used graph theory with modular analysis and machine-learning of resting-state-functional magnetic resonance imaging data from 220 participants: 155 healthy controls and 65 individuals with chronic low back pain due to ankylosing spondylitis, a form of arthritis. We found an extensive overlap in the graph partitions with the major brain intrinsic systems (ie, default mode, central, visual, and sensorimotor modules), but also sex-specific network topological characteristics in healthy people and those with chronic pain. People with chronic pain exhibited higher cross-network connectivity, and sex-specific nodal graph properties changes (ie, hub disruption), some of which were associated with the severity of the chronic pain condition. Females exhibited atypically higher functional segregation in the mid cingulate cortex and subgenual anterior cingulate cortex and lower connectivity in the network with the default mode and frontoparietal modules, whereas males exhibited stronger connectivity with the sensorimotor module. Classification models on nodal graph metrics could classify an individual's sex and whether they have chronic pain with high accuracies (77%-92%). These findings highlight the organizational abnormalities of resting-state-brain networks in people with chronic pain and provide a framework to consider sex-specific pain therapeutics.

Population-based body-brain mapping links brain morphology with anthropometrics and body composition

Understanding complex body-brain processes and the interplay between adipose tissue and brain health is important for understanding comorbidity between psychiatric and cardiometabolic disorders. We investigated associations between brain structure and anthropometric and body composition measures using brain magnetic resonance imaging (MRI; n = 24,728) and body MRI (n = 4973) of generally healthy participants in the UK Biobank. We derived regional and global measures of brain morphometry using FreeSurfer and tested their association with (i) anthropometric measures, and (ii) adipose and muscle tissue measured from body MRI. We identified several significant associations with small effect sizes. Anthropometric measures showed negative, nonlinear, associations with cerebellar/cortical gray matter, and brain stem structures, and positive associations with ventricular volumes. Subcortical structures exhibited mixed effect directionality, with strongest positive association for accumbens. Adipose tissue measures, including liver fat and muscle fat infiltration, were negatively associated with cortical/cerebellum structures, while total thigh muscle volume was positively associated with brain stem and accumbens. Regional investigations of cortical area, thickness, and volume indicated widespread and largely negative associations with anthropometric and adipose tissue measures, with an opposite pattern for thigh muscle volume. Self-reported diabetes, hypertension, or hypercholesterolemia were associated with brain structure. The findings provide new insight into physiological body-brain associations suggestive of shared mechanisms between cardiometabolic risk factors and brain health. Whereas the causality needs to be determined, the observed patterns of body-brain relationships provide a foundation for understanding the underlying mechanisms linking psychiatric disorders with obesity and cardiovascular disease, with potential for the development of new prevention strategies.

Abnormal subgenual anterior cingulate circuitry is unique to women but not men with chronic pain

The subgenual anterior cingulate cortex (sgACC) plays an important role in pain modulation. We previously demonstrated sex differences in sgACC functional connectivity (FC) in healthy individuals. Given that many chronic pain conditions show sex differences in prevalence, here we tested the hypothesis that people with chronic pain exhibit a sex-specific pattern of abnormal sgACC FC. We acquired resting-state functional magnetic resonance imaging data from 156 (82 W: 74 M) healthy participants and 38 (19 W: 19 M) people with chronic low back pain resulting from ankylosing spondylitis, a condition that predominantly affects men. We confirmed that there are sex differences in sgACC FC in our large cohort of healthy adults; women had greater sgACC FC with the precuneus, a key node of the default mode network, and men had greater sgACC FC with the posterior insula and the operculum. Next, we identified an interaction effect between sex and pain status (healthy/chronic pain) for sgACC FC. Within the chronic pain group, women had greater sgACC FC than men to the default mode and sensorimotor networks. Compared to healthy women, women with chronic pain also had greater sgACC FC to the precuneus and lower FC to the hippocampus and frontal regions. No differences in sgACC FC were seen in men with vs without chronic pain. Our findings indicate that abnormal sgACC circuitry is unique to women but not men with ankylosing spondylitis-related chronic pain. These sex differences may impact the benefit of therapeutics that target the sgACC for chronic pain.

