Sex-Based Differences in Cortical and Subcortical Development in 436 Individuals Aged 4-54 Years

Sex-based differences in brain development have long been established in ex vivo studies. Recent in vivo studies using magnetic resonance imaging (MRI) have offered considerable insight into sex-based variations in brain maturation. However, reports of sex-based differences in cortical volumes and thickness are inconsistent. We examined brain maturation in a cross-sectional, single-site cohort of 436 individuals (201 [46%] males) aged 4-54 years (median = 16 years). Cortical thickness, cortical surface area, subcortical surface area, volumes of the cerebral cortex, white matter (WM), cortical and subcortical gray matter (GM), including the thalamic subnuclei, basal ganglia, and hippocampi were calculated using automatic segmentation pipelines. Subcortical structures demonstrated distinct curvilinear trajectories from the cortex, in both volumetric maturation and surface-area expansion in relation to age. Surface-area analysis indicated that dorsal regions of the thalamus, globus pallidus and striatum, regions demonstrating structural connectivity with frontoparietal cortices, exhibited extensive expansion with age, and were inversely related to changes seen in cortical maturation, which contracted with age. Furthermore, surface-area expansion was more robust in males in comparison to females. Age- and sex-related maturational changes may reflect alterations in dendritic and synaptic architecture known to occur during development from early childhood through to mid-adulthood.

Can we accurately classify schizophrenia patients from healthy controls using magnetic resonance imaging and machine learning? A multi-method and multi-dataset study

Machine learning is a powerful tool that has previously been used to classify schizophrenia (SZ) patients from healthy controls (HC) using magnetic resonance images. Each study, however, uses different datasets, classification algorithms, and validation techniques. Here, we perform a critical appraisal of the accuracy of machine learning methodologies used in SZ/HC classifications studies by comparing three machine learning algorithms (logistic regression [LR], support vector machines [SVMs], and linear discriminant analysis [LDA]) on three independent datasets (435 subjects total) using two tissue density estimates and cortical thickness (CT). Performance is assessed using 10-fold cross-validation, as well as a held-out validation set. Classification using CT outperformed tissue densities, but there was no clear effect of dataset. LR, SVMs, and LDA each yielded the highest accuracies for a different feature set and validation paradigm, but most accuracies were between 55 and 70%, well below previously reported values. The highest accuracy achieved was 73.5% using CT data and an SVM. Taken together, these results illustrate some of the obstacles to constructing effective disease classifiers, and suggest that tissue densities and CT may not be sufficiently sensitive for SZ/HC classification given current available methodologies and sample sizes.

Progress update from the hippocampal subfields group

INTRODUCTION

Heterogeneity of segmentation protocols for medial temporal lobe regions and hippocampal subfields on in vivo magnetic resonance imaging hinders the ability to integrate findings across studies. We aim to develop a harmonized protocol based on expert consensus and histological evidence.

METHODS

Our international working group, funded by the EU Joint Programme-Neurodegenerative Disease Research (JPND), is working toward the production of a reliable, validated, harmonized protocol for segmentation of medial temporal lobe regions. The working group uses a novel postmortem data set and online consensus procedures to ensure validity and facilitate adoption.

RESULTS

This progress report describes the initial results and milestones that we have achieved to date, including the development of a draft protocol and results from the initial reliability tests and consensus procedures.

DISCUSSION

A harmonized protocol will enable the standardization of segmentation methods across laboratories interested in medial temporal lobe research worldwide.

