Mapping registration sensitivity in MR mouse brain images

A Cross-Species Neuroimaging Study of Sex Chromosome Dosage Effects on Human and Mouse Brain Anatomy

All eutherian mammals show chromosomal sex determination with contrasting sex chromosome dosages (SCDs) between males (XY) and females (XX). Studies in transgenic mice and humans with sex chromosome trisomy (SCT) have revealed direct SCD effects on regional mammalian brain anatomy, but we lack a formal test for cross-species conservation of these effects. Here, we develop a harmonized framework for comparative structural neuroimaging and apply this to systematically profile SCD effects on regional brain anatomy in both humans and mice by contrasting groups with SCT (XXY and XYY) versus XY controls. Total brain size was substantially altered by SCT in humans (significantly decreased by XXY and increased by XYY), but not in mice. Robust and spatially convergent effects of XXY and XYY on regional brain volume were observed in humans, but not mice, when controlling for global volume differences. However, mice do show subtle effects of XXY and XYY on regional volume, although there is not a general spatial convergence in these effects within mice or between species. Notwithstanding this general lack of conservation in SCT effects, we detect several brain regions that show overlapping effects of XXY and XYY both within and between species (cerebellar, parietal, and orbitofrontal cortex), thereby nominating high priority targets for future translational dissection of SCD effects on the mammalian brain. Our study introduces a generalizable framework for comparative neuroimaging in humans and mice and applies this to achieve a cross-species comparison of SCD effects on the mammalian brain through the lens of SCT.SIGNIFICANCE STATEMENT Sex chromosome dosage (SCD) affects neuroanatomy and risk for psychopathology in humans. Performing mechanistic studies in the human brain is challenging but possible in mouse models. Here, we develop a framework for cross-species neuroimaging analysis and use this to show that an added X- or Y-chromosome significantly alters human brain anatomy but has muted effects in the mouse brain. However, we do find evidence for conserved cross-species impact of an added chromosome in the fronto-parietal cortices and cerebellum, which point to regions for future mechanistic dissection of sex chromosome dosage effects on brain development.

Early or Late Gestational Exposure to Maternal Immune Activation Alters Neurodevelopmental Trajectories in Mice: An Integrated Neuroimaging, Behavioral, and Transcriptional Study

BACKGROUND

Exposure to maternal immune activation (MIA) in utero is a risk factor for neurodevelopmental disorders later in life. The impact of the gestational timing of MIA exposure on downstream development remains unclear.

METHODS

We characterized neurodevelopmental trajectories of mice exposed to the viral mimetic poly I:C (polyinosinic:polycytidylic acid) either on gestational day 9 (early) or on day 17 (late) using longitudinal structural magnetic resonance imaging from weaning to adulthood. Using multivariate methods, we related neuroimaging and behavioral variables for the time of greatest alteration (adolescence/early adulthood) and identified regions for further investigation using RNA sequencing.

RESULTS

Early MIA exposure was associated with accelerated brain volume increases in adolescence/early adulthood that normalized in later adulthood in the striatum, hippocampus, and cingulate cortex. Similarly, alterations in anxiety-like, stereotypic, and sensorimotor gating behaviors observed in adolescence normalized in adulthood. MIA exposure in late gestation had less impact on anatomical and behavioral profiles. Multivariate maps associated anxiety-like, social, and sensorimotor gating deficits with volume of the dorsal and ventral hippocampus and anterior cingulate cortex, among others. The most transcriptional changes were observed in the dorsal hippocampus, with genes enriched for fibroblast growth factor regulation, autistic behaviors, inflammatory pathways, and microRNA regulation.

CONCLUSIONS

Leveraging an integrated hypothesis- and data-driven approach linking brain-behavior alterations to the transcriptome, we found that MIA timing differentially affects offspring development. Exposure in late gestation leads to subthreshold deficits, whereas exposure in early gestation perturbs brain development mechanisms implicated in neurodevelopmental disorders.

A Simulation Toolkit for Testing the Sensitivity and Accuracy of Corticometry Pipelines

In recent years, the replicability of neuroimaging findings has become an important concern to the research community. Neuroimaging pipelines consist of myriad numerical procedures, which can have a cumulative effect on the accuracy of findings. To address this problem, we propose a method for simulating artificial lesions in the brain in order to estimate the sensitivity and specificity of lesion detection, using different automated corticometry pipelines. We have applied this method to different versions of two widely used neuroimaging pipelines (CIVET and FreeSurfer), in terms of coefficients of variation; sensitivity and specificity of detecting lesions in 4 different regions of interest in the cortex, while introducing variations to the lesion size, the blurring kernel used prior to statistical analyses, and different thickness metrics (in CIVET). These variations are tested in a between-subject design (in two random groups, with and without lesions, using T1-weigted MRIs of 152 individuals from the International Consortium of Brain Mapping (ICBM) dataset) and in a within-subject pre-/post-lesion design [using 21 T1-Weighted MRIs of a single adult individual, scanned in the Infant Brain Imaging Study (IBIS)]. The simulation method is sensitive to partial volume effect and lesion size. Comparisons between pipelines illustrate the ability of this method to uncover differences in sensitivity and specificity of lesion detection. We propose that this method be adopted in the workflow of software development and release.

