Effects of different intracranial volume correction methods on univariate sex differences in grey matter volume and multivariate sex prediction

Systematic evaluation with practical guidelines for single-cell and spatially resolved transcriptomics data simulation under multiple scenarios

BACKGROUND

Single-cell RNA sequencing (scRNA-seq) and spatially resolved transcriptomics (SRT) have led to groundbreaking advancements in life sciences. To develop bioinformatics tools for scRNA-seq and SRT data and perform unbiased benchmarks, data simulation has been widely adopted by providing explicit ground truth and generating customized datasets. However, the performance of simulation methods under multiple scenarios has not been comprehensively assessed, making it challenging to choose suitable methods without practical guidelines.

RESULTS

We systematically evaluated 49 simulation methods developed for scRNA-seq and/or SRT data in terms of accuracy, functionality, scalability, and usability using 152 reference datasets derived from 24 platforms. SRTsim, scDesign3, ZINB-WaVE, and scDesign2 have the best accuracy performance across various platforms. Unexpectedly, some methods tailored to scRNA-seq data have potential compatibility for simulating SRT data. Lun, SPARSim, and scDesign3-tree outperform other methods under corresponding simulation scenarios. Phenopath, Lun, Simple, and MFA yield high scalability scores but they cannot generate realistic simulated data. Users should consider the trade-offs between method accuracy and scalability (or functionality) when making decisions. Additionally, execution errors are mainly caused by failed parameter estimations and appearance of missing or infinite values in calculations. We provide practical guidelines for method selection, a standard pipeline Simpipe ( https://github.com/duohongrui/simpipe ; https://doi.org/10.5281/zenodo.11178409 ), and an online tool Simsite ( https://www.ciblab.net/software/simshiny/ ) for data simulation.

CONCLUSIONS

No method performs best on all criteria, thus a good-yet-not-the-best method is recommended if it solves problems effectively and reasonably. Our comprehensive work provides crucial insights for developers on modeling gene expression data and fosters the simulation process for users.

Modeling brain sex in the limbic system as phenotype for female-prevalent mental disorders

BACKGROUND

Sex differences exist in the prevalence and clinical manifestation of several mental disorders, suggesting that sex-specific brain phenotypes may play key roles. Previous research used machine learning models to classify sex from imaging data of the whole brain and studied the association of class probabilities with mental health, potentially overlooking regional specific characteristics.

METHODS

We here investigated if a regionally constrained model of brain volumetric imaging data may provide estimates that are more sensitive to mental health than whole brain-based estimates. Given its known role in emotional processing and mood disorders, we focused on the limbic system. Using two different cohorts of healthy subjects, the Human Connectome Project and the Queensland Twin IMaging, we investigated sex differences and heritability of brain volumes of limbic structures compared to non-limbic structures, and subsequently applied regionally constrained machine learning models trained solely on limbic or non-limbic features. To investigate the biological underpinnings of such models, we assessed the heritability of the obtained sex class probability estimates, and we investigated the association with major depression diagnosis in an independent clinical sample. All analyses were performed both with and without controlling for estimated total intracranial volume (eTIV).

RESULTS

Limbic structures show greater sex differences and are more heritable compared to non-limbic structures in both analyses, with and without eTIV control. Consequently, machine learning models performed well at classifying sex based solely on limbic structures and achieved performance as high as those on non-limbic or whole brain data, despite the much smaller number of features in the limbic system. The resulting class probabilities were heritable, suggesting potentially meaningful underlying biological information. Applied to an independent population with major depressive disorder, we found that depression is associated with male-female class probabilities, with largest effects obtained using the limbic model. This association was significant for models not controlling for eTIV whereas in those controlling for eTIV the associations did not pass significance correction.

CONCLUSIONS

Overall, our results highlight the potential utility of regionally constrained models of brain sex to better understand the link between sex differences in the brain and mental disorders.

Cortical gyrification in women and men and the (missing) link to prenatal androgens

Previous studies have reported sex differences in cortical gyrification. Since most cortical folding is principally defined in utero, sex chromosomes as well as gonadal hormones are likely to influence sex-specific aspects of local gyrification. Classic congenital adrenal hyperplasia (CAH) causes high levels of androgens during gestation in females, whereas levels in males are largely within the typical male range. Therefore, CAH provides an opportunity to study the possible effects of prenatal androgens on cortical gyrification. Here, we examined the vertex-wise absolute mean curvature-a common estimate for cortical gyrification-in individuals with CAH (33 women and 20 men) and pair-wise matched controls (33 women and 20 men). There was no significant main effect of CAH and no significant CAH-by-sex interaction. However, there was a significant main effect of sex in five cortical regions, where gyrification was increased in women compared to men. These regions were located on the lateral surface of the brain, specifically left middle frontal (rostral and caudal), right inferior frontal, left inferior parietal, and right occipital. There was no cortical region where gyrification was increased in men compared to women. Our findings do not only confirm prior reports of increased cortical gyrification in female brains but also suggest that cortical gyrification is not significantly affected by prenatal androgen exposure. Instead, cortical gyrification might be determined by sex chromosomes either directly or indirectly-the latter potentially by affecting the underlying architecture of the cortex or the size of the intracranial cavity, which is smaller in women.