Identifying schizophrenia subgroups using clustering and supervised learning

Schizophrenia has a 1% incidence rate world-wide and those diagnosed present with positive (e.g. hallucinations, delusions), negative (e.g. apathy, asociality), and cognitive symptoms. However, both symptom burden and associated brain alterations are highly heterogeneous and intimately linked to prognosis. In this study, we present a method to predict individual symptom profiles by first deriving clinical subgroups and then using machine learning methods to perform subject-level classification based on magnetic resonance imaging (MRI) derived neuroanatomical measures. Symptomatic and MRI data of 167 subjects were used. Subgroups were defined using hierarchical clustering of clinical data resulting in 3 stable clusters: 1) high symptom burden, 2) predominantly positive symptom burden, and 3) mild symptom burden. Cortical thickness estimates were obtained in 78 regions of interest and were input, along with demographic data, into three machine learning models (logistic regression, support vector machine, and random forest) to predict subgroups. Random forest performance metrics for predicting the group membership of the high and mild symptom burden groups exceeded those of the baseline comparison of the entire schizophrenia population versus normal controls (AUC: 0.81 and 0.78 vs. 0.75). Additionally, an analysis of the most important features in the random forest classification demonstrated consistencies with previous findings of regional impairments and symptoms of schizophrenia.

Genetic architecture of subcortical brain structures in 38,851 individuals

Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.

Common functional networks in the mouse brain revealed by multi-centre resting-state fMRI analysis

Preclinical applications of resting-state functional magnetic resonance imaging (rsfMRI) offer the possibility to non-invasively probe whole-brain network dynamics and to investigate the determinants of altered network signatures observed in human studies. Mouse rsfMRI has been increasingly adopted by numerous laboratories worldwide. Here we describe a multi-centre comparison of 17 mouse rsfMRI datasets via a common image processing and analysis pipeline. Despite prominent cross-laboratory differences in equipment and imaging procedures, we report the reproducible identification of several large-scale resting-state networks (RSN), including a mouse default-mode network, in the majority of datasets. A combination of factors was associated with enhanced reproducibility in functional connectivity parameter estimation, including animal handling procedures and equipment performance. RSN spatial specificity was enhanced in datasets acquired at higher field strength, with cryoprobes, in ventilated animals, and under medetomidine-isoflurane combination sedation. Our work describes a set of representative RSNs in the mouse brain and highlights key experimental parameters that can critically guide the design and analysis of future rodent rsfMRI investigations.

Attack-related damage of thalamic nuclei in neuromyelitis optica spectrum disorders

OBJECTIVES

In neuromyelitis optica spectrum disorders (NMOSD) thalamic damage is controversial, but thalamic nuclei were never studied separately. We aimed at assessing volume loss of thalamic nuclei in NMOSD. We hypothesised that only specific nuclei are damaged, by attacks affecting structures from which they receive afferences: the lateral geniculate nucleus (LGN), due to optic neuritis (ON) and the ventral posterior nucleus (VPN), due to myelitis.

METHODS

Thirty-nine patients with aquaporin 4-IgG seropositive NMOSD (age: 50.1±14.1 years, 36 women, 25 with prior ON, 36 with prior myelitis) and 37 healthy controls (age: 47.8 ± 12.5 years, 32 women) were included in this cross-sectional study. Thalamic nuclei were assessed in magnetic resonance images, using a multi-atlas-based approach of automated segmentation. Retinal optical coherence tomography was also performed.

RESULTS

Patients with ON showed smaller LGN volumes (181.6±44.2 mm³) compared with controls (198.3±49.4 mm³; B=-16.97, p=0.004) and to patients without ON (206.1±50 mm³ ; B=-23.74, p=0.001). LGN volume was associated with number of ON episodes (Rho=-0.536, p<0.001), peripapillary retinal nerve fibre layer thickness (B=0.70, p<0.001) and visual function (B=-0.01, p=0.002). Although VPN was not smaller in patients with myelitis (674.3±67.5 mm³) than controls (679.7±68.33; B=-7.36, p=0.594), we found reduced volumes in five patients with combined myelitis and brainstem attacks (B=-76.18, p=0.017). Volumes of entire thalamus and other nuclei were not smaller in patients than controls.

CONCLUSION

These findings suggest attack-related anterograde degeneration rather than diffuse thalamic damage in NMOSD. They also support a potential role of LGN volume as an imaging marker of structural brain damage in these patients.