Small Animal Multivariate Brain Analysis (SAMBA) - a High Throughput Pipeline with a Validation Framework

While many neuroscience questions aim to understand the human brain, much current knowledge has been gained using animal models, which replicate genetic, structural, and connectivity aspects of the human brain. While voxel-based analysis (VBA) of preclinical magnetic resonance images is widely-used, a thorough examination of the statistical robustness, stability, and error rates is hindered by high computational demands of processing large arrays, and the many parameters involved therein. Thus, workflows are often based on intuition or experience, while preclinical validation studies remain scarce. To increase throughput and reproducibility of quantitative small animal brain studies, we have developed a publicly shared, high throughput VBA pipeline in a high-performance computing environment, called SAMBA. The increased computational efficiency allowed large multidimensional arrays to be processed in 1–3 days—a task that previously took ~1 month. To quantify the variability and reliability of preclinical VBA in rodent models, we propose a validation framework consisting of morphological phantoms, and four metrics. This addresses several sources that impact VBA results, including registration and template construction strategies. We have used this framework to inform the VBA workflow parameters in a VBA study for a mouse model of epilepsy. We also present initial efforts towards standardizing small animal neuroimaging data in a similar fashion with human neuroimaging. We conclude that verifying the accuracy of VBA merits attention, and should be the focus of a broader effort within the community. The proposed framework promotes consistent quality assurance of VBA in preclinical neuroimaging, thus facilitating the creation and communication of robust results.

Average volume reference space for large scale registration of whole-body magnetic resonance images

BACKGROUND AND OBJECTIVES

The construction of whole-body magnetic resonance (MR) imaging atlases allows to perform statistical analysis with applications in anomaly detection, longitudinal, and correlation studies. Atlas-based methods require a common coordinate system to which all the subjects are mapped through image registration. Optimisation of the reference space is an important aspect that affects the subsequent analysis of the registered data, and having a reference space that is neutral with respect to local tissue volume is valuable in correlation studies. The purpose of this work is to generate a reference space for whole-body imaging that has zero voxel-wise average volume change when mapped to a cohort.

METHODS

This work proposes an approach to register multiple whole-body images to a common template using volume changes to generate a synthetic reference space, starting with an initial reference and refining it by warping it with a deformation that brings the voxel-wise average volume change associated to the mappings of all the images in the cohort to zero.

RESULTS

Experiments on fat/water separated whole-body MR images show how the method effectively generates a reference space neutral with respect to volume changes, without reducing the quality of the registration nor introducing artefacts in the anatomy, while providing better alignment when compared to an implicit reference groupwise approach.

CONCLUSIONS

The proposed method allows to quickly generate a reference space neutral with respect to local volume changes, that retains the registration quality of a sharp template, and that can be used for statistical analysis of voxel-wise correlations in large datasets of whole-body image data.

Global brain volume reductions in a sub-chronic phencyclidine animal model for schizophrenia and their relationship to recognition memory

BACKGROUND

Cognitive deficits and structural brain changes co-occur in patients with schizophrenia. Improving our understanding of the relationship between these is important to develop improved therapeutic strategies. Back-translation of these findings into rodent models for schizophrenia offers a potential means to achieve this goal.

AIMS

The purpose of this study was to determine the extent of structural brain changes and how these relate to cognitive behaviour in a sub-chronic phencyclidine rat model.

METHODS

Performance in the novel object recognition task was examined in female Lister Hooded rats at one and six weeks after sub-chronic phencyclidine (2 mg/kg intra-peritoneal, n=15) and saline controls (1 ml/kg intra-peritoneal, n=15). Locomotor activity following acute phencyclidine challenge was also measured. Brain volume changes were assessed in the same animals using ex vivo structural magnetic resonance imaging and computational neuroanatomical analysis at six weeks.

RESULTS

Female sub-chronic phencyclidine-treated Lister Hooded rats spent significantly less time exploring novel objects (p<0.05) at both time-points and had significantly greater locomotor activity response to an acute phencyclidine challenge (p<0.01) at 3-4 weeks of washout. At six weeks, sub-chronic phencyclidine-treated Lister Hooded rats displayed significant global brain volume reductions (p<0.05; q<0.05), without apparent regional specificity. Relative volumes of the perirhinal cortex however were positively correlated with novel object exploration time only in sub-chronic phencyclidine rats at this time-point.

CONCLUSION

A sustained sub-chronic phencyclidine-induced cognitive deficit in novel object recognition is accompanied by global brain volume reductions in female Lister Hooded rats. The relative volumes of the perirhinal cortex however are positively correlated with novel object exploration, indicating some functional relevance.

Central nervous system targeted autoimmunity causes regional atrophy: a 9.4T MRI study of the EAE mouse model of Multiple Sclerosis

Atrophy has become a clinically relevant marker of progressive neurodegeneration in multiple sclerosis (MS). To better understand atrophy, mouse models that feature atrophy along with other aspects of MS are needed. The experimental autoimmune encephalomyelitis (EAE) mouse model of MS was used to determine the extent of atrophy in a model of inflammation-associated central nervous system pathology. High-resolution magnetic resonance imaging (MRI) and atlas-based volumetric analysis were performed to measure brain regional volumes in EAE mice. EAE brains were larger at peak clinical disease (days 14–16) compared to controls, with affected regions including the cerebellum, hippocampus, and corpus callosum. Following peak clinical disease, EAE mice exhibited significant loss of volume at chronic long-term disease duration (day 66+). Atrophy was identified in both white and grey matter regions including the cerebral cortex, cerebellum, hippocampus, corpus callosum, basal forebrain, midbrain, optic tract, and colliculus. Histological analysis of the atrophied cortex, cerebellum, and hippocampus showed demyelination, and axonal/neuronal loss. We hypothesize this atrophy could be a result of inflammatory associated neurodegenerative processes, which may also be involved in MS. Using MRI and atlas-based volumetrics, EAE has the potential to be a test bed for treatments aimed at reducing progressive neurological deterioration in MS.