Aging pattern of the brainstem based on volumetric measurement and optimized surface shape analysis

The brainstem, a small and crucial structure, is connected to the cerebrum, spinal cord, and cerebellum, playing a vital role in regulating autonomic functions, transmitting motor and sensory information, and modulating cognitive processes, emotions, and consciousness. While previous research has indicated that changes in brainstem anatomy can serve as a biomarker for aging and neurodegenerative diseases, the structural changes that occur in the brainstem during normal aging remain unclear. This study aimed to examine the age- and sex-related differences in the global and local structural measures of the brainstem in 187 healthy adults (ranging in age from 18 to 70 years) using structural magnetic resonance imaging. The findings showed a significant negative age effect on the volume of the two major components of the brainstem: the medulla oblongata and midbrain. The shape analysis revealed that atrophy primarily occurs in specific structures, such as the pyramid, cerebral peduncle, superior and inferior colliculi. Surface area and shape analysis showed a trend of flattening in the aging brainstem. There were no significant differences between the sexes or sex-by-age interactions in brainstem structural measures. These findings provide a systematic description of age associations with brainstem structures in healthy adults and may provide a reference for future research on brain aging and neurodegenerative diseases.

Cocaine self-administration behavior is associated with subcortical and cortical morphometry measures in individuals with cocaine use disorder

Background: Individual differences in gray-matter morphometry in the limbic system and frontal cortex have been linked to clinical features of cocaine use disorder (CUD). Self-administration paradigms can provide more direct measurements of the relationship between the regulation of cocaine use and gray-matter morphometry when compared to self-report assessments.Objectives: Our goal was to investigate associations with self-administration behavior in subcortical and cortical brain regions. We hypothesized the number of cocaine infusions self-administered would be correlated with gray-matter volumes (GMVs) in the striatum, amygdala, and hippocampus. Due to scarcity in human studies, we did not hypothesize subcortical directionality. In the frontal cortex, we hypothesized thickness would be negatively correlated with self-administered cocaine.Methods: We conducted an analysis of cocaine self-administration and structural MRI data from 33 (nFemales = 10) individuals with moderate-to-severe CUD. Self-administration lasted 60-minutes and cocaine (8, 16, or 32 mg/70 kg) was delivered on an FR1 schedule (5-minute lockout). Subcortical and cortical regression analyses were performed that included combined bilateral regions and age, experimental variables and use history as confounders.Results: Self-administered cocaine infusions were positively associated with caudal GMV (b = 0.18, p = 0.030) and negatively with putamenal GMV (b = -0.10, p = 0.041). In the cortical model, infusions were positively associated with insular thickness (b = 0.39, p = 0.008) and women appeared to self-administer cocaine more frequently (b = 0.23, p = 0.019).Conclusions: Brain morphometry features in the striatum and insula may contribute to cocaine consumption in CUD. These differences in morphometry may reflect consequences of prolonged use, predisposed vulnerability, or other possibilities.Clinical Trial Numbers: NCT01978431; NCT03471182.

Sex and Gender in Population Neuroscience

To understand psychiatric and neurological disorders and the structural and functional properties of the human brain, it is essential to consider the roles of sex and gender. In this chapter, I first define sex and gender and describe studies of sex differences in non-human animals. In humans, I describe the sex differences in behavioral and clinical phenotypes and neuroimaging-derived phenotypes, including whole-brain measures, regional subcortical and cortical measures, and structural and functional connectivity. Although structural whole-brain sex differences are large, regional effects (adjusting for whole-brain volumes) are typically much smaller and often fail to replicate. Nevertheless, while an individual neuroimaging feature may have a small effect size, aggregating them in a "maleness/femaleness" score or machine learning multivariate paradigm may prove to be predictive and informative of sex- and gender-related traits. Finally, I conclude by summarizing emerging investigations of gender norms and gender identity and provide methodological recommendations to incorporate sex and gender in population neuroscience research.

Comparison of approaches to control for intracranial volume in research on the association of brain volumes with cognitive outcomes

Most neuroimaging studies linking regional brain volumes with cognition correct for total intracranial volume (ICV), but methods used for this correction differ across studies. It is unknown whether different ICV correction methods yield consistent results. Using a brain-wide association approach in the MRI substudy of UK Biobank (N = 41,964; mean age = 64.5 years), we used regression models to estimate the associations of 58 regional brain volumetric measures with eight cognitive outcomes, comparing no correction and four ICV correction approaches. Approaches evaluated included: no correction; dividing regional volumes by ICV (proportional approach); including ICV as a covariate in the regression (adjustment approach); and regressing the regional volumes against ICV in different normative samples and using calculated residuals to determine associations (residual approach). We used Spearman-rank correlations and two consistency measures to quantify the extent to which associations were inconsistent across ICV correction approaches for each possible brain region and cognitive outcome pair across 2320 regression models. When the association between brain volume and cognitive performance was close to null, all approaches produced similar estimates close to the null. When associations between a regional volume and cognitive test were not null, the adjustment and residual approaches typically produced similar estimates, but these estimates were inconsistent with results from the crude and proportional approaches. For example, when using the crude approach, an increase of 0.114 (95% confidence interval [CI]: 0.103-0.125) in fluid intelligence was associated with each unit increase in hippocampal volume. However, when using the adjustment approach, the increase was 0.055 (95% CI: 0.043-0.068), while the proportional approach showed a decrease of -0.025 (95% CI: -0.035 to -0.014). Different commonly used methods to correct for ICV yielded inconsistent results. The proportional method diverges notably from other methods and results were sometimes biologically implausible. A simple regression adjustment for ICV produced biologically plausible associations.