Hippocampal subfields and visuospatial associative memory across stages of schizophrenia-spectrum disorder

BACKGROUND

While previous studies have identified relationships between hippocampal volumes and memory performance in schizophrenia, these relationships are not apparent in healthy individuals. Further, few studies have examined the role of hippocampal subfields in illness-related memory deficits, and no study has examined potential differences across varying illness stages. The current study aimed to investigate whether individuals with early and established psychosis exhibited differential relationships between visuospatial associative memory and hippocampal subfield volumes.

METHODS

Measurements of visuospatial associative memory performance and grey matter volume were obtained from 52 individuals with a chronic schizophrenia-spectrum disorder, 28 youth with recent-onset psychosis, 52 older healthy controls, and 28 younger healthy controls.

RESULTS

Both chronic and recent-onset patients had impaired visuospatial associative memory performance, however, only chronic patients showed hippocampal subfield volume loss. Both chronic and recent-onset patients demonstrated relationships between visuospatial associative memory performance and hippocampal subfield volumes in the CA4/dentate gyrus and the stratum that were not observed in older healthy controls. There were no group by volume interactions when chronic and recent-onset patients were compared.

CONCLUSIONS

The current study extends the findings of previous studies by identifying particular hippocampal subfields, including the hippocampal stratum layers and the dentate gyrus, that appear to be related to visuospatial associative memory ability in individuals with both chronic and first-episode psychosis.

Tractography-based targeting of the ventral intermediate nucleus: accuracy and clinical utility in MRgFUS thalamotomy

OBJECTIVE

Tractography-based targeting of the thalamic ventral intermediate nucleus (T-VIM) is a novel method conferring patient-specific selection of VIM coordinates for tremor surgery; however, its accuracy and clinical utility in magnetic resonance imaging-guided focused ultrasound (MRgFUS) thalamotomy compared to conventional indirect targeting has not been specifically addressed. This retrospective study sought to compare the treatment locations and potential adverse effect profiles of T-VIM with indirect targeting in a large cohort of MRgFUS thalamotomy patients.

METHODS

T-VIM was performed using diffusion tractography outlining the pyramidal and medial lemniscus tracts in 43 MRgFUS thalamotomy patients. T-VIM coordinates were compared with the indirect treatment coordinates used in the procedure. Thalamotomy lesions were delineated on postoperative T1-weighted images and displaced ("translated") by the anteroposterior and mediolateral difference between T-VIM and treatment coordinates. Both translated and actual lesions were normalized to standard space and subsequently overlaid with areas previously reported to be associated with an increased risk of motor and sensory adverse effects when lesioned during MRgFUS thalamotomy.

RESULTS

T-VIM coordinates were 2.18 mm anterior and 1.82 mm medial to the "final" indirect treatment coordinates. Translated lesions lay more squarely within the boundaries of the VIM compared to nontranslated lesions and showed significantly less overlap with areas associated with sensory adverse effects. Translated lesions overlapped less with areas associated with motor adverse effects; however, this difference was not significant.

CONCLUSIONS

T-VIM leads to the selection of more anterior and medial coordinates than the conventional indirect methods. Lesions moved toward these anteromedial coordinates avoid areas associated with an increased risk of motor and sensory adverse effects, suggesting that T-VIM may improve clinical outcomes.

The P300 event-related potential in bipolar disorder: A systematic review and meta-analysis

BACKGROUND

Neurophysiology including P300, that is a typical index of event-related potential, may be potential biomarkers for bipolar disorder (BD) and it can be useful towards elucidating the pathophysiology of BD. However, previous findings from P300 studies were inconsistent due to the heterogeneity of research methods, which make it difficult to understand the neurobiological significance of them. The aim of this study is to conduct a meta-analysis on P300 in patients with BD.