The effect of automated landmark identification on morphometric analyses

Morphometric analysis of anatomical landmarks allows researchers to identify specific morphological differences between natural populations or experimental groups, but manually identifying landmarks is time-consuming. We compare manually and automatically generated adult mouse skull landmarks and subsequent morphometric analyses to elucidate how switching from manual to automated landmarking will impact morphometric analysis results for large mouse (Mus musculus) samples (n = 1205) that represent a wide range of 'normal' phenotypic variation (62 genotypes). Other studies have suggested that the use of automated landmarking methods is feasible, but this study is the first to compare the utility of current automated approaches to manual landmarking for a large dataset that allows the quantification of intra- and inter-strain variation. With this unique sample, we investigated how switching to a non-linear image registration-based automated landmarking method impacts estimated differences in genotype mean shape and shape variance-covariance structure. In addition, we tested whether an initial registration of specimen images to genotype-specific averages improves automatic landmark identification accuracy. Our results indicated that automated landmark placement was significantly different than manual landmark placement but that estimated skull shape covariation was correlated across methods. The addition of a preliminary genotype-specific registration step as part of a two-level procedure did not substantially improve on the accuracy of one-level automatic landmark placement. The landmarks with the lowest automatic landmark accuracy are found in locations with poor image registration alignment. The most serious outliers within morphometric analysis of automated landmarks displayed instances of stochastic image registration error that are likely representative of errors common when applying image registration methods to micro-computed tomography datasets that were initially collected with manual landmarking in mind. Additional efforts during specimen preparation and image acquisition can help reduce the number of registration errors and improve registration results. A reduction in skull shape variance estimates were noted for automated landmarking methods compared with manual landmarking. This partially reflects an underestimation of more extreme genotype shapes and loss of biological signal, but largely represents the fact that automated methods do not suffer from intra-observer landmarking error. For appropriate samples and research questions, our image registration-based automated landmarking method can eliminate the time required for manual landmarking and have a similar power to identify shape differences between inbred mouse genotypes.

Mapping the impact of exposure to maternal immune activation on juvenile Wistar rat brain macro- and microstructure during early post-natal development

Maternal immune activation is consistently associated with elevated risk for multiple psychiatric disorders in the affected offspring. Related to this, an important goal of our work is to explore the impact of maternal immune activation effects across the lifespan. In this context, we recently reported the effects of polyriboinosinic-polyribocytidylic acid-induced maternal immune activation at gestational day 15, immediately prior to birth, at gestational day 21 and again at post-natal day 21, providing a systematic assessment of plasma interleukin 6, body temperature and weight alterations in pregnant rats and preliminary evidence for gross morphological changes and microglial neuropathology in both male and female offsprings at these time points. Here, we sought to complement and extend these data by characterising in more detail the mesoscale impact of gestational polyriboinosinic-polyribocytidylic acid exposure at gestational day 15 on the neuroanatomy of the juvenile (post-natal day 21) rat brain using high-resolution, ex vivo anatomical magnetic resonance imaging in combination with atlas-based segmentation. Our preliminary data suggest subtle neuroanatomical effects of gestational polyriboinosinic-polyribocytidylic acid exposure (n = 10) relative to saline controls (n = 10) at this time-point. Specifically, we found an increase in the relative volume of the diagonal domain in polyriboinosinic-polyribocytidylic acid offspring (p < 0.01 uncorrected), which just failed to pass stringent multiple comparisons correction (actual q = 0.07). No statistically significant microstructural alterations were detectable using diffusion tensor imaging. Further studies are required to map the proximal effects of maternal immune activation on the developing rodent brain from foetal to early post-natal life and confirm our findings herein.

Within-subject test-retest reliability of the atlas-based cortical volume measurement in the rat brain: A voxel-based morphometry study

BACKGROUND

Various neurological and psychological disorders are related to cortical volume changes in specific brain regions, which can be measured in vivo using structural magnetic resonance imaging (sMRI). There is an increasing interest in MRI studies using rat models, especially in longitudinal studies of brain disorders and pharmacologic interventions. However, morphometric changes observed in sMRI are only meaningful if the measurements are reliable. To date, a systematic evaluation of the test-retest reliability of the morphometric measures in the rat brain is still lacking.

NEW METHOD

We rigorously evaluated the test-retest reliability of morphometric measures derived from the voxel-based morphometry (VBM) analysis. 37 Sprague-Dawley rats were scanned twice at an interval of six hours and the gray matter volume was estimated using the VBM-DARTEL method. The intraclass coefficient, percent volume change and Pearson correlation coefficient were used to evaluate the reliability in 96 subregions of the rat brain.

RESULTS

Most subregions showed excellent test-retest reliabilities within an interval of 6 h while a few regions demonstrated lower reliability, especially in the retrosplenial granular cortex. The results were consistent between different methods of reliability assessment.

COMPARISON WITH EXISTING METHOD

To the best of our knowledge, this is the first study to quantify the test-retest reliability of the VBM measurements of the rat brain.