SARS-CoV-2's brain impact: revealing cortical and cerebellar differences via cluster analysis in COVID-19 recovered patients

BACKGROUND

COVID-19 is a disease known for its neurological involvement. SARS-CoV-2 infection triggers neuroinflammation, which could significantly contribute to the development of long-term neurological symptoms and structural alterations in the gray matter. However, the existence of a consistent pattern of cerebral atrophy remains uncertain.

OBJECTIVE

Our study aimed to identify patterns of brain involvement in recovered COVID-19 patients and explore potential relationships with clinical variables during hospitalization.

METHODOLOGY

In this study, we included 39 recovered patients and 39 controls from a pre-pandemic database to ensure their non-exposure to the virus. We obtained clinical data of the patients during hospitalization, and 3 months later; in addition we obtained T1-weighted magnetic resonance images and performed standard screening cognitive tests.

RESULTS

We identified two groups of recovered patients based on a cluster analysis of the significant cortical thickness differences between patients and controls. Group 1 displayed significant cortical thickness differences in specific cerebral regions, while Group 2 exhibited significant differences in the cerebellum, though neither group showed cognitive deterioration at the group level. Notably, Group 1 showed a tendency of higher D-dimer values during hospitalization compared to Group 2, prior to p-value correction.

CONCLUSION

This data-driven division into two groups based on the brain structural differences, and the possible link to D-dimer values may provide insights into the underlying mechanisms of SARS-COV-2 neurological disruption and its impact on the brain during and after recovery from the disease.

After the trans brain: a critique of the neurobiological accounts of embodied trans* identities

This paper critically analyses three main neurobiological hypotheses on trans* identities: the neurobiological theory about the origin of gender dysphoria, the neurodevelopmental cortical hypothesis, and the alternative hypothesis of self-referential thinking and body perception. In this study I focus then the attention on three elements: the issue of (de)pathologisation, the idea of the trans brain, and the aetiology of trans* identities. While the neurobiological theory about the origin of gender dysphoria and the neurodevelopmental cortical hypothesis claim the existence of the trans brain, each offering its own neurobiological depiction, the hypothesis of self-referential thinking and body perception doesn't postulate a distinctive neurobiological trait for all trans* people. I problematize both portrayals of the trans brain departing from the findings and conceptualizations of the paradigm shifting brain mosaicism. Unlike the hypothesis of self-referential thinking and body perception that keeps the question of causation open, both the neurobiological theory about the origin of gender dysphoria and the neurodevelopmental cortical hypothesis situate the origin of trans* identities in the neurobiological domain. I challenge the biological deterministic framework in which this aetiology is inscribed from a dynamic processual entanglement perspective. Finally, concerning the issue of (de)pathologisation of trans* identities, an evolution can be seen in each of the hypothesis and among them, from the least to the most depathologising. However, I question their complete departure from a pathologising framework.

Involvement of the ipsilateral-to-the-pain anterior-superior hypothalamic subunit in chronic cluster headache

BACKGROUND

Despite hypothalamus has long being considered to be involved in the pathophysiology of cluster headache, the inconsistencies of previous neuroimaging studies and a limited understanding of the hypothalamic areas involved, impede a comprehensive interpretation of its involvement in this condition.

METHODS

We used an automated algorithm to extract hypothalamic subunit volumes from 105 cluster headache patients (57 chronic and 48 episodic) and 59 healthy individuals; after correcting the measures for the respective intracranial volumes, we performed the relevant comparisons employing logist regression models. Only for subunits that emerged as abnormal, we calculated their correlation with the years of illness and the number of headache attacks per day, and the effects of lithium treatment. As a post-hoc approach, using the 7 T resting-state fMRI dataset from the Human Connectome Project, we investigated whether the observed abnormal subunit, comprising the paraventricular nucleus and preoptic area, shows robust functional connectivity with the mesocorticolimbic system, which is known to be modulated by oxytocin neurons in the paraventricular nucleus and that is is abnormal in chronic cluster headache patients.

RESULTS

Patients with chronic (but not episodic) cluster headache, compared to control participants, present an increased volume of the anterior-superior hypothalamic subunit ipsilateral to the pain, which, remarkably, also correlates significantly with the number of daily attacks. The post-hoc approach showed that this hypothalamic area presents robust functional connectivity with the mesocorticolimbic system under physiological conditions. No evidence of the effects of lithium treatment on this abnormal subunit was found.

CONCLUSIONS

We identified the ipsilateral-to-the-pain antero-superior subunit, where the paraventricular nucleus and preoptic area are located, as the key hypothalamic region of the pathophysiology of chronic cluster headache. The significant correlation between the volume of this area and the number of daily attacks crucially reinforces this interpretation. The well-known roles of the paraventricular nucleus in coordinating autonomic and neuroendocrine flow in stress adaptation and modulation of trigeminovascular mechanisms offer important insights into the understanding of the pathophysiology of cluster headache.