Sex-Specific Interaction Between Cortisol and Striato-Limbic Responses to Psychosocial Stress

Although women and men differ in psychological and endocrine stress responses as well as in the prevalence rates of stress-related disorders, knowledge on sex differences regarding stress regulation in the brain is scarce. Therefore, we performed an in-depth analysis of data from 67 healthy participants (31 women, taking oral contraceptives), who were exposed to the ScanSTRESS paradigm in a functional magnetic resonance imaging study. Changes in cortisol, affect, heart rate and neural activation in response to psychosocial stress were examined in women and men as well as potential sex-specific interactions between stress response domains. Stress exposure led to significant cortisol increases, with men exhibiting higher levels than women. Depending on sex, cortisol elevations were differently associated with stress-related responses in striato-limbic structures: higher increases were associated with activations in men but with deactivations in women. Regarding affect or heart rate responses, no sex differences emerged. Although women and men differ in their overall stress reactivity, our findings do not support the idea of distinct neural networks as the base of this difference. Instead, we found differential stress reactions for women and men in identical structures. We propose considering quantitative predictors such as sex-specific cortisol increases when exploring neural response differences of women and men.

Sex and dependence related neuroanatomical differences in regular cannabis users: findings from the ENIGMA Addiction Working Group

Males and females show different patterns of cannabis use and related psychosocial outcomes. However, the neuroanatomical substrates underlying such differences are poorly understood. The aim of this study was to map sex differences in the neurobiology (as indexed by brain volumes) of dependent and recreational cannabis use. We compared the volume of a priori regions of interest (i.e., amygdala, hippocampus, nucleus accumbens, insula, orbitofrontal cortex (OFC), anterior cingulate cortex and cerebellum) between 129 regular cannabis users (of whom 70 were recreational users and 59 cannabis dependent) and 114 controls recruited from the ENIGMA Addiction Working Group, accounting for intracranial volume, age, IQ, and alcohol and tobacco use. Dependent cannabis users, particularly females, had (marginally significant) smaller volumes of the lateral OFC and cerebellar white matter than recreational users and controls. In dependent (but not recreational) cannabis users, there was a significant association between female sex and smaller volumes of the cerebellar white matter and OFC. Volume of the OFC was also predicted by monthly standard drinks. No significant effects emerged the other brain regions of interest. Our findings warrant future multimodal studies that examine if sex and cannabis dependence are specific key drivers of neurobiological alterations in cannabis users. This, in turn, could help to identify neural pathways specifically involved in vulnerable cannabis users (e.g., females with cannabis dependence) and inform individually tailored neurobiological targets for treatment.

Sex differences in dopamine integrity and brain structure among healthy older adults: Relationships to episodic memory

Normal brain aging is a multidimensional process that includes deterioration in various brain structures and functions, with large heterogeneity in patterns and rates of decline. Sex differences have been reported for various cognitive and brain parameters, but little is known in relation to neuromodulatory aspects of brain aging. We examined sex differences in dopamine D2-receptor (D2DR) availability in relation to episodic memory, but also, grey-matter volumes, white-matter lesions, and cerebral perfusion in healthy older adults (n = 181, age: 64-68 years) from the Cognition, Brain, and Aging study. Women had higher D2DR availability in midbrain and left caudate and putamen, as well as superior episodic memory performance. Controlling for left caudate D2DR availability attenuated sex differences in memory performance. In men, lower left caudate D2DR levels were associated with lower cortical perfusion and higher burden of white-matter lesions, as well as with episodic memory performance. However, sex was not a significant moderator of the reported links to D2DR levels. Our findings suggest that sex differences in multiple associations among DA receptor availability, vascular factors, and structural connectivity contribute to sex differences in episodic memory. Future longitudinal studies need to corroborate these patterns by lead-lag associations. This manuscript is part of the Special Issue entitled 'Cognitive Neuroscience of Healthy and Pathological Aging' edited by Drs. M. N. Rajah, S. Belleville, and R. Cabeza. This article is part of the Virtual Special Issue titled COGNITIVE NEUROSCIENCE OF HEALTHY AND PATHOLOGICAL AGING. The full issue can be found on ScienceDirect at https://www.sciencedirect.com/journal/neurobiology-of-aging/special-issue/105379XPWJP.

