Variation In Brain Morphology Research Articles

Abundant pleiotropy across neuroimaging modalities identified through a multivariate genome-wide association study

Genetic pleiotropy is abundant across spatially distributed brain characteristics derived from one neuroimaging modality (e.g. structural, functional or diffusion magnetic resonance imaging [MRI]). A better understanding of pleiotropy across modalities could inform us on the integration of brain function, micro- and macrostructure. Here we show extensive genetic overlap across neuroimaging modalities at a locus and gene level in the UK Biobank (N = 34,029) and ABCD Study (N = 8607). When jointly analysing phenotypes derived from structural, functional and diffusion MRI in a genome-wide association study (GWAS) with the Multivariate Omnibus Statistical Test (MOSTest), we boost the discovery of loci and genes beyond previously identified effects for each modality individually. Cross-modality genes are involved in fundamental biological processes and predominantly expressed during prenatal brain development. We additionally boost prediction of psychiatric disorders by conditioning independent GWAS on our multimodal multivariate GWAS. These findings shed light on the shared genetic mechanisms underlying variation in brain morphology, functional connectivity, and tissue composition.

Natural variability in bee brain size and symmetry revealed by micro-CT imaging and deep learning.

Analysing large numbers of brain samples can reveal minor, but statistically and biologically relevant variations in brain morphology that provide critical insights into animal behaviour, ecology and evolution. So far, however, such analyses have required extensive manual effort, which considerably limits the scope for comparative research. Here we used micro-CT imaging and deep learning to perform automated analyses of 3D image data from 187 honey bee and bumblebee brains. We revealed strong inter-individual variations in total brain size that are consistent across colonies and species, and may underpin behavioural variability central to complex social organisations. In addition, the bumblebee dataset showed a significant level of lateralization in optic and antennal lobes, providing a potential explanation for reported variations in visual and olfactory learning. Our fast, robust and user-friendly approach holds considerable promises for carrying out large-scale quantitative neuroanatomical comparisons across a wider range of animals. Ultimately, this will help address fundamental unresolved questions related to the evolution of animal brains and cognition.

Temperature and the microbial environment alter brain morphology in a larval amphibian.

Understanding how the global climate impacts the physiology of wildlife animals is of importance. Amphibians are particularly sensitive to climate change, and it is hypothesized that rising temperatures impair their neurodevelopment. Temperature influences the composition of the gut microbiota, which is critical to host neurodevelopment through the microbiota-gut-brain (MGB) axis. Most research investigating the link between the gut microbiota and neurodevelopment occurs in germ-free mammalian model systems, leaving the nature of the MGB axis in non-mammalian wildlife unclear. Here, we tested the hypothesis that the temperature and the microbial environment in which tadpoles were raised shapes neurodevelopment, possibly through the MGB axis. Newly hatched green frog tadpoles (Lithobates clamitans) were raised in natural pond water or autoclaved pond water, serving as an experimental manipulation of the microbiota by reducing colonizing microbes, at three different water temperatures: 14, 22 and 28°C. Neurodevelopment was analyzed through measures of relative brain mass and morphology of brain structures of interest. We found that tadpole development in warmer temperatures increased relative brain mass and optic tectum width and length. Further, tadpole development in autoclaved pond water increased relative optic tectum width and length. Additionally, the interaction of treatments altered relative diencephalon length. Lastly, we found that variation in brain morphology was associated with gut microbial diversity and the relative abundance of individual bacterial taxa. Our results indicate that both environmental temperature and microbial communities influence relative brain mass and shape. Furthermore, we provide some of the first evidence for the MGB axis in amphibians.

The effect of experimental hybridization on cognition and brain anatomy: Limited phenotypic variation and transgression in Poeciliidae.

Hybridization can promote phenotypic variation and often produces trait combinations distinct from the parental species. This increase in available variation can lead to the manifestation of functional novelty when new phenotypes bear adaptive value under the environmental conditions in which they occur. Although the role of hybridization as a driver of variation and novelty in traits linked to fitness is well recognized, it remains largely unknown whether hybridization can fuel behavioral novelty by promoting phenotypic variation in brain morphology and/or cognitive traits. To address this question, we investigated the effect of hybridization on brain anatomy, learning ability, and cognitive flexibility in first- and second-generation hybrids of two closely related fish species (Poecilia reticulata and Poecilia wingei). Overall, we found that F1 and F2 hybrids showed intermediate brain morphology and cognitive traits compared to parental groups. Moreover, as phenotypic dispersion and transgression were low for both brain and cognitive traits, we suggest that hybridization is not a strong driver of brain anatomical and cognitive diversification in these Poeciliidae. To determine the generality of this conclusion, hybridization experiments with cognitive tests need to be repeated in other families.