FTO variation and early frontostriatal brain development in children

OBJECTIVE

Common obesity-associated genetic variants at the fat mass and obesity-associated (FTO) locus have been associated with appetitive behaviors and altered structure and function of frontostriatal brain regions. The authors aimed to investigate the influence of FTO variation on frontostriatal appetite circuits in early life.

METHODS

Data were drawn from RESONANCE, a longitudinal study of early brain development. Growth trajectories of nucleus accumbens and frontal lobe volumes, as well as total gray matter and white matter volume, by risk allele (AA) carrier status on FTO single-nucleotide polymorphism rs9939609 were examined in 228 children (102 female, 126 male) using magnetic resonance imaging assessments obtained from infancy through middle childhood. The authors fit functional concurrent regression models with brain volume outcomes over age as functional responses, and FTO genotype, sex, BMI z score, and maternal education were included as predictors.

RESULTS

Bootstrap pointwise 95% CI for regression coefficient functions in the functional concurrent regression models showed that the AA group versus the group with no risk allele (TT) had greater nucleus accumbens volume (adjusted for total brain volume) in the interval of 750 to 2250 days (2-6 years).

CONCLUSIONS

These findings suggest that common genetic risk for obesity is associated with differences in early development of brain reward circuitry and argue for investigating dynamic relationships among genotype, brain, behavior, and weight throughout development.

A global multicohort study to map subcortical brain development and cognition in infancy and early childhood

The human brain grows quickly during infancy and early childhood, but factors influencing brain maturation in this period remain poorly understood. To address this gap, we harmonized data from eight diverse cohorts, creating one of the largest pediatric neuroimaging datasets to date focused on birth to 6 years of age. We mapped the developmental trajectory of intracranial and subcortical volumes in ∼2,000 children and studied how sociodemographic factors and adverse birth outcomes influence brain structure and cognition. The amygdala was the first subcortical volume to mature, whereas the thalamus exhibited protracted development. Males had larger brain volumes than females, and children born preterm or with low birthweight showed catch-up growth with age. Socioeconomic factors exerted region- and time-specific effects. Regarding cognition, males scored lower than females; preterm birth affected all developmental areas tested, and socioeconomic factors affected visual reception and receptive language. Brain-cognition correlations revealed region-specific associations.

Altered Sex Differences in Hippocampal Subfield Volumes in Schizophrenia

BACKGROUND AND HYPOTHESIS

The hippocampus is a heterogenous brain structure that differs between the sexes and has been implicated in the pathophysiology of psychiatric illnesses. Here, we explored sex and diagnostic group differences in hippocampal subfield volumes, in individuals with schizophrenia spectrum disorder (SZ), bipolar disorders (BD), and healthy controls (CTL).

STUDY DESIGN

One thousand and five hundred and twenty-one participants underwent T1-weighted magnetic resonance imaging (SZ, n = 452, mean age 30.7 ± 9.2 [SD] years, males 59.1%; BD, n = 316, 33.7 ± 11.4, 41.5%; CTL, n = 753, 34.1 ± 9.1, 55.6%). Total hippocampal, subfield, and intracranial volumes were estimated with Freesurfer (v6.0.0). Analysis of covariance and multiple regression models were fitted to examine sex-by-diagnostic (sub)group interactions in volume. In SZ and BD, separately, associations between volumes and clinical as well as cognitive measures were examined between the sexes using regression models.

STUDY RESULTS

Significant sex-by-group interactions were found for the total hippocampus, dentate gyrus, molecular layer, presubiculum, fimbria, hippocampal-amygdaloid transition area, and CA4, indicating a larger volumetric deficit in male patients relative to female patients when compared with same-sex CTL. Subgroup analyses revealed that this interaction was driven by males with schizophrenia. Effect sizes were overall small (partial η < 0.02). We found no significant sex differences in the associations between hippocampal volumes and clinical or cognitive measures in SZ and BD.

CONCLUSIONS

Using a well-powered sample, our findings indicate that the pattern of morphological sex differences in hippocampal subfields is altered in individuals with schizophrenia relative to CTL, due to higher volumetric deficits in males.

Univariate and multivariate sex differences and similarities in gray matter volume within essential language-processing areas

BACKGROUND

Sex differences in language-related abilities have been reported. It is generally assumed that these differences stem from a different organization of language in the brains of females and males. However, research in this area has been relatively scarce, methodologically heterogeneous and has yielded conflicting results.

METHODS

Univariate and multivariate sex differences and similarities in gray matter volume (GMVOL) within 18 essential language-processing brain areas were assessed in a sex-balanced sample (N = 588) of right-handed young adults. Univariate analyses involved location, spread, and shape comparisons of the females' and males' distributions and were conducted with several robust statistical methods able to quantify the size of sex differences and similarities in a complementary way. Multivariate sex differences and similarities were estimated by the same methods in the continuous scores provided by two distinct multivariate procedures (logistic regression and a multivariate analog of the Wilcoxon-Mann-Whitney test). Additional analyses were addressed to compare the outcomes of these two multivariate analytical strategies and described their structure (that is, the relative contribution of each brain area to the multivariate effects).