The Relationship between Intelligence and Divergent Thinking-A Meta-Analytic Update

This paper provides a meta-analytic update on the relationship between intelligence and divergent thinking (DT), as research on this topic has increased, and methods have diversified since Kim’s meta-analysis in 2005. A three-level meta-analysis was used to analyze 849 correlation coefficients from 112 studies with an overall N = 34,610. The overall effect showed a significant positive correlation of r = .25. This increase of the correlation as compared to Kim’s prior meta-analytic findings could be attributed to the correction of attenuation because a difference between effect sizes prior-Kim vs. post-Kim was non-significant. Different moderators such as scoring methods, instructional settings, intelligence facets, and task modality were tested together with theoretically relevant interactions between some of these factors. These moderation analyses showed that the intelligence–DT relationship can be higher (up to r = .31–.37) when employing test-like assessments coupled with be-creative instructions, and considering DT originality scores. The facet of intelligence (g vs. g_f vs. g_c) did not affect the correlation between intelligence and DT. Furthermore, we found two significant sample characteristics: (a) average sample age was positively associated with the intelligence–DT correlation, and (b) the intelligence–DT correlation decreased for samples with increasing percentages of females in the samples. Finally, inter-moderator correlations were checked to take potential confounding into account, and also publication bias was assessed. This meta-analysis provides a comprehensive picture of current research and possible research gaps. Theoretical implications, as well as recommendations for future research, are discussed.

Prediction of brain age and cognitive age: Quantifying brain and cognitive maintenance in aging

The concept of brain maintenance refers to the preservation of brain integrity in older age, while cognitive reserve refers to the capacity to maintain cognition in the presence of neurodegeneration or aging-related brain changes. While both mechanisms are thought to contribute to individual differences in cognitive function among older adults, there is currently no "gold standard" for measuring these constructs. Using machine-learning methods, we estimated brain and cognitive age based on deviations from normative aging patterns in the Whitehall II MRI substudy cohort (N = 537, age range = 60.34-82.76), and tested the degree of correspondence between these constructs, as well as their associations with premorbid IQ, education, and lifestyle trajectories. In line with established literature highlighting IQ as a proxy for cognitive reserve, higher premorbid IQ was linked to lower cognitive age independent of brain age. No strong evidence was found for associations between brain or cognitive age and lifestyle trajectories from midlife to late life based on latent class growth analyses. However, post hoc analyses revealed a relationship between cumulative lifestyle measures and brain age independent of cognitive age. In conclusion, we present a novel approach to characterizing brain and cognitive maintenance in aging, which may be useful for future studies seeking to identify factors that contribute to brain preservation and cognitive reserve mechanisms in older age.

Aging-Sensitive Networks Within the Human Structural Connectome Are Implicated in Late-Life Cognitive Declines

BACKGROUND

Aging-related cognitive decline is a primary risk factor for Alzheimer's disease and related dementias. More precise identification of the neurobiological bases of cognitive decline in aging populations may provide critical insights into the precursors of late-life dementias.

METHODS

Using structural and diffusion brain magnetic resonance imaging data from the UK Biobank (n = 8185; age range, 45-78 years), we examined aging of regional gray matter volumes (nodes) and white matter structural connectivity (edges) within 9 well-characterized networks of interest in the human brain connectome. In the independent Lothian Birth Cohort 1936 (n = 534; all 73 years of age), we tested whether aging-sensitive connectome elements are enriched for key domains of cognitive function before and after controlling for early-life cognitive ability.

RESULTS

In the UK Biobank, age differences in individual connectome elements corresponded closely with principal component loadings reflecting connectome-wide integrity (|rnodes| = .420; |redges| = .583), suggesting that connectome aging occurs on broad dimensions of variation in brain architecture. In the Lothian Birth Cohort 1936, composite indices of node integrity were predictive of all domains of cognitive function, whereas composite indices of edge integrity were associated specifically with processing speed. Elements within the central executive network were disproportionately predictive of late-life cognitive function relative to the network's small size. Associations with processing speed and visuospatial ability remained after controlling for childhood cognitive ability.