METHOD

A literature search was conducted using PubMed to identify studies that compared P300 event-related potential between patients with BD and healthy controls (HCs). We analyzed P300 indices such as amplitude and latency of P3a and P3b in auditory or visual paradigms. Further, moderator analyses were conducted to investigate the influence of patient characteristics (i.e. history of psychosis, diagnostic subcategories [BD-I/BD-II], and phase of illness [euthymic, manic, or depressive]) on P300 indices.

RESULT

Out of 124 initial records, we included 30 articles (BD: N = 1331; HCs: N = 1818). Patients with BD showed reduced P3a and P3b amplitude in both paradigms and delayed P3b latency in auditory paradigms compared to HCs. There was no influence on the history of psychosis, diagnostic subcategories, or phase of illness on P300 indices.

LIMITATION

The difference in medication use was difficult to control and it may affect the results.

CONCLUSION

This meta-analysis provides evidence for P300 abnormalities in patients with BD compared to HCs. Our results suggest that P300 may be trait markers rather than state markers in this illness.

Neurologic Examination Findings Associated With Small Cerebellar Volumes After Prematurity

To help clinicians understand what to expect from small cerebellar volumes after prematurity, this study aims to characterize the specific impacts of small cerebellar volumes on the infant neurologic examination. A prospective cohort of preterm newborns (<32 weeks' gestational age) had brain magnetic resonance imaging (MRI) studies at term-equivalent age. Cerebellar volumes were compared with neurologic examination findings in follow-up, adjusting for severity of intraventricular hemorrhage, white matter injury, and cerebellar hemorrhage. Deformation-based analyses delineated regional morphometric differences in the cerebellum associated with these findings. Of 119 infants with MRI scans, 109 (92%) had follow-up at 19.0±1.7 months corrected age. Smaller cerebellar volume at term was associated with increased odds of truncal hypotonia, postural instability on standing, and patellar hyperreflexia (P < .03). Small cerebellar volume defined as <19 cm³ by 40 weeks was associated with 7.5-fold increased odds of truncal hypotonia (P < .001), 8.9-fold odds postural instability (P < .001), and 9.7-fold odds of patellar hyperreflexia (P < .001). Voxel-based deformation-based morphometry showed postural instability associated with paravermian regions. Small cerebellar volume is associated with specific abnormalities on neurologic examination by 18 months of age, including truncal tone, reflexes, and postural stability.

Sex-biased trajectories of amygdalo-hippocampal morphology change over human development

The amygdala and hippocampus are two adjacent allocortical structures implicated in sex-biased and developmentally-emergent psychopathology. However, the spatiotemporal dynamics of amygdalo-hippocampal development remain poorly understood in healthy humans. The current study defined trajectories of volume and shape change for the amygdala and hippocampus by applying a multi-atlas segmentation pipeline (MAGeT-Brain) and semi-parametric mixed-effects spline modeling to 1,529 longitudinally-acquired structural MRI brain scans from a large, single-center cohort of 792 youth (403 males, 389 females) between the ages of 5 and 25 years old. We found that amygdala and hippocampus volumes both follow curvilinear and sexually dimorphic growth trajectories. These sex-biases were particularly striking in the amygdala: males showed a significantly later and slower adolescent deceleration in volume expansion (at age 20 years) than females (age 13 years). Shape analysis localized significant hot-spots of sex-biased anatomical development in sub-regional territories overlying rostral and caudal extremes of the CA1/2 in the hippocampus, and the centromedial nuclear group of the amygdala. In both sexes, principal components analysis revealed close integration of amygdala and hippocampus shape change along two main topographically-organized axes – low vs. high areal expansion, and early vs. late growth deceleration. These results (i) bring greater resolution to our spatiotemporal understanding of amygdalo-hippocampal development in healthy males and females, and (ii) uncover focal sex-differences in the structural maturation of the brain components that may contribute to differences in behavior and psychopathology that emerge during adolescence.