RESULTS

When not adjusted for total intracranial volume (TIV) variation, "large" univariate sex differences (males > females) were found in all 18 brain areas considered. In contrast, "small" differences (females > males) in just two of these brain areas were found when controlling for TIV. The two multivariate methods tested provided very similar results. Multivariate sex differences surpassed univariate differences, yielding "large" differences indicative of larger volumes in males when calculated from raw GMVOL estimates. Conversely, when calculated from TIV-adjusted GMVOL, multivariate differences were "medium" and indicative of larger volumes in females. Despite their distinct size and direction, multivariate sex differences in raw and TIV-adjusted GMVOL shared a similar structure and allowed us to identify the components of the SENT_CORE network which more likely contribute to the observed effects.

CONCLUSIONS

Our results confirm and extend previous findings about univariate sex differences in language-processing areas, offering unprecedented evidence at the multivariate level. We also observed that the size and direction of these differences vary quite substantially depending on whether they are estimated from raw or TIV-adjusted GMVOL measurements.

Sex-dependent differences in connectivity patterns are related to episodic memory recall

Previous studies have shown that females typically outperform males on episodic memory tasks. In this study, we investigated if (1) there are differences between males and females in their connectome characteristics, (2) if these connectivity patterns are associated with memory performance, and (3) if these brain connectome characteristics contribute to the differences in episodic memory performance between sexes. In a sample of 655 healthy young subjects (n = 391 females; n = 264 males), we derived brain network characteristics from diffusion-weighted imaging (DWI) data using models of crossing fibers within each voxel of the brain and probabilistic tractography (graph strength, shortest path length, global efficiency, and weighted transitivity). Group differences were analysed with linear models and mediation analyses were used to explore how connectivity patterns might relate to sex-dependent differences in memory performance. Our results show significant sex-dependent differences in weighted transitivity (d = 0.42), with males showing higher values. Further, we observed a negative association between weighted transitivity and memory performance (r = -0.12). Finally, these distinct connectome characteristics partially mediated the observed differences in memory performance (effect size of the indirect effect r = 0.02). Our findings indicate a higher interconnectedness in females compared to males. Additionally, we demonstrate that the sex-dependent differences in episodic memory performance can be partially explained by the differences in this connectome measure. These results further underscore the importance of sex-dependent differences in brain connectivity and their impact on cognitive function.

Posterior Fossa Sub-Arachnoid Cysts Observed in Patients with Bipolar Disorder: a Retrospective Cohort Study

Posterior fossa arachnoid cysts (PFACs) are rare congenital abnormalities observed in 0.3 to 1.7% of the population and are traditionally thought to be benign. While conducting a neuroimaging study investigating cerebellar structure in bipolar disorder, we observed a higher incidence of PFACs in bipolar patients (5 of 75; 6.6%) compared to the neuronormative control group (1 of 54; 1.8%). In this report, we detail the cases of the five patients with bipolar disorder who presented with PFACs. Additionally, we compare neuropsychiatric measures and cerebellar volumes of these patients to neuronormative controls and bipolar controls (those with bipolar disorder without neuroanatomical abnormalities). Our findings suggest that patients with bipolar disorder who also present with PFACs may have a milder symptom constellation relative to patients with bipolar disorder and no neuroanatomical abnormalities. Furthermore, our observations align with prior literature suggesting an association between PFACs and psychiatric symptoms that warrants further study. While acknowledging sample size limitations, our primary aim in the present work is to highlight a connection between PFACs and BD-associated symptoms and encourage further study of cerebellar abnormalities in psychiatry.

Multiclass prediction of different dementia syndromes based on multi-centric volumetric MRI imaging

INTRODUCTION

Dementia syndromes can be difficult to diagnose. We aimed at building a classifier for multiple dementia syndromes using magnetic resonance imaging (MRI).

METHODS

Atlas-based volumetry was performed on T1-weighted MRI data of 426 patients and 51 controls from the multi-centric German Research Consortium of Frontotemporal Lobar Degeneration including patients with behavioral variant frontotemporal dementia, Alzheimer's disease, the three subtypes of primary progressive aphasia, i.e., semantic, logopenic and nonfluent-agrammatic variant, and the atypical parkinsonian syndromes progressive supranuclear palsy and corticobasal syndrome. Support vector machine classification was used to classify each patient group against controls (binary classification) and all seven diagnostic groups against each other in a multi-syndrome classifier (multiclass classification).

RESULTS

The binary classification models reached high prediction accuracies between 71 and 95% with a chance level of 50%. Feature importance reflected disease-specific atrophy patterns. The multi-syndrome model reached accuracies of more than three times higher than chance level but was far from 100%. Multi-syndrome model performance was not homogenous across dementia syndromes, with better performance in syndromes characterized by regionally specific atrophy patterns. Whereas diseases generally could be classified vs controls more correctly with increasing severity and duration, differentiation between diseases was optimal in disease-specific windows of severity and duration.

DISCUSSION

Results suggest that automated methods applied to MR imaging data can support physicians in diagnosis of dementia syndromes. It is particularly relevant for orphan diseases beside frequent syndromes such as Alzheimer's disease.