CONCLUSION

Atlas-based cortical volume of the rat brain can be reliably estimated using the VBM-DARTEL method in most subregions. However, findings in subregions with lower reliability must be interpreted with caution.

Structural covariance of brain region volumes is associated with both structural connectivity and transcriptomic similarity

An organizational pattern seen in the brain, termed structural covariance, is the statistical association of pairs of brain regions in their anatomical properties. These associations, measured across a population as covariances or correlations usually in cortical thickness or volume, are thought to reflect genetic and environmental underpinnings. Here, we examine the biological basis of structural volume covariance in the mouse brain. We first examined large scale associations between brain region volumes using an atlas-based approach that parcellated the entire mouse brain into 318 regions over which correlations in volume were assessed, for volumes obtained from 153 mouse brain images via high-resolution MRI. We then used a seed-based approach and determined, for 108 different seed regions across the brain and using mouse gene expression and connectivity data from the Allen Institute for Brain Science, the variation in structural covariance data that could be explained by distance to seed, transcriptomic similarity to seed, and connectivity to seed. We found that overall, correlations in structure volumes hierarchically clustered into distinct anatomical systems, similar to findings from other studies and similar to other types of networks in the brain, including structural connectivity and transcriptomic similarity networks. Across seeds, this structural covariance was significantly explained by distance (17% of the variation, up to a maximum of 49% for structural covariance to the visceral area of the cortex), transcriptomic similarity (13% of the variation, up to maximum of 28% for structural covariance to the primary visual area) and connectivity (15% of the variation, up to a maximum of 36% for structural covariance to the intermediate reticular nucleus in the medulla) of covarying structures. Together, distance, connectivity, and transcriptomic similarity explained 37% of structural covariance, up to a maximum of 63% for structural covariance to the visceral area. Additionally, this pattern of explained variation differed spatially across the brain, with transcriptomic similarity playing a larger role in the cortex than subcortex, while connectivity explains structural covariance best in parts of the cortex, midbrain, and hindbrain. These results suggest that both gene expression and connectivity underlie structural volume covariance, albeit to different extents depending on brain region, and this relationship is modulated by distance.

Regional brain volume changes following chronic antipsychotic administration are mediated by the dopamine D2 receptor

BACKGROUND

Neuroanatomical alterations are well established in patients suffering from schizophrenia, however the extent to which these changes are attributable to illness, antipsychotic drugs (APDs), or their interaction is unclear. APDs have been extremely effective for treatment of positive symptoms in major psychotic disorders. Their therapeutic effects are mediated, in part, through blockade of D2-like dopamine (DA) receptors, i.e. the D2, D3 and D4 dopamine receptors. Furthermore, the dependency of neuroanatomical change on DA system function and D2-like receptors has yet to be explored.

METHODS

We undertook a preclinical longitudinal study to examine the effects of typical (haloperidol (HAL)) and atypical (clozapine (CLZ)) APDs in wild type (WT) and dopamine D2 knockout (D2KO) mice over 9-weeks using structural magnetic resonance imaging (MRI).

RESULTS

Chronic typical APD administration in WT mice was associated with reductions in total brain (p = 0.009) and prelimbic area (PL) (p = 0.02) volumes following 9-weeks, and an increase in striatal volume (p = 0.04) after six weeks. These APD-induced changes were not present in D2KOs, where, at baseline, we observed significantly smaller overall brain volume (p < 0.01), thinner cortices (q < 0.05), and enlarged striata (q < 0.05). Stereological assessment revealed increased glial density in PL area of HAL treated wild types. Interestingly, in WT and D2KO mice, chronic CLZ administration caused more limited changes in brain structure.

CONCLUSIONS

Our results present evidence for the role of D2 DA receptors in structural alterations induced by the administration of the typical APD HAL and that chronic administration of CLZ has a limited influence on brain structure.

Impact of X/Y genes and sex hormones on mouse neuroanatomy

Biological sex influences brain anatomy across many species. Sex differences in brain anatomy have classically been attributed to differences in sex chromosome complement (XX versus XY) and/or in levels of gonadal sex steroids released from ovaries and testes. Using the four core genotype (4CG) mouse model in which gonadal sex and sex chromosome complement are decoupled, we previously found that sex hormones and chromosomes influence the volume of distinct brain regions. However, recent studies suggest there may be more complex interactions between hormones and chromosomes, and that circulating steroids can compensate for and/or mask underlying chromosomal effects. Moreover, the impact of pre vs post-pubertal sex hormone exposure on this sex hormone/sex chromosome interplay is not well understood. Thus, we used whole brain high-resolution ex-vivo MRI of intact and pre-pubertally gonadectomized 4CG mice to investigate two questions: 1) Do circulating steroids mask sex differences in brain anatomy driven by sex chromosome complement? And 2) What is the contribution of pre- versus post-pubertal hormones to sex-hormone-dependent differences in brain anatomy? We found evidence of both cooperative and compensatory interactions between sex chromosomes and sex hormones in several brain regions, but the interaction effects were of low magnitude. Additionally, most brain regions affected by sex hormones were sensitive to both pre- and post-pubertal hormones. This data provides further insight into the biological origins of sex differences in brain anatomy.

