Grey matter sublayer thickness estimation in the mouse cerebellum

The cerebellar grey matter morphology is an important feature to study neurodegenerative diseases such as Alzheimer’s disease or Down’s syndrome. Its volume or thickness is commonly used as a surrogate imaging biomarker for such diseases. Most studies about grey matter thickness estimation focused on the cortex, and little attention has been drawn on the morphology of the cerebellum. Using ex vivo highresolution MRI, it is now possible to visualise the different cell layers in the mouse cerebellum. In this work, we introduce a framework to extract the Purkinje layer within the grey matter, enabling the estimation of the thickness of the cerebellar grey matter, the granular layer and molecular layer from gadolinium-enhanced ex vivo mouse brain MRI. Application to mouse model of Down’s syndrome found reduced cortical and layer thicknesses in the transchromosomic group

Automated morphometry for mouse brain MRI through structural parcellation and thickness estimation

Quantitative morphometric analysis is an important tool in neuroimaging for the study of understanding the physiology of development, normal aging, disease pathology and treatment effect. However, compared to clinical study, image analysis methods specific to preclinical neuroimaging are still lacking. The aim of this PhD thesis is to achieve automatic quantitative structural analysis of mouse brain MRI. This thesis focuses on two quantitative methods which have been widely accepted as quantitative imaging biomarkers: brain structure segmentation and cortical thickness estimation. Firstly, a multi-atlas based structural parcellation framework has been constructed, which incorporates preprocessing steps such as intensity non-uniformity correction and multi-atlas based brain extraction, followed by non-rigid registration and local weighted multi-atlas label fusion. Validation of the framework demonstrated improved performance compared to single-atlas-based structural parcellation, as well as to global weighted multi-atlas label fusion methods. The framework has been further applied to in vivo and ex vivo data acquired from the same cohort so that the respective volumetric analysis can be compared. The results reveal a non-uniform distribution of volume changes from the in vivo to the post-mortem brain. In addition, volumetric analysis based on the segmented structures showed similar statistical power on in vivo or ex vivo data within the same cohort. Secondly, a framework to segment the mouse cerebellar cortex sublayers from brain MRI data and estimate the thickness of the corresponding layers has been developed. Application of the framework on the experimental data demonstrated its ability to distinguish sublayer thickness variation between transgenic strains and their wild-type littermate, which cannot be detected using full cortical thickness measurements alone. In conclusion, two quantitative morphometric analysis frameworks have been pre-sented in this thesis. This demonstrated the successful application of translational quantitative methods to preclinical mouse brain MRI

Substantially thinner internal granular layer and reduced molecular layer surface in the cerebellum of the Tc1 mouse model of Down Syndrome - a comprehensive morphometric analysis with active staining contrast-enhanced MRI

Down Syndrome is a chromosomal disorder that affects the development of cerebellar cortical lobules. Impaired neurogenesis in the cerebellum varies among different types of neuronal cells and neuronal layers. In this study, we developed an imaging analysis framework that utilizes gadolinium-enhanced ex vivo mouse brain MRI. We extracted the middle Purkinje layer of the mouse cerebellar cortex, enabling the estimation of the volume, thickness, and surface area of the entire cerebellar cortex, the internal granular layer, and the molecular layer in the Tc1 mouse model of Down Syndrome. The morphometric analysis of our method revealed that a larger proportion of the cerebellar thinning in this model of Down Syndrome resided in the inner granule cell layer, while a larger proportion of the surface area shrinkage was in the molecular layer

Visualizing the Distribution of Synapses from Individual Neurons in the Mouse Brain

BACKGROUND:Proper function of the mammalian brain relies on the establishment of highly specific synaptic connections among billions of neurons. To understand how complex neural circuits function, it is crucial to precisely describe neuronal connectivity and the distributions of synapses to and from individual neurons. METHODS AND FINDINGS:In this study, we present a new genetic synaptic labeling method that relies on expression of a presynaptic marker, synaptophysin-GFP (Syp-GFP) in individual neurons in vivo. We assess the reliability of this method and use it to analyze the spatial patterning of synapses in developing and mature cerebellar granule cells (GCs). In immature GCs, Syp-GFP is distributed in both axonal and dendritic regions. Upon maturation, it becomes strongly enriched in axons. In mature GCs, we analyzed synapses along their ascending segments and parallel fibers. We observe no differences in presynaptic distribution between GCs born at different developmental time points and thus having varied depths of projections in the molecular layer. We found that the mean densities of synapses along the parallel fiber and the ascending segment above the Purkinje cell (PC) layer are statistically indistinguishable, and higher than previous estimates. Interestingly, presynaptic terminals were also found in the ascending segments of GCs below and within the PC layer, with the mean densities two-fold lower than that above the PC layer. The difference in the density of synapses in these parts of the ascending segment likely reflects the regional differences in postsynaptic target cells of GCs. CONCLUSIONS:The ability to visualize synapses of single neurons in vivo is valuable for studying synaptogenesis and synaptic plasticity within individual neurons as well as information flow in neural circuits