MR-based age-related effects on the striatum, globus pallidus, and thalamus in healthy individuals across the adult lifespan

While numerous studies have used magnetic resonance imaging (MRI) to elucidate normative age‐related trajectories in subcortical structures across the human lifespan, there exists substantial heterogeneity among different studies. Here, we investigated the normative relationships between age and morphology (i.e., volume and shape), and microstructure (using the T1‐weighted/T2‐weighted [T1w/T2w] signal ratio as a putative index of myelin and microstructure) of the striatum, globus pallidus, and thalamus across the adult lifespan using a dataset carefully quality controlled, yielding a final sample of 178 for the morphological analyses, and 162 for the T1w/T2w analyses from an initial dataset of 253 healthy subjects, aged 18–83. In accordance with previous cross‐sectional studies of adults, we observed age‐related volume decrease that followed a quadratic relationship between age and bilateral striatal and thalamic volumes, and a linear relationship in the globus pallidus. Our shape indices consistently demonstrated age‐related posterior and medial areal contraction bilaterally across all three structures. Beyond morphology, we observed a quadratic inverted U‐shaped relationship between T1w/T2w signal ratio and age, with a peak value occurring in middle age (at around 50 years old). After permutation testing, the Akaike information criterion determined age relationships remained significant for the bilateral globus pallidus and thalamus, for both the volumetric and T1w/T2w analyses. Our findings serve to strengthen and expand upon previous volumetric analyses by providing a normative baseline of morphology and microstructure of these structures to which future studies investigating patients with various disorders can be compared.

Hand preference and local asymmetry in cerebral cortex, basal ganglia, and cerebellar white matter

Hand preference is a striking example of functional lateralization, with 90% of the population preferentially using their right hand. However, the search for brain structural correlates of this lateralization has produced inconsistent results. While large-scale neuroimaging studies using automated methods have largely failed to find local anatomical asymmetries associated with hand preference, other studies identifying specific motor regions have been able to find local morphological and functional differences. The present study looked at brain asymmetries in the brain's motor system using established cortical landmarks to identify the somatomotor hand region and extracted regional volumes of subcortical and cerebellar regions. Our results showed a strong left-right asymmetry in the cortical hand region, with weaker asymmetries appearing in the striatum and cerebellar white matter. Such asymmetries were much more pronounced in right-handers, whereas much weaker or absent lateralizing effects were observed in left-handed subjects. This study demonstrates the importance of local landmarks in studying individual anatomical differences. More generally, establishing structural correlates of hand preference is important, as this could further establish the origins of cerebral lateralization.

BDNF-Dependent Effects on Amygdala-Cortical Circuitry and Depression Risk in Children and Youth

The brain-derived neurotrophic factor (BDNF) is critical for brain development, and the functional BDNF Val66Met polymorphism is implicated in risk for mood disorders. The objective of this study was to determine how the Val66Met polymorphism influences amygdala-cortical connectivity during neurodevelopment and assess the relevance for mood disorders. Age- and sex-specific effects of the BDNF Val66Met polymorphism on amygdala-cortical connectivity were assessed by examining covariance of amygdala volumes with thickness throughout the cortex in a sample of Caucasian youths ages 8-22 that were part of the Philadelphia Neurodevelopmental Cohort (n = 339). Follow-up analyses assessed corresponding BDNF genotype effects on resting-state functional connectivity (n = 186) and the association between BDNF genotype and major depressive disorder (MDD) (n = 2749). In adolescents, amygdala-cortical covariance was significantly stronger in Met allele carriers compared with Val/Val homozygotes in amygdala-cortical networks implicated in depression; these differences were driven by females. In follow-up analyses, the Met allele was also associated with stronger resting-state functional connectivity in adolescents and increased likelihood of MDD in adolescent females. The BDNF Val66Met polymorphism may confer risk for mood disorders in females through effects on amygdala-cortical connectivity during adolescence, coinciding with a period in the lifespan when onset of depression often occurs, more commonly in females.