Spatial gene expression analysis of neuroanatomical differences in mouse models

MRI is a powerful modality to detect neuroanatomical differences that result from mutations and treatments. Knowing which genes drive these differences is important in understanding etiology, but candidate genes are often difficult to identify. We tested whether spatial gene expression data from the Allen Brain Institute can be used to inform us about genes that cause neuroanatomical differences. For many single-gene-mutation mouse models, we found that affected neuroanatomy was not strongly associated with the spatial expression of the altered gene and there are specific caveats for each model. However, among models with significant neuroanatomical differences from their wildtype controls, the mutated genes had preferential spatial expression in affected neuroanatomy. In mice exposed to environmental enrichment, candidate genes could be identified by a genome-wide search for genes with preferential spatial expression in the altered neuroanatomical regions. These candidates have functions related to learning and plasticity. We demonstrate that spatial gene expression of single-genes is a poor predictor of altered neuroanatomy, but altered neuroanatomy can identify candidate genes responsible for neuroanatomical phenotypes.

Evolution of structural abnormalities in the rat brain following in utero exposure to maternal immune activation: A longitudinal in vivo MRI study

Genetic and environmental risk factors for psychiatric disorders are suggested to disrupt the trajectory of brain maturation during adolescence, leading to the development of psychopathology in adulthood. Rodent models are powerful tools to dissect the specific effects of such risk factors on brain maturational profiles, particularly when combined with Magnetic Resonance Imaging (MRI; clinically comparable technology). We therefore investigated the effect of maternal immune activation (MIA), an epidemiological risk factor for adult-onset psychiatric disorders, on rat brain maturation using atlas and tensor-based morphometry analysis of longitudinal in vivo MR images. Exposure to MIA resulted in decreases in the volume of several cortical regions, the hippocampus, amygdala, striatum, nucleus accumbens and unexpectedly, the lateral ventricles, relative to controls. In contrast, the volumes of the thalamus, ventral mesencephalon, brain stem and major white matter tracts were larger, relative to controls. These volumetric changes were maximal between post-natal day 50 and 100 with no differences between the groups thereafter. These data are consistent with and extend prior studies of brain structure in MIA-exposed rodents. Apart from the ventricular findings, these data have robust face validity to clinical imaging findings reported in studies of individuals at high clinical risk for a psychiatric disorder. Further work is now required to address the relationship of these MRI changes to behavioral dysfunction and to establish thier cellular correlates.

Quantitative magnetic resonance imaging of brain atrophy in a mouse model of Niemann-Pick type C disease

In vivo magnetic resonance imaging (MRI) was used to investigate regional and global brain atrophy in the neurodegenerative Niemann Pick Type C1 (NPC1) disease mouse model. Imaging experiments were conducted with the most commonly studied mouse model of NPC1 disease at early and late disease states. High-resolution in vivo images were acquired at early and late stages of the disease and analyzed with atlas-based registration to obtain measurements of twenty brain region volumes. A two-way ANOVA analysis indicated eighteen of these regions were different due to genotype and thirteen showed a significant interaction with age and genotype. The ability to measure in vivo neurodegeneration evidenced by brain atrophy adds to the ability to monitor disease progression and treatment response in the mouse model.

Altered cerebral blood flow and cerebrovascular function after voluntary exercise in adult mice

The beneficial effects of physical exercise on brain health are well documented, yet how exercise modulates cerebrovascular function is not well understood. This study used continuous arterial spin labeling magnetic resonance imaging with a hypercapnic challenge to examine changes in cerebral blood flow and vascular function after voluntary exercise in healthy, adult mice. Thirty exercise mice and twenty-one control mice were imaged prior to the start of the exercise regime (at 12 weeks of age) and after 4 weeks of voluntary exercise. After the second in vivo imaging session, we performed high-resolution ex vivo anatomical brain imaging to correlate the structural brain changes with functional measures of flow and vascular reserve. We found that exercise resulted in increases in the normocapnic and hypercapnic blood flow in the hippocampus. Moreover, the change in normocapnic blood flow between pre-exercise and post-exercise was positively correlated to the hippocampal structure volume following exercise. There was no overall effect of voluntary exercise on blood flow in the motor cortex. Surprisingly, the hypercapnic hippocampal blood flow when measured prior to the start of exercise was predictive of subsequent exercise activity. Moreover, exercise was found to normalize this pre-existing difference in hypercapnic blood flow between mice.

Whole-brain ex-vivo quantitative MRI of the cuprizone mouse model

Myelin is a critical component of the nervous system and a major contributor to contrast in Magnetic Resonance (MR) images. However, the precise contribution of myelination to multiple MR modalities is still under debate. The cuprizone mouse is a well-established model of demyelination that has been used in several MR studies, but these have often imaged only a single slice and analysed a small region of interest in the corpus callosum. We imaged and analyzed the whole brain of the cuprizone mouse ex-vivo using high-resolution quantitative MR methods (multi-component relaxometry, Diffusion Tensor Imaging (DTI) and morphometry) and found changes in multiple regions, including the corpus callosum, cerebellum, thalamus and hippocampus. The presence of inflammation, confirmed with histology, presents difficulties in isolating the sensitivity and specificity of these MR methods to demyelination using this model.