A comparison of intracranial volume estimation methods and their cross-sectional and longitudinal associations with age

Intracranial volume (ICV) is frequently used in volumetric magnetic resonance imaging (MRI) studies, both as a covariate and as a variable of interest. Findings of associations between ICV and age have varied, potentially due to differences in ICV estimation methods. Here, we compared five commonly used ICV estimation methods and their associations with age. T1-weighted cross-sectional MRI data was included for 651 healthy individuals recruited through the NORMENT Centre (mean age = 46.1 years, range = 12.0-85.8 years) and 2410 healthy individuals recruited through the UK Biobank study (UKB, mean age = 63.2 years, range = 47.0-80.3 years), where longitudinal data was also available. ICV was estimated with FreeSurfer (eTIV and sbTIV), SPM12, CAT12, and FSL. We found overall high correlations across ICV estimation method, with the lowest observed correlations between FSL and eTIV (r = .87) and between FSL and CAT12 (r = .89). Widespread proportional bias was found, indicating that the agreement between methods varied as a function of head size. Body weight, age, sex, and mean ICV across methods explained the most variance in the differences between ICV estimation methods, indicating possible confounding for some estimation methods. We found both positive and negative cross-sectional associations with age, depending on dataset and ICV estimation method. Longitudinal ICV reductions were found for all ICV estimation methods, with annual percentage change ranging from -0.293% to -0.416%. This convergence of longitudinal results across ICV estimation methods offers strong evidence for age-related ICV reductions in mid- to late adulthood.

Macular Layer Thickness and Effect of BMI, Body Fat, and Traditional Cardiovascular Risk Factors: The Tromsø Study

Purpose

The purpose of this study was to investigate associations between cardiovascular risk factors and the thickness of retinal nerve fiber layer (RNFL), ganglion cell-inner plexiform layer (GCIPL), and outer retina layers (ORL).

Methods

In this population-based study, we included participants from the Tromsø Study: Tromsø6 (2007 to 2008) and Tromsø7 (2015 to 2016). Persons with diabetes and/or diagnosed glaucoma were excluded from this study. Retinal thickness was measured on optical coherence tomography (Cirrus HD-OCT) macula-scans, segmented on RNFL, GCIPL, and ORL and associations were analyzed cross-sectionally (N = 8288) and longitudinally (N = 2595). We used directed acyclic graphs (DAGs) for model selection, and linear regression to adjust for confounders and mediators in models assessing direct effects. Factors examined were age, sex, blood pressure, daily smoking, serum lipids, glycated hemoglobin, body mass index (BMI), total body fat percentage (BFP), and the adjustment variables refraction and height.

Results

The explained variance of cardiovascular risk factors was highest in GCIPL (0.126). GCIPL had a strong negative association with age. Women had thicker GCIPL than men at higher age and thinner ORL at all ages (P < 0.001). Systolic blood pressure was negatively associated with RNFL/GCIPL (P = 0.001/0.004), with indication of a U-shaped relationship with GCIPL in women. The negative association with BMI was strongest in men, with significant effect for RNFL/GCIPL/ORL (P = 0.001/<0.001/0.019) and in women for GCIPL/ORL (P = 0.030/0.037). BFP was negatively associated with GCIPL (P = 0.01). Higher baseline BMI was associated with a reduction in GCIPL over 8 years (P = 0.03).

Conclusions

Cardiovascular risk factors explained 12.6% of the variance in GCIPL, with weight and blood pressure the most important modifiable factors.

Sexually divergent development of depression-related brain networks during healthy human adolescence

Sexual differences in human brain development could be relevant to sex differences in the incidence of depression during adolescence. We tested for sex differences in parameters of normative brain network development using fMRI data on N = 298 healthy adolescents, aged 14 to 26 years, each scanned one to three times. Sexually divergent development of functional connectivity was located in the default mode network, limbic cortex, and subcortical nuclei. Females had a more "disruptive" pattern of development, where weak functional connectivity at age 14 became stronger during adolescence. This fMRI-derived map of sexually divergent brain network development was robustly colocated with i prior loci of reward-related brain activation ii a map of functional dysconnectivity in major depressive disorder (MDD), and iii an adult brain gene transcriptional pattern enriched for genes on the X chromosome, neurodevelopmental genes, and risk genes for MDD. We found normative sexual divergence in adolescent development of a cortico-subcortical brain functional network that is relevant to depression.

Single-subject analysis of regional brain volumetric measures can be strongly influenced by the method for head size adjustment

Purpose

Total intracranial volume (TIV) is often a nuisance covariate in MRI-based brain volumetry. This study compared two TIV adjustment methods with respect to their impact on z-scores in single subject analyses of regional brain volume estimates.

Methods

Brain parenchyma, hippocampus, thalamus, and TIV were segmented in a normal database comprising 5059 T1w images. Regional volume estimates were adjusted for TIV using the residual method or the proportion method. Age was taken into account by regression with both methods. TIV- and age-adjusted regional volumes were transformed to z-scores and then compared between the two adjustment methods. Their impact on the detection of thalamus atrophy was tested in 127 patients with multiple sclerosis.