Evidence for Network-Based Cortical Thickness Reductions in Schizophrenia

OBJECTIVE

Cortical thickness reductions in schizophrenia are irregularly distributed across multiple loci. The authors hypothesized that cortical connectivity networks would explain the distribution of cortical thickness reductions across the cortex, and, specifically, that cortico-cortical connectivity between loci with these reductions would be exceptionally strong and form an interconnected network. This hypothesis was tested in three cross-sectional schizophrenia cohorts: first-episode psychosis, chronic schizophrenia, and treatment-resistant schizophrenia.

METHODS

Structural brain images were acquired for 70 patients with first-episode psychosis, 153 patients with chronic schizophrenia, and 47 patients with treatment-resistant schizophrenia and in matching healthy control groups (N=57, N=168, and N=54, respectively). Cortical thickness was compared between the patient and respective control groups at 148 regions spanning the cortex. Structural connectivity strength between pairs of cortical regions was quantified with structural covariance analysis. Connectivity strength between regions with cortical thickness reductions was compared with connectivity strength between 5,000 sets of randomly chosen regions to establish whether regions with reductions were interconnected more strongly than would be expected by chance.

RESULTS

Significant (false discovery rate corrected) and widespread cortical thickness reductions were found in the chronic schizophrenia (79 regions) and treatment-resistant schizophrenia (106 regions) groups, with more circumscribed reductions in the first-episode psychosis group (34 regions). Cortical thickness reductions with the largest effect sizes were found in frontal, temporal, cingulate, and insular regions. In all cohorts, both the patient and healthy control groups showed significantly increased structural covariance between regions with cortical thickness reductions compared with randomly selected regions.

CONCLUSIONS

Brain network architecture can explain the irregular topographic distribution of cortical thickness reductions in schizophrenia. This finding, replicated in three distinct schizophrenia cohorts, suggests that the effect is robust and independent of illness stage.

An artificial neural network model for clinical score prediction in Alzheimer disease using structural neuroimaging measures

Background

The development of diagnostic and prognostic tools for Alzheimer disease is complicated by substantial clinical heterogeneity in prodromal stages. Many neuroimaging studies have focused on case–control classification and predicting conversion from mild cognitive impairment to Alzheimer disease, but predicting scores from clinical assessments (such as the Alzheimer’s Disease Assessment Scale or the Mini Mental State Examination) using MRI data has received less attention. Predicting clinical scores can be crucial in providing a nuanced prognosis and inferring symptomatic severity.

Methods

We predicted clinical scores at the individual level using a novel anatomically partitioned artificial neural network (APANN) model. The model combined input from 2 structural MRI measures relevant to the neurodegenerative patterns observed in Alzheimer disease: hippocampal segmentations and cortical thickness. We evaluated the performance of the APANN model with 10 rounds of 10-fold cross-validation in 3 experiments, using cohorts from the Alzheimer’s Disease Neuroimaging Initiative (ADNI): ADNI1, ADNI2 and ADNI1 + 2.

Results

Pearson correlation and root mean square error between the actual and predicted scores on the Alzheimer’s Disease Assessment Scale (ADNI1: r = 0.60; ADNI2: r = 0.68; ADNI1 + 2: r = 0.63) and Mini Mental State Examination (ADNI1: r = 0.52; ADNI2: r = 0.55; ADNI1 + 2: r = 0.55) showed that APANN can accurately infer clinical severity from MRI data.

Limitations

To rigorously validate the model, we focused primarily on large cross-sectional baseline data sets with only proof-of-concept longitudinal results.

Conclusion

The APANN provides a highly robust and scalable framework for predicting clinical severity at the individual level using high-dimensional, multimodal neuroimaging data.