Hippocampal to basal forebrain transport of Mn2+ is impaired by deletion of KLC1, a subunit of the conventional kinesin microtubule-based motor

Microtubule-based motors carry cargo back and forth between the synaptic region and the cell body. Defects in axonal transport result in peripheral neuropathies, some of which are caused by mutations in KIF5A, a gene encoding one of the heavy chain isoforms of conventional kinesin-1. Some mutations in KIF5A also cause severe central nervous system defects in humans. While transport dynamics in the peripheral nervous system have been well characterized experimentally, transport in the central nervous system is less experimentally accessible and until now not well described. Here we apply manganese-enhanced magnetic resonance (MEMRI) to study transport dynamics within the central nervous system, focusing on the hippocampal-forebrain circuit, and comparing kinesin-1 light chain 1 knock-out (KLC-KO) mice with age-matched wild-type littermates. We injected Mn²⁺ into CA3 of the posterior hippocampus and imaged axonal transport in vivo by capturing whole-brain 3D magnetic resonance images (MRI) in living mice at discrete time-points after injection. Precise placement of the injection site was monitored in both MR images and in histologic sections. Mn²⁺-induced intensity progressed along fiber tracts (fimbria and fornix) in both genotypes to the medial septal nuclei (MSN), correlating in location with the traditional histologic tract tracer, rhodamine dextran. Pairwise statistical parametric mapping (SPM) comparing intensities at successive time-points within genotype revealed Mn²⁺-enhanced MR signal as it proceeded from the injection site into the forebrain, the expected projection from CA3. By region of interest (ROI) analysis of the MSN, wide variation between individuals in each genotype was found. Despite this statistically significant intensity increases in the MSN at 6h post-injection was found in both genotypes, albeit less so in the KLC-KO. While the average accumulation at 6h was less in the KLC-KO, the difference between genotypes did not reach significance. Projections of SPM T-maps for each genotype onto the same grayscale image revealed differences in the anatomical location of significant voxels. Although KLC-KO mice had smaller brains than wild-type, the gross anatomy was normal with no apparent loss of septal cholinergic neurons. Hence anatomy alone does not explain the differences in SPM maps. We conclude that kinesin-1 defects may have only a minor effect on the rate and distribution of transported Mn²⁺ within the living brain. This impairment is less than expected for this abundant microtubule-based motor, yet such defects could still be functionally significant, resulting in cognitive/emotional dysfunction due to decreased replenishments of synaptic vesicles or mitochondria during synaptic activity. This study demonstrates the power of MEMRI to observe and measure vesicular transport dynamics in the central nervous system that may result from or lead to brain pathology.

Simultaneous effects on parvalbumin-positive interneuron and dopaminergic system development in a transgenic rat model for sporadic schizophrenia

To date, unequivocal neuroanatomical features have been demonstrated neither for sporadic nor for familial schizophrenia. Here, we investigated the neuroanatomical changes in a transgenic rat model for a subset of sporadic chronic mental illness (CMI), which modestly overexpresses human full-length, non-mutant Disrupted-in-Schizophrenia 1 (DISC1), and for which aberrant dopamine homeostasis consistent with some schizophrenia phenotypes has previously been reported. Neuroanatomical analysis revealed a reduced density of dopaminergic neurons in the substantia nigra and reduced dopaminergic fibres in the striatum. Parvalbumin-positive interneuron occurrence in the somatosensory cortex was shifted from layers II/III to V/VI, and the number of calbindin-positive interneurons was slightly decreased. Reduced corpus callosum thickness confirmed trend-level observations from in vivo MRI and voxel-wise tensor based morphometry. These neuroanatomical changes help explain functional phenotypes of this animal model, some of which resemble changes observed in human schizophrenia post mortem brain tissues. Our findings also demonstrate how a single molecular factor, DISC1 overexpression or misassembly, can account for a variety of seemingly unrelated morphological phenotypes and thus provides a possible unifying explanation for similar findings observed in sporadic schizophrenia patients. Our anatomical investigation of a defined model for sporadic mental illness enables a clearer definition of neuroanatomical changes associated with subsets of human sporadic schizophrenia.

Fully-Automated μMRI Morphometric Phenotyping of the Tc1 Mouse Model of Down Syndrome

We describe a fully automated pipeline for the morphometric phenotyping of mouse brains from μMRI data, and show its application to the Tc1 mouse model of Down syndrome, to identify new morphological phenotypes in the brain of this first transchromosomic animal carrying human chromosome 21. We incorporate an accessible approach for simultaneously scanning multiple ex vivo brains, requiring only a 3D-printed brain holder, and novel image processing steps for their separation and orientation. We employ clinically established multi-atlas techniques–superior to single-atlas methods–together with publicly-available atlas databases for automatic skull-stripping and tissue segmentation, providing high-quality, subject-specific tissue maps. We follow these steps with group-wise registration, structural parcellation and both Voxel- and Tensor-Based Morphometry–advantageous for their ability to highlight morphological differences without the laborious delineation of regions of interest. We show the application of freely available open-source software developed for clinical MRI analysis to mouse brain data: NiftySeg for segmentation and NiftyReg for registration, and discuss atlases and parameters suitable for the preclinical paradigm. We used this pipeline to compare 29 Tc1 brains with 26 wild-type littermate controls, imaged ex vivo at 9.4T. We show an unexpected increase in Tc1 total intracranial volume and, controlling for this, local volume and grey matter density reductions in the Tc1 brain compared to the wild-types, most prominently in the cerebellum, in agreement with human DS and previous histological findings.

