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Despite the constant improvement of algorithms for automated brain tissue classification, the accurate delineation of subcortical structures using magnetic resonance images (MRI) data remains challenging. The main difficulties arise from the low gray-white matter contrast of iron rich areas in T1-weighted (T1w) MRI data and from the lack of adequate priors for basal ganglia and thalamus. The most recent attempts to obtain such priors were based on cohorts with limited size that included subjects in a narrow age range, failing to account for age-related gray-white matter contrast changes. Aiming to improve the anatomical plausibility of automated brain tissue classification from T1w data, we have created new tissue probability maps for subcortical gray matter regions. Supported by atlas-derived spatial information, raters manually labeled subcortical structures in a cohort of healthy subjects using magnetization transfer saturation and R2* MRI maps, which feature optimal gray-white matter contrast in these areas. After assessment of inter-rater variability, the new tissue priors were tested on T1w data within the framework of voxel-based morphometry. The automated detection of gray matter in subcortical areas with our new probability maps was more anatomically plausible compared to the one derived with currently available priors. We provide evidence that the improved delineation compensates age-related bias in the segmentation of iron rich subcortical regions. The new tissue priors, allowing robust detection of basal ganglia and thalamus, have the potential to enhance the sensitivity of voxel-based morphometry in both healthy and diseased brains. •We create new tissue probability maps of subcortical structures based on magnetization transfer saturation and R2* MRI data.•We obtain anatomically plausible delineation of subcortical structures from T1w data with the new tissue probability maps.•Automated tissue classification with the new tissue probability maps is more robust against the age impact on MR contrast.

After more than eight decades of electroconvulsive therapy (ECT) for pharmaco-resistant depression, the mechanisms governing its anti-depressant effects remain poorly understood. Computational anatomy studies using longitudinal T1-weighted magnetic resonance imaging (MRI) data have demonstrated ECT effects on hippocampus volume and cortical thickness, but they lack the interpretational specificity about underlying neurobiological processes. We sought to fill in the gap of knowledge by acquiring quantitative MRI indicative for brain's myelin, iron and tissue water content at multiple time-points before, during and after ECT treatment. We adapted established tools for longitudinal spatial registration of MRI data to the relaxometry-based multi-parameter maps aiming to preserve the initial total signal amount and introduced a dedicated multivariate analytical framework. The whole-brain voxel-based analysis based on a multivariate general linear model showed that there is no brain tissue oedema contributing to the predicted ECT-induced hippocampus volume increase neither in the short, nor in the long-term observations. Improvements in depression symptom severity over time were associated with changes in both volume estimates and brain tissue properties expanding beyond mesial temporal lobe structures to anterior cingulate cortex, precuneus and striatum. The obtained results stemming from multi-contrast MRI quantitative data provided a fingerprint of ECT-induced brain tissue changes over time that are contrasted against the background of established morphometry findings. The introduced data processing and statistical testing algorithms provided a reliable analytical framework for longitudinal multi-parameter brain maps. The results, particularly the evidence of lack of ECT impact on brain tissue water, should be considered preliminary considering the small sample size of the study.

Anatomical structures and mechanisms linking genes to neuropsychiatric disorders are not deciphered. Reciprocal copy number variants at the 16p11.2 BP4-BP5 locus offer a unique opportunity to study the intermediate phenotypes in carriers at high risk for autism spectrum disorder (ASD) or schizophrenia (SZ). We investigated the variation in brain anatomy in 16p11.2 deletion and duplication carriers. Beyond gene dosage effects on global brain metrics, we show that the number of genomic copies negatively correlated to the gray matter volume and white matter tissue properties in cortico-subcortical regions implicated in reward, language and social cognition. Despite the near absence of ASD or SZ diagnoses in our 16p11.2 cohort, the pattern of brain anatomy changes in carriers spatially overlaps with the well-established structural abnormalities in ASD and SZ. Using measures of peripheral mRNA levels, we confirm our genomic copy number findings. This combined molecular, neuroimaging and clinical approach, applied to larger datasets, will help interpret the relative contributions of genes to neuropsychiatric conditions by measuring their effect on local brain anatomy.

This study set out to examine the role of different adversities experienced at different life course stages on cognitive aging (i.e., level and change). Data from the longitudinal study: Survey of Health, Ageing, and Retirement in Europe (SHARE) with the selection of participants over 60 years were used ( N  = 2662, Mdn age  = 68, SD age  = 5.39) in a Structural Equation Modeling. In early life, the experience of hunger predicted lower delayed recall (β = − 0.10, p  < 0.001) and verbal fluency (β = − 0.06, p  = 0.001) performance in older age, whereas financial hardship predicted lower verbal fluency (β = − 0.06, p  = 0.005) performance and steeper decline in delayed recall (β = − 0.11, p  < 0.001). In early adulthood, financial hardship and stress predicted better delayed recall (financial hardship: β = 0.08, p  = 0.001; stress: β = 0.07, p  = 0.003) and verbal fluency performance (financial hardship: β = 0.08, p  = 0.001; stress β = 0.10, p  < 0.001), but no adversities were associated with a change in cognitive performance. In middle adulthood, no adversities were associated with the level of cognitive performance, but financial hardship predicted lower decline in delayed recall (β = 0.07, p  = 0.048). This study highlights the importance of disentangling the period effect from the specific effect of the adversity experienced in the association between adversity and cognition in older age. Moreover, differential results for delayed recall and verbal fluency measures suggest that it is also important to consider the cognitive outcome domains examined.