Role of D3 dopamine receptors in modulating neuroanatomical changes in response to antipsychotic administration

Clinical research has shown that chronic antipsychotic drug (APD) treatment further decreases cortical gray matter and hippocampus volume, and increases striatal and ventricular volume in patients with schizophrenia. D2-like receptor blockade is necessary for clinical efficacy of the drugs, and may be responsible for inducing these volume changes. However, the role of other D2-like receptors, such as D3, remains unclear. Following our previous work, we undertook a longitudinal study to examine the effects of chronic (9-week) typical (haloperidol (HAL)) and atypical (clozapine (CLZ)) APDs on the neuroanatomy of wild-type (WT) and dopamine D3-knockout (D3KO) mice using magnetic resonance imaging (MRI) and histological assessments in a sub-region of the anterior cingulate cortex (the prelimbic [PL] area) and striatum. D3KO mice had larger striatal volume prior to APD administration, coupled with increased glial and neuronal cell density. Chronic HAL administration increased striatal volume in both WT and D3KO mice, and reduced PL area volume in D3KO mice both at trend level. CLZ increased volume of the PL area of WT mice at trend level, but decreased D3KO PL area glial cell density. Both typical and atypical APD administration induced neuroanatomical remodeling of regions rich in D3 receptor expression, and typically altered in schizophrenia. Our findings provide novel insights on the role of D3 receptors in structural changes observed following APD administration in clinical populations.

Larger Amygdala Volume Mediates the Association Between Prenatal Maternal Stress and Higher Levels of Externalizing Behaviors: Sex Specific Effects in Project Ice Storm

Introduction: The amygdala is a brain structure involved in emotional regulation. Studies have shown that larger amygdala volumes are associated with behavioral disorders. Prenatal maternal depression is associated with structural changes in the amygdala, which in turn, is predictive of an increase in behavioral problems. Girls may be particularly vulnerable. However, it is not known whether disaster-related prenatal maternal stress (PNMS), or which aspect of the maternal stress experience (i.e., objective hardship, subjective distress, and cognitive appraisal), influences amygdala volumes. Nor is it known whether amygdala volumes mediate the effect of PNMS on behavioral problems in girls and boys. Aims: To assess whether aspects of PNMS are associated with amygdala volume, to determine whether timing of exposure moderates the effect, and to test whether amygdala volume mediates the association between PNMS and internalizing and externalizing problems in 11½ year old children exposed in utero, to varying levels of disaster-related PNMS. Methods: Bilateral amygdala volumes (AGV) and total brain volume (TBV) were acquired using magnetic resonance imaging, from 35 boys and 33 girls whose mothers were pregnant during the January 1998 Quebec Ice Storm. The mothers' disaster-related stress was assessed in June 1998. Child internalizing and externalizing problems were assessed at 11½ years using the Child Behavior Checklist (CBCL). Hierarchical regression analyses and mediation analyses were conducted on boys and girls separately, controlling for perinatal and postnatal factors. Results: In boys, subjective distress was associated with larger right AGV/TBV when mothers where exposed during late pregnancy, which in turn explained higher levels of externalizing behavior. However, when adjusting for postnatal factors, the effect was no longer significant. In girls, later gestational exposure to the ice storm was associated with larger AGV/TBV, but here, higher levels of objective PNMS were associated with more externalizing problems, which was, in part, mediated by larger AGV/TBV. No effects were detected on internalizing behaviors. Conclusion: These results suggest that the effects of PNMS on amygdala development and externalizing symptoms, as assessed in boys and girls in early adolescence, can be influenced by the timing of the stress in pregnancy, and the particular aspect of the mother's stress experience.