Brain morphology correlates of learning and cognitive flexibility in a fish species (Poecilia reticulata).

Determining how variation in brain morphology affects cognitive abilities is important to understand inter-individual variation in cognition and, ultimately, cognitive evolution. Yet, despite many decades of research in this area, there is surprisingly little experimental data available from assays that quantify cognitive abilities and brain morphology in the same individuals. Here, we tested female guppies (Poecilia reticulata) in two tasks, colour discrimination and reversal learning, to evaluate their learning abilities and cognitive flexibility. We then estimated the size of five brain regions (telencephalon, optic tectum, hypothalamus, cerebellum and dorsal medulla), in addition to relative brain size. We found that optic tectum relative size, in relation to the rest of the brain, correlated positively with discrimination learning performance, while relative telencephalon size correlated positively with reversal learning performance. The other brain measures were not associated with performance in either task. By evaluating how fast learning occurs and how fast an animal adjusts its learning rules to changing conditions, we find support for that different brain regions have distinct functional correlations at the individual level. Importantly, telencephalon size emerges as an important neural correlate of higher executive functions such as cognitive flexibility. This is rare evidence supporting the theory that more neural tissue in key brain regions confers cognitive benefits.

Two distinct evolutionary conserved neural degeneration pathways characterized in a colonial chordate

Colonial tunicates are marine organisms that possess multiple brains simultaneously during their colonial phase. While the cyclical processes of neurogenesis and neurodegeneration characterizing their life cycle have been documented previously, the cellular and molecular changes associated with such processes and their relationship with variation in brain morphology and individual (zooid) behavior throughout adult life remains unknown. Here, we introduce Botryllus schlosseri as an invertebrate model for neurogenesis, neural degeneration, and evolutionary neuroscience. Our analysis reveals that during the weekly colony budding (i.e., asexual reproduction), prior to programmed cell death and removal by phagocytes, decreases in the number of neurons in the adult brain are associated with reduced behavioral response and significant change in the expression of 73 mammalian homologous genes associated with neurodegenerative disease. Similarly, when comparing young colonies (1 to 2 y of age) to those reared in a laboratory for ∼20 y, we found that older colonies contained significantly fewer neurons and exhibited reduced behavioral response alongside changes in the expression of 148 such genes (35 of which were differentially expressed across both timescales). The existence of two distinct yet apparently related neurodegenerative pathways represents a novel platform to study the gene products governing the relationship between aging, neural regeneration and degeneration, and loss of nervous system function. Indeed, as a member of an evolutionary clade considered to be a sister group of vertebrates, this organism may be a fundamental resource in understanding how evolution has shaped these processes across phylogeny and obtaining mechanistic insight.

Comparing personalized brain-based and genetic risk scores for major depressive disorder in large population samples of adults and adolescents.

Major depressive disorder (MDD) is a polygenic disorder associated with brain alterations but until recently, there have been no brain-based metrics to quantify individual-level variation in brain morphology. Here, we evaluated and compared the performance of a new brain-based 'Regional Vulnerability Index' (RVI) with polygenic risk scores (PRS), in the context of MDD. We assessed associations with syndromal MDD in an adult sample (N=702, age=59±10) and with subclinical depressive symptoms in a longitudinal adolescent sample (baseline N=3,825, age=10±1; 2-year follow-up N=2,081, age=12±1). MDD-RVIs quantify the correlation of the individual's corresponding brain metric with the expected pattern for MDD derived in an independent sample. Using the same methodology across samples, subject-specific MDD-PRS and six MDD-RVIs based on different brain modalities (subcortical volume, cortical thickness, cortical surface area, mean diffusivity, fractional anisotropy, and multimodal) were computed. In adults, MDD-RVIs (based on white matter and multimodal measures) were more strongly associated with MDD (β=0.099-0.281, PFDR=0.001-0.043) than MDD-PRS (β=0.056-0.152, PFDR=0.140-0.140). In adolescents, depressive symptoms were associated with MDD-PRS at baseline and follow-up (β=0.084-0.086, p=1.38×10-4-4.77×10-4) but not with any MDD-RVIs (β<0.05, p>0.05). Our results potentially indicate the ability of brain-based risk scores to capture a broader range of risk exposures than genetic risk scores in adults and are also useful in helping us to understand the temporal origins of depression-related brain features. Longitudinal data, specific to the developmental period and on white matter measures, will be useful in informing risk for subsequent psychiatric illness.