Distinct Populations of Layer 5B Pyramidal Neurons in the Primary Motor Cortex

The ability of motor cortex to plan, execute, and refine different movements depends on the coordinated activity of many neurons found across its laminar structure. Layer 5b (L5b), a deep cortical layer that drives output signals from the cortex, contains excitatory pyramidal neurons that innervate many subcortical areas of the brain. In the motor cortex, L5b is thicker and contains more pyramidal neurons than L5b of other cortical areas. Electrophysiological, anatomical, and RNA-Seq profiling of neurons in the motor cortex suggests there are diverse pyramidal neuron types within L5b. However, the precise identities of these distinct populations and their defining traits have been difficult to assess. Determining the cell type-specific properties of distinct L5b pyramidal neurons will not only help in understanding how the motor cortex is able to execute its varied functions, but may also reveal how selective vulnerability is established in neurodegenerative diseases that affect the motor cortex, such as Amyotrophic Lateral Sclerosis (ALS). Despite being expressed in all cells of the body, mutations associated with ALS lead to specific loss of LMNs in the brainstem and the ventral horn of the spinal cord, and UMNs in L5b of the motor cortex. For this reason, it is important to characterize the unique molecular profiles that may underlie an increased vulnerability of these cell Ph.D. types to the ubiquitously expressed mutations. In the motor cortex, this requires us to determine the characteristics that differentiate vulnerable L5b cells from other resistant cell types in the same area, and understand how these features may contribute to their death in ALS. This study aims to understand how anatomical traits and molecular properties, defined at the level of gene expression, vary across subpopulations of L5b pyramidal neurons in the motor cortex. We show that there are two distinct, but closely related, pyramidal neuron subtypes in mouse primary motor cortex which occupy discrete sublayers of L5b. In the SOD1-G93A mouse model of ALS, we observe loss of only one of these cell types, establishing the other as an analogous resistant L5b population. Using TRAP (Translating Ribosome Affinity Purification) with RNA-Seq, we show that these cells have important baseline differences in gene expression in healthy tissues, and that they display differential molecular responses to SOD1-G93A expression. Together, these findings reveal that the gene expression differences between the distinct L5b populations not only reflect their diverse cortical and subcortical anatomy, but may also establish selective vulnerability in ALS

Automated morphometric analysis and phenotyping of mouse brains from structural µMR images

In light of the utility and increasing ubiquity of mouse models of genetic and neurological disease, I describefully automated pipelines for the investigation of structural microscopic magnetic resonance images of mouse brains – for both high-throughput phenotyping, and monitoring disease. Mouse models offer unparalleled insight into genetic function and brain plasticity, in phenotyping studies; and neurodegenerative disease onset and progression, in therapeutic trials. I developed two cohesive, automatic software tools, for Voxel- and Tensor-Based Morphometry (V/TBM) and the Boundary Shift Integral (BSI), in the mouse brain. V/TBM are advantageous for their ability to highlight morphological differences between groups, without laboriously delineating regions of interest. The BSI is a powerful and sensitive imaging biomarker for the detection of atrophy. The resulting pipelines are described in detail. I show the translation and application of open-source software developed for clinical MRI analysis to mouse brain data: for tissue segmentation into high-quality, subject-specific maps, using contemporary multi-atlas techniques; and for symmetric, inverse-consistent registration. I describe atlases and parameters suitable for the preclinical paradigm, and illustrate and discuss image processing challenges encountered and overcome during development. As proof of principle and to illustrate robustness, I used both pipelines with in and ex vivo mouse brain datasets to identify differences between groups, representing the morphological influence of genes, and subtle, longitudinal changes over time, in particular relation to Down syndrome and Alzheimer’s disease. I also discuss the merits of transitioning preclinical analysis from predominately ex vivo MRI to in vivo, where morphometry is still viable and fewer mice are necessary. This thesis conveys the cross-disciplinary translation of up-to-date image analysis techniques to the preclinical paradigm; the development of novel methods and adaptations to robustly process large cohorts of data; and the sensitive detection of phenotypic differences and neurodegenerative changes in the mouse brai