Normal ageing is associated with characteristic changes in brain microstructure. Although in vivo neuroimaging captures spatial and temporal patterns of age-related changes of anatomy at the macroscopic scale, our knowledge of the underlying (patho)physiological processes at cellular and molecular levels is still limited. The aim of this study is to explore brain tissue properties in normal ageing using quantitative magnetic resonance imaging (MRI) alongside conventional morphological assessment. Using a whole-brain approach in a cohort of 26 adults, aged 18–85years, we performed voxel-based morphometric (VBM) analysis and voxel-based quantification (VBQ) of diffusion tensor, magnetization transfer (MT), R1, and R2* relaxation parameters. We found age-related reductions in cortical and subcortical grey matter volume paralleled by changes in fractional anisotropy (FA), mean diffusivity (MD), MT and R2*. The latter were regionally specific depending on their differential sensitivity to microscopic tissue properties. VBQ of white matter revealed distinct anatomical patterns of age-related change in microstructure. Widespread and profound reduction in MT contrasted with local FA decreases paralleled by MD increases. R1 reductions and R2* increases were observed to a smaller extent in overlapping occipito-parietal white matter regions. We interpret our findings, based on current biophysical models, as a fingerprint of age-dependent brain atrophy and underlying microstructural changes in myelin, iron deposits and water. The VBQ approach we present allows for systematic unbiased exploration of the interaction between imaging parameters and extends current methods for detection of neurodegenerative processes in the brain. The demonstrated parameter-specific distribution patterns offer insights into age-related brain structure changes in vivo and provide essential baseline data for studying disease against a background of healthy ageing. ►High-resolution FLASH-based parameter mapping is suitable for clinical purposes. ►Patterns of age-dependent parameter changes reflect specificity to tissue properties. ►Combining VBM and VBQ offers complementary information about brain architecture.

IntroductionThe association between CYP2C19 poor metabolizer status, depressive symptom severity and hippocampal volume in humans is controversial. Progress in understanding not only the pathophysiology of depression but also potential protective mechanisms is important both for daily clinical practice and for the development of new antidepressant therapies.ObjectivesTo test and validate previous findings regarding the impact of CYP2C19 status on depressive symptoms and to examine whether it could influence hippocampus subregions and brain tissue microstructure.MethodsA total of 4152 individuals from the Longitudinal cohort in the community-dwelling adult population - Colaus|PsyCoLaus in Lausanne, Switzerland were included. They have participated in at least one psychiatric evaluation. Brain anatomy patterns using a comprehensive set of psychometry, water diffusion- and relaxometry-based magnetic resonance imaging data were analysed in a subset of the cohort (BrainLaus, n=1187).ResultsIn this population-based cohort study, better lifetime global assessment of functioning scores were observed in poor metabolizers when compared to other metabolizers, this result was mainly driven by female participants (ß=3.9, P=0.01). Examination of brain imaging data revealed that higher right hippocampal subiculum volume was related to poor metabolizer status (ß=0.03, P=0.006). In addition, associations were observed between metabolizer status and white matter microstructure in the left uncinate fasciculus (ß=-0.01, P=0.01) and the left cingulum bundle (ß=-0.01, P=0.01).ConclusionsCYP2C19 status is associated with modifications in lifetime global functioning, and brain anatomy. Such differences in brain structures can contribute to explain the protective effect of CYP2C19 poor metabolizer status.DisclosureNo significant relationships.