Brain morphological adaptations of Gambusia affinis along climatic gradients in China

Many studies have confirmed the impact of the environment on the brain. However, it is still controversial whether the cause of the change is phenotypically plastic or heritable. In this study, we studied morphological variations of the brain among Gambusia affinis obtained from 10 different populations in China. We found that the sizes of total brain and brain regions were affected by climatic gradients. For instance, there was a decrease in the volume of olfactory bulbs, optic tectum, corpus cerebelli, and total brain from north to south. Common-garden experiments indicated that the variations in the sizes of the hypothalamus and the total brain were heritable, while that of other brain regions were phenotypically plastic. Variation in brain morphology of wild fish supports the mosaic hypothesis. The common-garden experiments provide a reference for heritability estimates and phenotypic plasticity of brain volumes. In addition, our study has laid the foundation for in-depth research on the adaptive evolution of the brain of G. affinis.

Multivariate analysis reveals shared genetic architecture of brain morphology and human behavior

Human variation in brain morphology and behavior are related and highly heritable. Yet, it is largely unknown to what extent specific features of brain morphology and behavior are genetically related. Here, we introduce a computationally efficient approach for multivariate genomic-relatedness-based restricted maximum likelihood (MGREML) to estimate the genetic correlation between a large number of phenotypes simultaneously. Using individual-level data (N = 20,190) from the UK Biobank, we provide estimates of the heritability of gray-matter volume in 74 regions of interest (ROIs) in the brain and we map genetic correlations between these ROIs and health-relevant behavioral outcomes, including intelligence. We find four genetically distinct clusters in the brain that are aligned with standard anatomical subdivision in neuroscience. Behavioral traits have distinct genetic correlations with brain morphology which suggests trait-specific relevance of ROIs. These empirical results illustrate how MGREML can be used to estimate internally consistent and high-dimensional genetic correlation matrices in large datasets.

Variation in brain anatomy in frogs and its possible bearing on their locomotor ecology.

Despite the long-standing interest in the evolution of the brain, relatively little is known about variation in brain anatomy in frogs. Yet, frogs are ecologically diverse and, as such, variation in brain anatomy linked to differences in lifestyle or locomotor behavior can be expected. Here we present a comparative morphological study focusing on the macro- and micro-anatomy of the six regions of the brain and its choroid plexus: the olfactory bulbs, the telencephalon, the diencephalon, the mesencephalon, the rhombencephalon, and the cerebellum. We also report on the comparative anatomy of the plexus brachialis responsible for the innervation of the forelimbs. It is commonly thought that amphibians have a simplified brain organization, associated with their supposedly limited behavioral complexity and reduced motor skills. We compare frogs with different ecologies that also use their limbs in different contexts and for other functions. Our results show that brain morphology is more complex and more variable than typically assumed. Moreover, variation in brain morphology among species appears related to locomotor behavior as suggested by our quantitative analyses. Thus we propose that brain morphology may be related to the locomotor mode, at least in the frogs included in our analysis.

Individual Differences in Human Path Integration Abilities Correlate with Gray Matter Volume in Retrosplenial Cortex, Hippocampus, and Medial Prefrontal Cortex.