Deep brain stimulation of the ventromedial prefrontal cortex causes reorganization of neuronal processes and vasculature

BACKGROUND

Chronic high-frequency electrical deep brain stimulation (DBS) of the subcallosal cingulate region is currently being investigated clinically as a therapy for treatment of refractory depression. Experimental DBS of the homologous region, the ventromedial prefrontal cortex (VMPFC), in rodent models has previously demonstrated anti-depressant-like effects. Our goal was to determine if structural remodeling accompanies the alterations of brain function previously observed as a result of chronic DBS.

METHODS

Here we applied 6h of high-frequency bilateral VMPFC DBS daily to 8 9-week old C57Bl/6 mice for 5days. We investigated the "micro-lesion" effect by using a sham stimulation group (8 mice) and a control group (8 mice with a hole drilled into the skull only). Whole brain anatomy was investigated post-mortem using high-resolution magnetic resonance imaging and areas demonstrating volumetric expansion were further investigated using histology and immunohistochemistry.

RESULTS

The DBS group demonstrated bilateral increases in whole hippocampus and the left thalamus volume compared to both sham and control groups. Local hippocampal and thalamic volume increases were also observed at the voxel-level; however these increases were observed in both DBS and sham groups. Follow-up immunohistochemistry in the hippocampus revealed DBS increased blood vessel size and synaptic density relative to the control group whereas the sham group demonstrated increased astrocyte size.

CONCLUSIONS

Our work demonstrates that DBS not only works by altering function with neural circuits, but also by structurally altering circuits at the cellular level. Neuroplastic alterations may play a role in mediating the clinical efficacy of DBS therapy.

A simple rapid process for semi-automated brain extraction from magnetic resonance images of the whole mouse head

BACKGROUND

Magnetic resonance imaging (MRI) is a well-developed technique in neuroscience. Limitations in applying MRI to rodent models of neuropsychiatric disorders include the large number of animals required to achieve statistical significance, and the paucity of automation tools for the critical early step in processing, brain extraction, which prepares brain images for alignment and voxel-wise statistics.

NEW METHOD

This novel timesaving automation of template-based brain extraction ("skull-stripping") is capable of quickly and reliably extracting the brain from large numbers of whole head images in a single step. The method is simple to install and requires minimal user interaction.

RESULTS

This method is equally applicable to different types of MR images. Results were evaluated with Dice and Jacquard similarity indices and compared in 3D surface projections with other stripping approaches. Statistical comparisons demonstrate that individual variation of brain volumes are preserved.

COMPARISON WITH EXISTING METHODS

A downloadable software package not otherwise available for extraction of brains from whole head images is included here. This software tool increases speed, can be used with an atlas or a template from within the dataset, and produces masks that need little further refinement.

CONCLUSIONS

Our new automation can be applied to any MR dataset, since the starting point is a template mask generated specifically for that dataset. The method reliably and rapidly extracts brain images from whole head images, rendering them useable for subsequent analytical processing. This software tool will accelerate the exploitation of mouse models for the investigation of human brain disorders by MRI.

4D MEMRI atlas of neonatal FVB/N mouse brain development

The widespread use of the mouse as a model system to study brain development has created the need for noninvasive neuroimaging methods that can be applied to early postnatal mice. The goal of this study was to optimize in vivo three- (3D) and four-dimensional (4D) manganese (Mn)-enhanced MRI (MEMRI) approaches for acquiring and analyzing data from the developing mouse brain. The combination of custom, stage-dependent holders and self-gated (motion-correcting) 3D MRI sequences enabled the acquisition of high-resolution (100-μm isotropic), motion artifact-free brain images with a high level of contrast due to Mn-enhancement of numerous brain regions and nuclei. We acquired high-quality longitudinal brain images from two groups of FVB/N strain mice, six mice per group, each mouse imaged on alternate odd or even days (6 3D MEMRI images at each day) covering the developmental stages between postnatal days 1 to 11. The effects of Mn-exposure, anesthesia and MRI were assessed, showing small but significant transient effects on body weight and brain volume, which recovered with time and did not result in significant morphological differences when compared to controls. Metrics derived from deformation-based morphometry (DBM) were used for quantitative analysis of changes in volume and position of a number of brain regions. The cerebellum, a brain region undergoing significant changes in size and patterning at early postnatal stages, was analyzed in detail to demonstrate the spatiotemporal characterization made possible by this new atlas of mouse brain development. These results show that MEMRI is a powerful tool for quantitative analysis of mouse brain development, with great potential for in vivo phenotype analysis in mouse models of neurodevelopmental diseases.

Clustering autism: using neuroanatomical differences in 26 mouse models to gain insight into the heterogeneity

Autism is a heritable disorder, with over 250 associated genes identified to date, yet no single gene accounts for >1-2% of cases. The clinical presentation, behavioural symptoms, imaging and histopathology findings are strikingly heterogeneous. A more complete understanding of autism can be obtained by examining multiple genetic or behavioural mouse models of autism using magnetic resonance imaging (MRI)-based neuroanatomical phenotyping. Twenty-six different mouse models were examined and the consistently found abnormal brain regions across models were parieto-temporal lobe, cerebellar cortex, frontal lobe, hypothalamus and striatum. These models separated into three distinct clusters, two of which can be linked to the under and over-connectivity found in autism. These clusters also identified previously unknown connections between Nrxn1α, En2 and Fmr1; Nlgn3, BTBR and Slc6A4; and also between X monosomy and Mecp2. With no single treatment for autism found, clustering autism using neuroanatomy and identifying these strong connections may prove to be a crucial step in predicting treatment response.