Results

The residual method removed the association with TIV in all regions. The proportion method resulted in a switch of the direction without relevant change of the strength of the association. The reduction of physiological between-subject variability was larger with the residual method than with the proportion method. The difference between z-scores obtained with the residual method versus the proportion method was strongly correlated with TIV. It was larger than one z-score point in 5% of the subjects. The area under the ROC curve of the TIV- and age-adjusted thalamus volume for identification of multiple sclerosis patients was larger with the residual method than with the proportion method (0.84 versus 0.79).

Conclusion

The residual method should be preferred for TIV and age adjustments of T1w-MRI-based brain volume estimates in single subject analyses.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00234-022-02961-6.

Relationships between Personality Traits and Brain Gray Matter Are Different in Risky and Non-risky Drivers

Personality traits such as impulsivity or sensitivity to rewards and punishments have been associated with risky driving behavior, but it is still unclear how brain anatomy is related to these traits as a function of risky driving. In the present study, we explore the neuroanatomical basis of risky driving behavior and how the level of risk-taking influences the relationship between the traits of impulsivity and sensitivity to rewards and punishments and brain gray matter volume. One hundred forty-four participants with different risk-taking tendencies assessed by real-life driving situations underwent MRI. Personality traits were assessed with self-report measures. We observed that the total gray matter volume varied as a function of risky driving tendencies, with higher risk individuals showing lower gray matter volumes. Similar results were found for volumes of brain areas involved in the reward and cognitive control networks, such as the frontotemporal, parietal, limbic, and cerebellar cortices. We have also shown that sensitivity to reward and punishment and impulsivity are differentially related to gray matter volumes as a function of risky driving tendencies. Highly risky individuals show lower absolute correlations with gray matter volumes than less risk-prone individuals. Taken together, our results show that risky drivers differ in the brain structure of the areas involved in reward processing, cognitive control, and behavioral modulation, which may lead to dysfunctional decision-making and riskier driving behavior.

Bipolar spectrum disorders are associated with increased gray matter volume in the medial orbitofrontal cortex and nucleus accumbens

Objective

Elevated sensitivity to rewards prospectively predicts Bipolar Spectrum Disorder (BSD) onset; however, it is unclear whether volumetric abnormalities also reflect BSD risk. BSDs emerge when critical neurodevelopment in frontal and striatal regions occurs in sex-specific ways. The current paper examined the volume of frontal and striatal brain regions in both individuals with and at risk for a BSD with exploratory analyses examining sex-specificity.

Methods

One hundred fourteen medication-free individuals ages 18-27 at low-risk for BSD (moderate-reward sensitivity; N = 37), at high-risk without a BSD (high-reward sensitivity; N = 47), or with a BSD (N = 30) completed a structural MRI scan of the brain. We examined group differences in gray matter volume in a priori medial orbitofrontal cortex (mOFC) and nucleus accumbens (NAcc) regions-of-interest.

Results

The BSD group had enlarged frontostriatal volumes (mOFC, NAcc) compared to low individuals (d = 1.01). The mOFC volume in BSD was larger than low-risk (d = 1.01) and the high-risk groups (d = 0.74). This effect was driven by males with a BSD, who showed an enlarged mOFC compared to low (d = 1.01) and high-risk males (d = 0.74). Males with a BSD also showed a greater NAcc volume compared to males at low-risk (d = 0.49), but not high-risk males.

Conclusions

An enlarged frontostriatal volume (averaged mOFC, NAcc) is associated with the presence of a BSD, while subvolumes (mOFC vs. NAcc) showed unique patterning in relation to risk. We report preliminary evidence that sex moderates frontostriatal volume in BSD, highlighting the need for larger longitudinal risk studies examining the role of sex-specific neurodevelopmental trajectories in emerging BSDs.

Sex/gender differences in children with autism spectrum disorder: A brief overview on epidemiology, symptom profile, and neuroanatomy

Autism spectrum disorders (ASD) are a heterogeneous group of neurodevelopmental conditions whose shared core features are impairments in social interaction and communication as well as restricted patterns of behavior, interests, and activities. The significant and consistent male preponderance in ASD prevalence has historically affected the scientific knowledge of autism in females as regards, inter alia, the clinical presentation, the genetic architecture, and the structural brain underpinnings. Indeed, females with ASD are under-investigated as samples recruited for clinical research typically reflect the strong male bias of the disorder. In the last years, the study of the various aspects of sex/gender (s/g) differences in ASD is gaining increased clinical and research interest resulting in a growing number of investigations on this topic. Here, I review and discuss evidence emerged from epidemiological, clinical, and neuroimaging studies in the last decade focusing on s/g differences in children with ASD. These studies are the prerequisites for the development of assessment and treatment practices which take into consideration s/g differences in ASD. Ultimately, a better understanding of s/g differences aims at improving healthcare for both ASD males and females.