Humans differ in their individual navigational abilities. These individual differences may exist in part because successful navigation relies on several disparate abilities, which rely on different brain structures. One such navigational capability is path integration, the updating of position and orientation, in which navigators track distances, directions, and locations in space during movement. Although structural differences related to landmark-based navigation have been examined, gray matter volume related to path integration ability has not yet been tested. Here, we examined individual differences in two path integration paradigms: (1) a location tracking task and (2) a task tracking translational and rotational self-motion. Using voxel-based morphometry, we related differences in performance in these path integration tasks to variation in brain morphology in 26 healthy young adults. Performance in the location tracking task positively correlated with individual differences in gray matter volume in three areas critical for path integration: the hippocampus, the retrosplenial cortex, and the medial prefrontal cortex. These regions are consistent with the path integration system known from computational and animal models and provide novel evidence that morphological variability in retrosplenial and medial prefrontal cortices underlies individual differences in human path integration ability. The results for tracking rotational self-motion—but not translation or location—demonstrated that cerebellum gray matter volume correlated with individual performance. Our findings also suggest that these three aspects of path integration are largely independent. Together, the results of this study provide a link between individual abilities and the functional correlates, computational models, and animal models of path integration.

Effects of cranial integration on hominid endocranial shape.

Because brains do not fossilize, the internal surface of the braincase (endocast) serves as an important source of information about brain growth, development, and evolution. Recent studies of endocranial morphology and development in great apes, fossil hominins, and modern humans have revealed taxon-specific differences. However, it remains to be investigated to which extent differences in endocranial morphology reflect differences in actual brain morphology and development, and to which extent they reflect different interactions of the brain and its case with the cranial base and face. Here we address this question by analyzing the effects of cranial integration on endocranial morphology. We test the 'spatial packing' and 'facial orientation' hypotheses, which propose that size and orientation of the neurocranium relative to the viscerocranium influence endocranial shape. Results show that a substantial proportion of endocranial shape variation along and across ontogenetic trajectories is due to cranial integration. Specifically, the uniquely globular shape of the human endocast mainly results from the combination of an exceptionally large brain with a comparatively small face. Overall, thus, cranial integration has pervasive effects on endocranial morphology, and only a comparatively small proportion of inter- and intra-taxon variation can directly be associated with variation in brain morphology.

FoxP1 Protein Shows Differential Layer Expression in the Parahippocampal Domain among Bird Species

Different bird orders show diversity in neural capabilities supported by variations in brain morphology. The parahippocampal domain in the medial pallium, together with the hippocampus proper, plays an important role in memory skills. In the present work, we analyze the expression pattern of the FoxP1 protein in the parahippocampal area of four different bird species: the nonvocal learner birds quail and chicken (Galliformes) and two vocal learner birds, i.e. the zebra finch (Passeriformes) and the budgerigar (Psittaciformes), at different developmental and adult stages. We also analyze the expression of the calbindin protein in quails and zebra finches. We observed differences in the FoxP1 parahippocampal layer among bird species. In quails, chickens, and budgerigar, FoxP1 cells were located in the outer layers of the lateral and caudolateral parahippocampal sectors. In contrast, FoxP1 immunoreactive cells appeared in the inner layer of the same sectors in the zebra finch parahippocampal domain. These differences suggest two possibilities: either the FoxP1-positive cells described in quails, chickens, and budgerigars are a different population than the one described in the zebra finch, or there are changes in the pattern of radial migration in the parahippocampal area among birds. In the present study, we show that FoxP1 expression is more similar between quails, chickens, and budgerigars than between budgerigars and zebra finches in the parahippocampal area. This result contrasts with previous data in other telencephalic structures, like the calbindin-positive projection neurons described in the striatum of budgerigars and zebra finches but not in quails and chickens. All of these data point to diversity in the evolution of different morphological characters and, therefore, a mosaic model for telencephalic evolution in birds.

Prefrontal lobe structural integrity and trail making test, part B: converging findings from surface-based cortical thickness and voxel-based lesion symptom analyses

Surface-based cortical thickness (CT) analyses are increasingly being used to investigate variations in brain morphology across the spectrum of brain health, from neurotypical to neuropathological. An outstanding question is whether individual differences in cortical morphology, such as regionally increased or decreased CT, are associated with domain-specific performance deficits in healthy adults. Since CT studies are correlational, they cannot establish causality between brain morphology and cognitive performance. A direct comparison with classic lesion methods is needed to determine whether the regional specificity of CT-cognition correlations is similar to that observed in patients with brain lesions. We address this question by comparing the neuroanatomical overlap of effects when 1) whole brain vertex-wise CT is tested as a correlate of performance variability on a commonly used neuropsychological test of executive function, Trailmaking Test Part B (TMT-B), in healthy adults and 2) voxel-based lesion-symptom mapping (VBLSM) is used to map lesion location to performance decrements on the same task in patients with frontal lobe lesions. We found that reduced performance on the TMT-B was associated with increased CT in bilateral prefrontal regions in healthy adults and that results spatially overlapped in the left dorsomedial prefrontal cortex with findings from the VBLSM analysis in patients with frontal brain lesions. Findings indicate that variations in the structural integrity of the left dorsomedial prefrontal lobe, ranging from individual CT differences in healthy adults to structural lesions in patients with neurological disorders, are associated with poor performance on the TMT-B. These converging results suggest that the left dorsomedial prefrontal region houses a critical region for the complex processing demands of TMT-B, which include visuomotor tracking, sequencing, and cognitive flexibility.