Evidence from magnetic resonance imaging (MRI) studies shows that healthy aging is associated with profound changes in cortical and subcortical brain structures. The reliable delineation of cortex and basal ganglia using automated computational anatomy methods based on T1-weighted images remains challenging, which results in controversies in the literature. In this study we use quantitative MRI (qMRI) to gain an insight into the microstructural mechanisms underlying tissue ageing and look for potential interactions between ageing and brain tissue properties to assess their impact on automated tissue classification. To this end we acquired maps of longitudinal relaxation rate R1, effective transverse relaxation rate R2* and magnetization transfer – MT, from healthy subjects (n=96, aged 21–88years) using a well-established multi-parameter mapping qMRI protocol. Within the framework of voxel-based quantification we find higher grey matter volume in basal ganglia, cerebellar dentate and prefrontal cortex when tissue classification is based on MT maps compared with T1 maps. These discrepancies between grey matter volume estimates can be attributed to R2* - a surrogate marker of iron concentration, and further modulation by an interaction between R2* and age, both in cortical and subcortical areas. We interpret our findings as direct evidence for the impact of ageing-related brain tissue property changes on automated tissue classification of brain structures using SPM12. Computational anatomy studies of ageing and neurodegeneration should acknowledge these effects, particularly when inferring about underlying pathophysiology from regional cortex and basal ganglia volume changes. •We acquire quantitative bias free whole-brain maps of MT, R1 and R2* parameters.•Grey matter volume estimation based on MT maps is higher than the R1-based in specific cortical and subcortical areas.•Differences in grey matter volume estimations are correlated with iron concentration and further modulated by age.•Iron decreases locally the grey-white matter contrast in R1 but not in MT maps.

Modern neuroscience has elucidated general mechanisms underlying the functional plasticity of the adult mammalian brain after limb deafferentation. However, little is known about possible structural alterations following amputation and chronic loss of afferent input in humans. Using voxel-based morphometry (VBM), based on high-resolution magnetic resonance images, we investigated the brain structure of 28 volunteers with unilateral limb amputation and compared them to healthy controls. Subjects with limb amputation exhibited a decrease in gray matter of the posterolateral thalamus contralateral to the side of the amputation. The thalamic gray matter differences were positively correlated with the time span after the amputation but not with the frequency or magnitude of coexisting phantom pain. Phantom limb pain was unrelated to thalamic structural variations, but was positively correlated to a decrease in brain areas related to the processing of pain. No gray matter increase was detected. The unilateral thalamic differences may reflect a structural correlate of the loss of afferent input as a secondary change following deafferentation.

Background: The 600 kb BP4-BP5 copy number variants (CNVs) at the 16p11.2 locus have been associated with a range of neurodevelopmental conditions including autism spectrum disorders and schizophrenia. The number of genomic copies in this region is inversely correlated with body mass index (BMI): the deletion is associated with a highly penetrant form of obesity (present in 50% of carriers by the age of 7 years and in 70% of adults), and the duplication with being underweight. Mechanisms underlying this energy imbalance remain unknown. Objective: This study aims to investigate eating behavior, cognitive traits and their relationships with BMI in carriers of 16p11.2 CNVs. Methods: We assessed individuals carrying a 16p11.2 deletion or duplication and their intrafamilial controls using food-related behavior questionnaires and cognitive measures. We also compared these carriers with cohorts of individuals presenting with obesity, binge eating disorder or bulimia. Results: Response to satiety is gene dosage-dependent in pediatric CNV carriers. Altered satiety response is present in young deletion carriers before the onset of obesity. It remains altered in adolescent carriers and correlates with obesity. Adult deletion carriers exhibit eating behavior similar to that seen in a cohort of obesity without eating disorders such as bulimia or binge eating. None of the cognitive measures are associated with eating behavior or BMI. Conclusions: These findings suggest that abnormal satiety response is a strong contributor to the energy imbalance in 16p11.2 CNV carriers, and, akin to other genetic forms of obesity, altered satiety responsiveness in children precedes the increase in BMI observed later in adolescence.

Our understanding of how genotype determines phenotype in primary dystonia is limited. Familial young-onset primary dystonia is commonly due to the DYT1 gene mutation. A critical question, given the 30% penetrance of clinical symptoms in DYT1 mutation carriers, is why the same genotype leads to differential clinical expression and whether non-DYT1 adult-onset primary dystonia, with and without family history share pathophysiological mechanisms with DYT1 dystonia. This study examines the relationship between dystonic phenotype and the DYT1 gene mutation by monitoring whole-brain structure using voxel-based morphometry. We acquired magnetic resonance imaging data of symptomatic and asymptomatic DYT1 mutation carriers, of non-DYT1 primary dystonia patients, with and without family history and control subjects with normal DYT1 alleles. By crossing the factors genotype and phenotype we demonstrate a significant interaction in terms of brain anatomy confined to the basal ganglia bilaterally. The explanation for this effect differs according to both gene and dystonia status: non-DYT1 adult-onset dystonia patients and asymptomatic DYT1 carriers have significantly larger basal ganglia compared to healthy subjects and symptomatic DYT1 mutation carriers. There is a significant negative correlation between severity of dystonia and basal ganglia size in DYT1 mutation carriers. We propose that differential pathophysiological and compensatory mechanisms lead to brain structure changes in non-DYT1 primary adult-onset dystonias and DYT1 gene carriers. Given the range of age of onset, there may be differential genetic modulation of brain development that in turn determines clinical expression. Alternatively, a DYT1 gene dependent primary defect of motor circuit development may lead to stress-induced remodelling of the basal ganglia and hence dystonia.