Reflections on Neurofeminism and Intersectionality Using Insights From Psychology

Intersectionality contends that sex/gender is constituted of and with other social categories, and that the social structures giving rise to inequality should be addressed in research. This is a powerful and important perspective from which to investigate the processes and consequences of social group memberships, one which has been overlooked by most neuroscientific research. In particular, neurofeminism, a field of critical neuroscience that challenges neuroscientific assumptions, methods and interpretations of data that reinforce sexism, has ignored intersectionality to date. In contrast, research in the field of psychology has been engaging with intersectionality for more than a decade. In reflecting on how intersectionality has advanced feminist research in psychology, this paper provides a critical analysis of potential novel research avenues for neurofeminism. We identify three main research themes guided by intersectionality. The first theme involves research centered on understanding the socio-structural causes of health inequalities experienced by individuals with intersecting marginalized social identities; the second concerns research addressing the psychological processing of social group memberships that underlies the enactment of systemic discriminatory practices; and the third theme comprises intersectionality research that aims to challenge psychological epistemology. Drawing parallels between the fields of psychology and neuroscience, we explore the potential benefits and risks of advancing an intersectionality-informed neurofeminism.

Sex/gender differences in the brain are not trivial-A commentary on Eliot et al. (2021)

In this commentary to the comprehensive review by Eliot et al. (2021), we fully comply with rejecting the 'sexual dimorphism' concept in its extreme, binary form. However, we criticise the authors' extreme position and argue that sex/gender differences in the brain are far from being 'trivial' and 'unlikely to be meaningful'. Our key arguments refer to the importance of small effects which can have meaningful behavioural consequences, and to several non-binary sex/gender-related factors which might explain individual differences better than sex/gender per se and which have shown to play important roles as risk factors in the aetiology of many mental and neurodevelopmental disorders. We conclude that the biopsychosocial approach is key to understanding sex/gender differences in the brain better than we currently do.

Beyond the binary: Rethinking sex and the brain

The paper reviews the relations between sex and brain in light of the binary conceptualization of these relations and the challenges posed to it by the 'mosaic' hypothesis. Recent formulations of the binary framework range from arguing that the typical male brain is different from the typical female brain to claiming that brains are typically male or female because brain structure can be used to predict the sex category (female/male) of the brain's owner. These formulations are challenged by evidence that sex effects on the brain may be opposite under different conditions, that human brains are comprised of mosaics of female-typical and male-typical features, and that sex category explains only a small part of the variability in human brain structure. These findings led to a new, non-binary, framework, according to which mosaic brains reside in a multi-dimensional space that cannot meaningfully be reduced to a male-female continuum or to a binary variable. This framework may also apply to sex-related variables and has implications for research.

A comprehensive atlas of white matter tracts in the chimpanzee

Chimpanzees (Pan troglodytes) are, along with bonobos, humans’ closest living relatives. The advent of diffusion MRI tractography in recent years has allowed a resurgence of comparative neuroanatomical studies in humans and other primate species. Here we offer, in comparative perspective, the first chimpanzee white matter atlas, constructed from in vivo chimpanzee diffusion-weighted scans. Comparative white matter atlases provide a useful tool for identifying neuroanatomical differences and similarities between humans and other primate species. Until now, comprehensive fascicular atlases have been created for humans (Homo sapiens), rhesus macaques (Macaca mulatta), and several other nonhuman primate species, but never in a nonhuman ape. Information on chimpanzee neuroanatomy is essential for understanding the anatomical specializations of white matter organization that are unique to the human lineage.

Diffusion MRI tractography reveals the first complete atlas of white matter of the chimpanzee, with the potential to help understand differences between the organization of human and chimpanzee brains.

Considerations in genetic counseling of transgender patients: Cultural competencies and altered disease risk profiles

Transgender people are a growing population with specific healthcare needs, barriers to care, and disease risk factors. Cultural competencies for working with transgender people in healthcare settings are essential to reduce barriers to care and combat the associated health disparities. Genetic counselors support their patients to understand and manage medically and personally complex life events and decisions. A genetic counselor caring for a transgender patient or a patient with a transgender relative will therefore require specific cultural competencies and medical knowledge that may not have been covered in their training. Transgender health is also a relatively young field in which new insights may quickly become fundamental. The present paper therefore provides an overview of current best practices for culturally sensitive working with transgender patients, and an introduction to the additional considerations for assessment of disease risk in transgender people. Guidance on how to ensure communication with patients and other stakeholders is inclusive and affirming of transgender identities, is offered. Medical interventions used for gender transitions are described, and their (potential) effects on cancer and cardiovascular disease risk are discussed. Furthermore, the effects of sociocultural risk factors such as minority stress are outlined. In sum, we invite the reader to consider the specific biological, psychological, and social context of the consultation. Finally, we explore culturally competent approaches to pedigree charting and physical examinations with transgender people and provide recommendations for practice.

"Masculine" Describes Gender Expressions, Not Neurobiologies: Response to Dutton and Madison (2020)

This letter is a response to "Gender Dysphoria and Transgender Identity Is Associated with Physiological and Psychological Masculinization: a Theoretical Integration of Findings, Supported by Systematic Reviews" by Dutton and Madison (2020), which relies on theorisations for which substantial counter-evidence exists, fails to engage with these or other criticisms of the theories upon which it seeks to build, and reaches conclusions that contradict existing evidence. Furthermore, the original theorisations contained in Dutton and Madison (2020), and the conclusions drawn from those theorisations, risk causing serious harm to already-marginalised groups.