Variation in Brain Morphology of Intertidal Gobies: A Comparison of Methodologies Used to Quantitatively Assess Brain Volumes in Fish

When correlating brain size and structure with behavioural and environmental characteristics, a range of techniques can be utilised. This study used gobiid fishes to quantitatively compare brain volumes obtained via three different methods; these included the commonly used techniques of histology and approximating brain volume to an idealised ellipsoid, and the recently established technique of X-ray micro-computed tomography (micro-CT). It was found that all three methods differed significantly from one another in their volume estimates for most brain lobes. The ellipsoid method was prone to over- or under-estimation of lobe size, histology caused shrinkage in the telencephalon, and although micro-CT methods generated the most reliable results, they were also the most expensive. Despite these differences, all methods depicted quantitatively similar relationships among the four different species for each brain lobe. Thus, all methods support the same conclusions that fishes inhabiting rock pool and sandy habitats have different patterns of brain organisation. In particular, fishes from spatially complex rock pool habitats were found to have larger telencephalons, while those from simple homogenous sandy shores had a larger optic tectum. Where possible we recommend that micro-CT be used in brain volume analyses, as it allows for measurements without destruction of the brain and fast identification and quantification of individual brain lobes, and minimises many of the biases resulting from the histology and ellipsoid methods.

Estimating individual contribution from group-based structural correlation networks

Coordinated variations in brain morphology (e.g., cortical thickness) across individuals have been widely used to infer large-scale population brain networks. These structural correlation networks (SCNs) have been shown to reflect synchronized maturational changes in connected brain regions. Further, evidence suggests that SCNs, to some extent, reflect both anatomical and functional connectivity and hence provide a complementary measure of brain connectivity in addition to diffusion weighted networks and resting-state functional networks. Although widely used to study between-group differences in network properties, SCNs are inferred only at the group-level using brain morphology data from a set of participants, thereby not providing any knowledge regarding how the observed differences in SCNs are associated with individual behavioral, cognitive and disorder states. In the present study, we introduce two novel distance-based approaches to extract information regarding individual differences from the group-level SCNs. We applied the proposed approaches to a moderately large dataset (n=100) consisting of individuals with fragile X syndrome (FXS; n=50) and age-matched typically developing individuals (TD; n=50). We tested the stability of proposed approaches using permutation analysis. Lastly, to test the efficacy of our method, individual contributions extracted from the group-level SCNs were examined for associations with intelligence scores and genetic data. The extracted individual contributions were stable and were significantly related to both genetic and intelligence estimates, in both typically developing individuals and participants with FXS. We anticipate that the approaches developed in this work could be used as a putative biomarker for altered connectivity in individuals with neurodevelopmental disorders.

Genetics and brain morphology.

A wealth of empirical evidence is accumulating on the genetic mediation of brain structure phenotypes. This comes from twin studies that assess heritability and genetic covariance between traits, candidate gene associations, and genome-wide association studies (GWAS) that can identify specific genetic variants. Here we review the major findings from each of these approaches and consider how they inform on the genetic architecture of brain structure. The findings from twin studies show there is a strong genetic influence (heritability) on brain structure, and overlap of genetic effects (pleiotropy) between structures, and between structure and cognition. However, there is also evidence for genetic specificity, with distinct genetic effects across some brain regions. Candidate gene associations show little convergence; most have been under powered to detect effect sizes of the magnitude now expected. GWAS have identified 19 genetic variants for brain structure, though no replicated associations account for more than 1% of the variance. Together these studies are revealing new insights into the genetic architecture of brain morphology. As the scope of inquiry broadens, including measures that capture the complexity of the brain, along with larger samples and new analyses, such as genome-wide common trait analysis (GCTA) and polygenic scores, which combine variant effects for a phenotype, as well as whole-genome sequencing, more genetic variants for brain structure will be identified. Increasingly, large-scale multi-site studies will facilitate this next wave of studies, and promise to enhance our understanding of the etiology of variation in brain morphology, as well as brain disorders.