CONCLUSIONS

These results implicate global dimensions of variation in the human structural connectome in aging-related cognitive decline. The central executive network may demarcate a constellation of elements that are centrally important to age-related cognitive impairments.

The gender-binary cycle: the perpetual relations between a biological-essentialist view of gender, gender ideology, and gender-labelling and sorting

Gender inequality is one of the most pressing issues of our time. A core factor that feeds gender inequality is people's gender ideology-a set of beliefs about the proper order of society in terms of the roles women and men should fill. We argue that gender ideology is shaped, in large parts, by the way people make sense of gender differences. Specifically, people often think of gender differences as expressions of a predetermined biology, and of men and women as different 'kinds'. We describe work suggesting that thinking of gender differences in this biological-essentialist way perpetuates a non-egalitarian gender ideology. We then review research that refutes the hypothesis that men and women are different 'kinds' in terms of brain function, hormone levels and personality characteristics. Next, we describe how the organization of the environment in a gender-binary manner, together with cognitive processes of categorization drive a biological-essentialist view of gender differences. We then describe the self-perpetuating relations, which we term the gender-binary cycle, between a biological-essentialist view of gender differences, a non-egalitarian gender ideology and a binary organization of the environment along gender lines. Finally, we consider means of intervention at different points in this cycle. This article is part of the theme issue 'The political brain: neurocognitive and computational mechanisms'.

Individual variation underlying brain age estimates in typical development

Typical brain development follows a protracted trajectory throughout childhood and adolescence. Deviations from typical growth trajectories have been implicated in neurodevelopmental and psychiatric disorders. Recently, the use of machine learning algorithms to model age as a function of structural or functional brain properties has been used to examine advanced or delayed brain maturation in healthy and clinical populations. Termed 'brain age', this approach often relies on complex, nonlinear models that can be difficult to interpret. In this study, we use model explanation methods to examine the cortical features that contribute to brain age modelling on an individual basis. In a large cohort of n = 768 typically-developing children (aged 3-21 years), we build models of brain development using three different machine learning approaches. We employ SHAP, a model-agnostic technique to identify sample-specific feature importance, to identify regional cortical metrics that explain errors in brain age prediction. We find that, on average, brain age prediction and the cortical features that explain model predictions are consistent across model types and reflect previously reported patterns of regions brain development. However, while several regions are found to contribute to brain age prediction error, we find little spatial correspondence between individual estimates of feature importance, even when matched for age, sex and brain age prediction error. We also find no association between brain age error and cognitive performance in this typically-developing sample. Overall, this study shows that, while brain age estimates based on cortical development are relatively robust and consistent across model types and preprocessing strategies, significant between-subject variation exists in the features that explain erroneous brain age predictions on an individual level.

Perinatal Dietary Polyunsaturated Fatty Acids in Brain Development, Role in Neurodevelopmental Disorders

n-3 and n-6 polyunsaturated fatty acids (PUFAs) are essential fatty acids that are provided by dietary intake. Growing evidence suggests that n-3 and n-6 PUFAs are paramount for brain functions. They constitute crucial elements of cellular membranes, especially in the brain. They are the precursors of several metabolites with different effects on inflammation and neuron outgrowth. Overall, long-chain PUFAs accumulate in the offspring brain during the embryonic and post-natal periods. In this review, we discuss how they accumulate in the developing brain, considering the maternal dietary supply, the polymorphisms of genes involved in their metabolism, and the differences linked to gender. We also report the mechanisms linking their bioavailability in the developing brain, their transfer from the mother to the embryo through the placenta, and their role in brain development. In addition, data on the potential role of altered bioavailability of long-chain n-3 PUFAs in the etiologies of neurodevelopmental diseases, such as autism, attention deficit and hyperactivity disorder, and schizophrenia, are reviewed.