Drift and stabilization of cortical response selectivity

Synaptic turnover and long term functional stability are two seemingly contradicting features of neuronal networks, which show varying expressions across different brain regions. Recent studies have shown, how both of these are strongly expressed in the hippocampus, raising the question how this can be reconciled within a biological network. In this work, I use a data set of neuron activity from mice behaving within a virtual environment recorded over up to several months to extend and develop methods, showing how the activity of hundreds of neurons per individual animal can be reliably tracked and characterized. I employ these methods to analyze network- and individual neuron behavior during the initial formation of a place map from the activity of individual place cells while the animal learns to navigate in a new environment, as well as during the condition of a constant environment over several weeks. In a published study included in this work, we find that map formation is driven by selective stabilization of place cells coding for salient regions, with distinct characteristics for neurons coding for landmark, reward, or other locations. Strikingly, we find that in mice lacking Shank2, an autism spectrum disorder (ASD)-linked gene encoding an excitatory postsynaptic scaffold protein, a characteristic overrepresentation of visual landmarks is missing while the overrepresentation of reward location remains intact, suggesting different underlying mechanisms in the stabilization. In the condition of a constant environment, I find how turnover dynamics largely decouple from the location of a place field and are governed by a strong decorrelation of population activity on short time scales (hours to days), followed by long-lasting correlations (days to months) above chance level. In agreement with earlier studies, I find a slow, constant drift in the population of active neurons, while – contrary to earlier results – place fields within the active population are assumed approximately randomly. Place field movement across days is governed by periods of stability around an anchor position, interrupted by random, long-range relocation. The data does not suggest the existence of populations of neurons showing distinct properties of stability, but rather shows a continuous range from highly unstable to very stable functional- and non-functional activity. Average timescales of reliable contributions to the neural code are on the order of few days, in agreement with earlier reported timescales of synaptic turnover in the hippocampus.2021-08-0

Studies on the visual system of the rat

Minimal structural changes, not detected by qualitative assessment require quantitative methods for recognition. This work is concerned with the development of such a quantitative technique, and its application to minimal change situations, namely the visual cortices of rats with retinal dystrophy (Campbell strain) and of rats which had received a low grade retinotoxic insult.As well as the anatomy and normal development, the literature survey included those factors which can influence the normal development and function of the visual system, and hence the quantitative data. The quantitation review demonstrated the diversity of approach of the various authors working in this field, and revealed how little quantitative data exists on the rat cerebrum. No reports could be found on visual system quantitation of either of the situations investigated in this work.In the section on the problems of quantitation, the high technical demands and inherent errors are discussed, and the methods and correction factors to overcome these problems are detailed. Strict comparability of sections was attained by devising a method which ensured similar anatomical location in every case, despite great variation in brain size.A technique was devised to measure the variable shrinkage of processing, a problem ignored by many authors. By means of this Reduction Factor, the exact volume of tissue in a section is known and quantitative data can be calculated in a standard comparable form.From a total of 1,500 sections, after screening by ophthalmoscopy, post mortem examination, section thickness control and histological scrutiny, some 950 sections were selected for quantitation. The 950 sections, from 190 individuals provided the large sample, necessary because of individual variation.The quantitative results are presented in graphical and statistical forms, subdivided by age, sex and strain. These results show the method revealed differences between the dystrophic (Campbell) and control (P.V.G.) visual cortices. The Campbell cortex has a smaller mean cell size, which is produced by two factors, namely an increase in small cell density and a decrease in the density of the largest cells. Ultrastructural and special light microscopic investigation identified these cells as microglia and neurones respectively.These results, which have never previously been reported in the rat compare well with those produced in other species with visual deprivation and are consistent with the results of biochemical investigation of the Campbell visual cortex.The retinotoxic drugs, two diaminophenoxy compounds and iodoacetate which are retinotoxic in other species at the dose schedule used, failed to cause any changes in the P.V.G. rat by ophthalmoscopic, histological or quantitative investigation. It would seem the rat eye is relatively resistant to such drugs, and it is suggested that species other than the rat should be used to determine retinotoxicity

Placental morphology and the cellular brain in mammalian evolution

A major focus of evolutionary neurobiology has been on whether different regions of the eutherian brain evolve in concert, and how free the brain is to evolve independently of body plans. Since the eutherian brain is loosely modularized, such that one region is rarely isolated for specialization at the expense of others, but the design of modularization itself can be adapted by tweaking developmental programs, the degree to which brain regions must evolve in concert and can evolve independently may carry a deep phylogenetic signal. Using data collected from preserved brain tissue of 37 primate, 21 carnivore, and 15 other eutherian species (spanning 11 orders), I examined the phylogenetic level at which the proliferation of neurons and glia in the primary visual cortex and hippocampus proper, as well as granular layer volumes of the dentate gyrus and cerebellum, may be constrained by conserved developmental programs. In doing so, I was able to test for cellular signatures of (1) evolutionary changes in metabolic activity, (2) phylogenetic divergences, (3) specializations in behavior, and (4) developmental constraints. The degree to which disparate brain regions evolve in concert is shown to be generally conserved in Eutheria, although a derived ability to evolve regions independently is observed along the primate lineage. Using a separate dataset on placental and life-histroy character states, a comprehensive comparative phylogenetic approach was used to resolve relationships among five aspects of placental structure and to identify syndromes of placental morphology with life-history variables. My results support two discrete biological phenotypes of placental morphology and life-history, which are shown to have an evolutionary affect on allocortical, but not neocortical, brain organization. I have provided a new perspective on exploring how developmental constraints – acting both within and without the brain – may affect brain organization at the cellular level, and the extent to which those constraints have been adapted along certain eutherian lineages