Separate effects of sex hormones and sex chromosomes on brain structure and function revealed by high-resolution magnetic resonance imaging and spatial navigation assessment of the Four Core Genotype mouse model

Males and females exhibit several differences in brain structure and function. To examine the basis for these sex differences, we investigated the influences of sex hormones and sex chromosomes on brain structure and function in mice. We used the Four Core Genotype (4CG) mice, which can generate both male and female mice with XX or XY sex chromosome complement, allowing the decoupling of sex chromosomes from hormonal milieu. To examine whole brain structure, high-resolution ex vivo MRI was performed, and to assess differences in cognitive function, mice were trained on a radial arm maze. Voxel-wise and volumetric analyses of MRI data uncovered a striking independence of hormonal versus chromosomal influences in 30 sexually dimorphic brain regions. For example, the bed nucleus of the stria terminalis and the parieto-temporal lobe of the cerebral cortex displayed steroid-dependence while the cerebellar cortex, corpus callosum, and olfactory bulbs were influenced by sex chromosomes. Spatial learning and memory demonstrated strict hormone-dependency with no apparent influence of sex chromosomes. Understanding the influences of chromosomes and hormones on brain structure and function is important for understanding sex differences in brain structure and function, an endeavor that has eventual implications for understanding sex biases observed in the prevalence of psychiatric disorders.

Pydpiper: a flexible toolkit for constructing novel registration pipelines

Using neuroimaging technologies to elucidate the relationship between genotype and phenotype and brain and behavior will be a key contribution to biomedical research in the twenty-first century. Among the many methods for analyzing neuroimaging data, image registration deserves particular attention due to its wide range of applications. Finding strategies to register together many images and analyze the differences between them can be a challenge, particularly given that different experimental designs require different registration strategies. Moreover, writing software that can handle different types of image registration pipelines in a flexible, reusable and extensible way can be challenging. In response to this challenge, we have created Pydpiper, a neuroimaging registration toolkit written in Python. Pydpiper is an open-source, freely available software package that provides multiple modules for various image registration applications. Pydpiper offers five key innovations. Specifically: (1) a robust file handling class that allows access to outputs from all stages of registration at any point in the pipeline; (2) the ability of the framework to eliminate duplicate stages; (3) reusable, easy to subclass modules; (4) a development toolkit written for non-developers; (5) four complete applications that run complex image registration pipelines “out-of-the-box.” In this paper, we will discuss both the general Pydpiper framework and the various ways in which component modules can be pieced together to easily create new registration pipelines. This will include a discussion of the core principles motivating code development and a comparison of Pydpiper with other available toolkits. We also provide a comprehensive, line-by-line example to orient users with limited programming knowledge and highlight some of the most useful features of Pydpiper. In addition, we will present the four current applications of the code.

Automated pipeline for anatomical phenotyping of mouse embryos using micro-CT

The International Mouse Phenotyping Consortium (IMPC) plans to phenotype 20,000 single-gene knockout mice to gain an insight into gene function. Approximately 30% of these knockout mouse lines will be embryonic or perinatal lethal. The IMPC has selected three-dimensional (3D) imaging to phenotype these mouse lines at relevant stages of embryonic development in an attempt to discover the cause of lethality using detailed anatomical information. Rate of throughput is paramount as IMPC production centers have been given the ambitious task of completing this phenotyping project by 2021. Sifting through the wealth of data within high-resolution 3D mouse embryo data sets by trained human experts is infeasible at this scale. Here, we present a phenotyping pipeline that identifies statistically significant anatomical differences in the knockout, in comparison with the wild type, through a computer-automated image registration algorithm. This phenotyping pipeline consists of three analyses (intensity, deformation, and atlas based) that can detect missing anatomical structures and differences in volume of whole organs as well as on the voxel level. This phenotyping pipeline was applied to micro-CT images of two perinatal lethal mouse lines: a hypomorphic mutation of the Tcf21 gene (Tcf21-hypo) and a knockout of the Satb2 gene. With the proposed pipeline we were able to identify the majority of morphological phenotypes previously published for both the Tcf21-hypo and Satb2 mutant mouse embryos in addition to novel phenotypes. This phenotyping pipeline is an unbiased, automated method that highlights only those structural abnormalities that survive statistical scrutiny and illustrates them in a straightforward fashion.

Automatic structural parcellation of mouse brain MRI using multi-atlas label fusion

Multi-atlas segmentation propagation has evolved quickly in recent years, becoming a state-of-the-art methodology for automatic parcellation of structural images. However, few studies have applied these methods to preclinical research. In this study, we present a fully automatic framework for mouse brain MRI structural parcellation using multi-atlas segmentation propagation. The framework adopts the similarity and truth estimation for propagated segmentations (STEPS) algorithm, which utilises a locally normalised cross correlation similarity metric for atlas selection and an extended simultaneous truth and performance level estimation (STAPLE) framework for multi-label fusion. The segmentation accuracy of the multi-atlas framework was evaluated using publicly available mouse brain atlas databases with pre-segmented manually labelled anatomical structures as the gold standard, and optimised parameters were obtained for the STEPS algorithm in the label fusion to achieve the best segmentation accuracy. We showed that our multi-atlas framework resulted in significantly higher segmentation accuracy compared to single-atlas based segmentation, as well as to the original STAPLE framework.