Generalization of memory-related brain function in asymptomatic older women with a family history of late onset Alzheimer's Disease: Results from the PREVENT-AD Cohort

Late-onset Alzheimer's disease (AD) disproportionately affects women compared to men. Episodic memory decline is one of the earliest and most pronounced deficits observed in AD. However, it remains unclear whether sex influences episodic memory-related brain function in cognitively intact older adults at risk of developing AD. Here we used task-based multivariate partial least squares analysis to examine sex differences in episodic memory-related brain activity and brain activity-behavior correlations in a matched sample of cognitively intact older women and men with a family history of AD from the PREVENT-AD cohort study in Montreal, Canada (M_age=63.03±3.78; M_education=15.41±3.40). We observed sex differences in task-related brain activity and brain activity-behavior correlations during the encoding of object-location associative memories and object-only item memory, and the retrieval of object only item memories. Our findings suggest a generalization of episodic memory-related brain activation and performance in women compared to men. Follow up analyses should test for sex differences in the relationship between brain activity patterns and performance longitudinally, in association with risk factors for AD development. This article is part of the Virtual Special Issue titled COGNITIVE NEUROSCIENCE OF HEALTHY AND PATHOLOGICAL AGING. The full issue can be found on ScienceDirect at https://www.sciencedirect.com/journal/neurobiology-of-aging/special-issue/105379XPWJP.

Sex-related Differences in Stress Reactivity and Cingulum White Matter

The prefrontal cortex and limbic system are important components of the neural circuit that underlies stress and anxiety. These brain regions are connected by white matter tracts that support neural communication including the cingulum, uncinate fasciculus, and the fornix/stria-terminalis. Determining the relationship between stress reactivity and these white matter tracts may provide new insight into factors that underlie stress susceptibility and resilience. Therefore, the present study investigated sex differences in the relationship between stress reactivity and generalized fractional anisotropy (GFA) of the white matter tracts that link the prefrontal cortex and limbic system. Diffusion weighted images were collected and deterministic tractography was completed in 104 young adults (55 men, 49 women; mean age = 18.87 SEM = 0.08). Participants also completed self-report questionnaires (e.g., Trait Anxiety) and donated saliva (later assayed for cortisol) before, during, and after the Trier Social Stress Test. Results revealed that stress reactivity (area under the curve increase in cortisol) and GFA of the cingulum bundle varied by sex. Specifically, men demonstrated greater cortisol reactivity and greater GFA within the cingulum than women. Further, an interaction between sex, stress reactivity, and cingulum GFA was observed in which men demonstrated a positive relationship while women demonstrated a negative relationship between GFA and cortisol reactivity. Finally, trait anxiety was positively associated with the GFA of the fornix/stria terminalis - the white matter pathways that connect the hippocampus/amygdala to the hypothalamus. These findings advance our understanding of factors that underlie individual differences in stress reactivity.

Sex difference in cerebral blood flow and cerebral glucose metabolism: an activation-likelihood estimation meta-analysis

OBJECTIVES

Sex differences exist in a variety of aspects including neurochemicals as well as behavioral traits of cognition, language, and aggression. We performed a meta-analysis of studies using a coordinate-based technique of activation-likelihood estimation (ALE) to identify the pooled estimated effect of sex difference.

METHODS

We performed a systematic search of MEDLINE and EMBASE for English-language publications using the keywords of 'positron emission tomography (PET)', 'single-photon emission computed tomography (SPECT)', and 'sex'. A threshold of uncorrected P < 0.001 (minimum volume of 200 mm3) was applied to the resulting ALE map.

RESULTS

Cerebral blood flow (CBF) in right precuneus, left superior temporal gyrus, left inferior temporal, left inferior frontal gyrus, right cerebellar tonsil, and right middle temporal gyrus was higher in females than males. CBF in left anterior cingulate was higher in males than females. Whereas, the cerebral metabolic rate for glucose (CMRglu) in left thalamus, left cingulate gyrus, right inferior parietal lobule, left medial frontal gyrus, right middle frontal gyrus, right midbrain, and left inferior parietal lobule was higher in females than males. However, there was no brain region that showed higher CMRglu in males than females.

CONCLUSION

Regional CBF and CMRglu from PET and SPECT showed the difference between males and females.