Reversed brain size sexual dimorphism accompanies loss of parental care in white sticklebacks.

Uncovering factors that shape variation in brain morphology remains a major challenge in evolutionary biology. Recently, it has been shown that brain size is positively associated with level of parental care behavior in various taxa. One explanation for this pattern is that the cognitive demands of performing complex parental care may require increased brain size. This idea is known as the parental brain hypothesis (PBH). We set out to test the predictions of this hypothesis in wild populations of threespine stickleback (Gasterosteus aculeatus). These fish are commonly known to exhibit (1) uniparental male care and (2) sexual dimorphism in brain size (males>females). To test the PBH, we took advantage of the existence of closely related populations of stickleback that display variation in parental care behavior: common marine threespine sticklebacks (uniparental male care) and white threespine sticklebacks (no care). To begin, we quantified genetic differentiation among two common populations and three white populations from Nova Scotia. We found overall low differentiation among populations, although FST was increased in between-type comparisons. We then measured the brain weights of males and females from all five populations along with two additional common populations from British Columbia. We found that sexual dimorphism in brain size is reversed in white stickleback populations: males have smaller brains than females. Thus, while several alternatives need to be ruled out, the PBH appears to be a reasonable explanation for sexual dimorphism in brain size in threespine sticklebacks.

Beyond classical inheritance: the influence of maternal genotype upon child's brain morphology and behavior.

Genetic variance has been associated with variations in brain morphology, cognition, behavior, and disease risk. One well studied example of how common genetic variance is associated with brain morphology is the serotonin transporter gene polymorphism within the promoter region (5-HTTLPR). Because serotonin is a key neurotrophic factor during brain development, genetically determined variations in serotonin activity during maturation, in particular during early prenatal development, may underlie the observed association. However, the intrauterine microenvironment is not only determined by the child's, but also the mother's genotype. Therefore, we hypothesized that maternal 5-HTTLPR genotype influences the child's brain development beyond direct inheritance. To test this hypothesis, we investigated 76 children who were all heterozygous for the 5-HTTLPR (sl) and who had mothers who were either homozygous for the long (ll) or the short allele (ss). Using MRI, we assessed brain morphology as a function of maternal genotype. Gray matter density of the somatosensory cortex was found to be greater in children of ss mothers compared with children of ll mothers. Behavioral assessment showed that fine motor task performance was altered in children of ll mothers and the degree of this behavioral effect correlated with somatosensory cortex density across individuals. Our findings provide initial evidence that maternal genotype can affect the child's phenotype beyond effects of classical inheritance. Our observation appears to be explained by intrauterine environmental differences or by differences in maternal behavior.

Influence of Choice of Null Network on Small-World Parameters of Structural Correlation Networks

In recent years, coordinated variations in brain morphology (e.g., volume, thickness) have been employed as a measure of structural association between brain regions to infer large-scale structural correlation networks. Recent evidence suggests that brain networks constructed in this manner are inherently more clustered than random networks of the same size and degree. Thus, null networks constructed by randomizing topology are not a good choice for benchmarking small-world parameters of these networks. In the present report, we investigated the influence of choice of null networks on small-world parameters of gray matter correlation networks in healthy individuals and survivors of acute lymphoblastic leukemia. Three types of null networks were studied: 1) networks constructed by topology randomization (TOP), 2) networks matched to the distributional properties of the observed covariance matrix (HQS), and 3) networks generated from correlation of randomized input data (COR). The results revealed that the choice of null network not only influences the estimated small-world parameters, it also influences the results of between-group differences in small-world parameters. In addition, at higher network densities, the choice of null network influences the direction of group differences in network measures. Our data suggest that the choice of null network is quite crucial for interpretation of group differences in small-world parameters of structural correlation networks. We argue that none of the available null models is perfect for estimation of small-world parameters for correlation networks and the relative strengths and weaknesses of the selected model should be carefully considered with respect to obtained network measures.