Hippocampal alterations and functional correlates in adolescents and young adults with congenital heart disease

There is a high prevalence of neurodevelopmental impairments in individuals living with congenital heart disease (CHD) and the neural correlates of these impairments are not yet fully understood. Recent studies have shown that hippocampal volume and shape differences may provide unique biomarkers for neurodevelopmental disorders. The hippocampus is vulnerable to early life injury, especially in populations at risk for hypoxemia or hemodynamic instability such as in neonates with CHD. We compared hippocampal gray and white matter volume and morphometry between youth born with CHD (n = 50) aged 16-24 years and healthy peers (n = 48). We also explored whether hippocampal gray and white matter volume and morphometry are associated with executive function and self-regulation deficits. To do so, participants underwent 3T brain magnetic resonance imaging and completed the self-reported Behavior Rating Inventory of Executive Function-Adult version. We found that youth with CHD had smaller hippocampal volumes (all statistics corrected for false discovery rate; q < 0.05) as compared to controls. We also observed significant smaller surface area bilaterally and inward displacement on the left hippocampus predominantly on the ventral side (q < 0.10) in the CHD group that were not present in the controls. Left CA1 and CA2/3 were negatively associated with working memory (p < .05). Here, we report, for the first-time, hippocampal morphometric alterations in youth born with CHD when compared to healthy peers, as well as, structure-function relationships between hippocampal volumes and executive function. These differences may reflect long lasting alterations in brain development specific to individual with CHD.

Trait impulsivity is not related to post-commissural putamen volumes: A replication study in healthy men

High levels of trait impulsivity are considered a risk factor for substance abuse and drug addiction. We recently found that non-planning trait impulsivity was negatively correlated with post-commissural putamen volumes in men, but not women, using the Karolinska Scales of Personality (KSP). Here, we attempted to replicate this finding in an independent sample using an updated version of the KSP: the Swedish Universities Scales of Personality (SSP). Data from 88 healthy male participants (Mean Age: 28.16±3.34), who provided structural T1-weighted magnetic resonance images (MRIs) and self-reported SSP impulsivity scores, were analyzed. Striatal sub-region volumes were acquired using the Multiple Automatically Generated Templates (MAGeT-Brain) algorithm. Contrary to our previous findings trait impulsivity measured using SSP was not a significant predictor of post-commissural putamen volumes (β = .14, df = 84, p = .94). A replication Bayes Factors analysis strongly supported this null result. Consistent with our previous findings, secondary exploratory analyses found no relationship between ventral striatum volumes and SSP trait impulsivity (β = -.05, df = 84, p = .28). An exploratory analysis of the other striatal compartments showed that there were no significant associations with trait impulsivity. While we could not replicate our previous findings in the current sample, we believe this work will aide future studies aimed at establishing meaningful brain biomarkers for addiction vulnerability in healthy humans.

Cortical abnormalities in episodic migraine: A multi-center 3T MRI study

BACKGROUND

Several previous studies have investigated cortical abnormalities, specifically cortical thickness, in patients with migraine, with variable results. The relatively small sample sizes of most previous studies may partially explain these inconsistencies.

OBJECTIVE

To investigate differences of cortical thickness between control subjects and migraineurs in a large cohort.

METHODS

Three Tesla MRI data of 131 patients (38 with and 93 without aura) and 115 control subjects were analysed. A vertex-wise linear model was applied controlling for age, gender and MRI scanner to investigate differences between groups and determine the impact of clinical factors on cortical thickness measures.

RESULTS

Migraineurs showed areas of thinned cortex compared with controls bilaterally in the central sulcus, in the left middle-frontal gyrus, in left visual cortices and the right occipito-temporal gyrus. Frequency of migraine attacks and the duration of the disorder had a significant impact on cortical thickness in the sensorimotor cortex and middle-frontal gyrus. Patients without aura showed thinner cortex than controls bilaterally in the central sulcus and in the middle frontal gyrus, in the left primary visual cortices, in the left supramarginal gyrus and in the right cuneus. Patients with aura showed clusters of thinner cortex bilaterally in the subparietal sulcus (between the precuneus and posterior cingulate cortex), in the left intraparietal sulcus and in the right anterior cingulate.

CONCLUSION

These results indicate cortical abnormalities in specific brain regions in migraineurs. Some of the observed abnormalities may reflect a genetic susceptibility towards developing migraine attacks, while others are probably a consequence of repeated head pain attacks.