On the Usage of Brain Atlases in Neuroimaging Research

Developmental mouse brain common coordinate framework

3D brain atlases are key resources to understand the brain's spatial organization and promote interoperability across different studies. However, unlike the adult mouse brain, the lack of developing mouse brain 3D reference atlases hinders advancements in understanding brain development. Here, we present a 3D developmental common coordinate framework (DevCCF) spanning embryonic day (E)11.5, E13.5, E15.5, E18.5, and postnatal day (P)4, P14, and P56, featuring undistorted morphologically averaged atlas templates created from magnetic resonance imaging and co-registered high-resolution light sheet fluorescence microscopy templates. The DevCCF with 3D anatomical segmentations can be downloaded or explored via an interactive 3D web-visualizer. As a use case, we utilize the DevCCF to unveil GABAergic neuron emergence in embryonic brains. Moreover, we map the Allen CCFv3 and spatial transcriptome cell-type data to our stereotaxic P56 atlas. In summary, the DevCCF is an openly accessible resource for multi-study data integration to advance our understanding of brain development.

An interactive image segmentation method for the anatomical structures of the main olfactory bulb with micro-level resolution

The main olfactory bulb is the key element of the olfactory pathway of rodents. To precisely dissect the neural pathway in the main olfactory bulb (MOB), it is necessary to construct the three-dimensional morphologies of the anatomical structures within it with micro-level resolution. However, the construction remains challenging due to the complicated shape of the anatomical structures in the main olfactory bulb and the high resolution of micro-optical images. To address these issues, we propose an interactive volume image segmentation method with micro-level resolution in the horizontal and axial direction. Firstly, we obtain the initial location of the anatomical structures by manual annotation and design a patch-based neural network to learn the complex texture feature of the anatomical structures. Then we randomly sample some patches to predict by the trained network and perform an annotation reconstruction based on intensity calculation to get the final location results of the anatomical structures. Our experiments were conducted using Nissl-stained brain images acquired by the Micro-optical sectioning tomography (MOST) system. Our method achieved a mean dice similarity coefficient (DSC) of 81.8% and obtain the best segmentation performance. At the same time, the experiment shows the three-dimensional morphology reconstruction results of the anatomical structures in the main olfactory bulb are smooth and consistent with their natural shapes, which addresses the possibility of constructing three-dimensional morphologies of the anatomical structures in the whole brain.

Developmental Mouse Brain Common Coordinate Framework

3D standard reference brains serve as key resources to understand the spatial organization of the brain and promote interoperability across different studies. However, unlike the adult mouse brain, the lack of standard 3D reference atlases for developing mouse brains has hindered advancement of our understanding of brain development. Here, we present a multimodal 3D developmental common coordinate framework (DevCCF) spanning mouse embryonic day (E) 11.5, E13.5, E15.5, E18.5, and postnatal day (P) 4, P14, and P56 with anatomical segmentations defined by a developmental ontology. At each age, the DevCCF features undistorted morphologically averaged atlas templates created from Magnetic Resonance Imaging and co-registered high-resolution templates from light sheet fluorescence microscopy. Expert-curated 3D anatomical segmentations at each age adhere to an updated prosomeric model and can be explored via an interactive 3D web-visualizer. As a use case, we employed the DevCCF to unveil the emergence of GABAergic neurons in embryonic brains. Moreover, we integrated the Allen CCFv3 into the P56 template with stereotaxic coordinates and mapped spatial transcriptome cell-type data with the developmental ontology. In summary, the DevCCF is an openly accessible resource that can be used for large-scale data integration to gain a comprehensive understanding of brain development.

Post-mortem Magnetic Resonance Imaging of Degenerating and Reorganizing White Matter in Post-stroke Rodent Brain

Magnetic resonance imaging (MRI) allows noninvasive and non-destructive imaging of brain tissue. More specifically, the status of white matter fibers can be measured with diffusion-weighted MRI, enabling assessment of structural degeneration or remodeling of white matter tracts in diseased brain. Here, we describe the preparation of post-stroke rodent brain samples for post-mortem high-resolution 3D diffusion-weighted MR imaging, accompanied with guidelines for acquiring and processing the images.

Histological and MRI brain atlas of the common shrew, Sorex araneus, with brain region-specific gene expression profiles

The common shrew, Sorex araneus, is a small mammal of growing interest in neuroscience research, as it exhibits dramatic and reversible seasonal changes in individual brain size and organization (a process known as Dehnel's phenomenon). Despite decades of studies on this system, the mechanisms behind the structural changes during Dehnel's phenomenon are not yet understood. To resolve these questions and foster research on this unique species, we present the first combined histological, magnetic resonance imaging (MRI), and transcriptomic atlas of the common shrew brain. Our integrated morphometric brain atlas provides easily obtainable and comparable anatomic structures, while transcriptomic mapping identified distinct expression profiles across most brain regions. These results suggest that high-resolution morphological and genetic research is pivotal for elucidating the mechanisms underlying Dehnel's phenomenon while providing a communal resource for continued research on a model of natural mammalian regeneration. Morphometric and NCBI Sequencing Read Archive are available at https://doi.org/10.17617/3.HVW8ZN.

APOE ε4 genotype, amyloid-β, and sex interact to predict tau in regions of high APOE mRNA expression

The apolipoprotein E (APOE) ε4 allele is strongly linked with cerebral β-amyloidosis, but its relationship with tauopathy is less established. We investigated the relationship between APOE ε4 carrier status, regional amyloid-β (Aβ), magnetic resonance imaging (MRI) volumetrics, tau positron emission tomography (PET), APOE messenger RNA (mRNA) expression maps, and cerebrospinal fluid phosphorylated tau (CSF ptau₁₈₁). Three hundred fifty participants underwent imaging, and 270 had ptau₁₈₁. We used computational models to evaluate the main effect of APOE ε4 carrier status on regional neuroimaging values and then the interaction of ε4 status and global Aβ on regional tau PET and brain volumes as well as CSF ptau₁₈₁. Separately, we also examined the additional interactive influence of sex. We found that, for the same degree of Aβ burden, APOE ε4 carriers showed greater tau PET signal relative to noncarriers in temporal regions, but no interaction was present for MRI volumes or CSF ptau₁₈₁. This potentiation of tau aggregation irrespective of sex occurred in brain regions with high APOE mRNA expression, suggesting local vulnerabilities to tauopathy. There were greater effects of APOE genotype in females, although the interactive sex effects did not strongly mirror mRNA expression. Pathology is not homogeneously expressed throughout the brain but mirrors underlying biological patterns such as gene expression.

Network analysis of neuroimaging in mice

Graph theory allows assessing changes of neuronal connectivity and interactions of brain regions in response to local lesions, e.g., after stroke, and global perturbations, e.g., due to psychiatric dysfunctions or neurodegenerative disorders. Consequently, network analysis based on constructing graphs from structural and functional MRI connectivity matrices is increasingly used in clinical studies. In contrast, in mouse neuroimaging, the focus is mainly on basic connectivity parameters, i.e., the correlation coefficient or fiber counts, whereas more advanced network analyses remain rarely used. This review summarizes graph theoretical measures and their interpretation to describe networks derived from recent in vivo mouse brain studies. To facilitate the entry into the topic, we explain the related mathematical definitions, provide a dedicated software toolkit, and discuss practical considerations for the application to rs-fMRI and DTI. This way, we aim to foster cross-species comparisons and the application of standardized measures to classify and interpret network changes in translational brain disease studies.

Seeing the Forest and Its Trees Together: Implementing 3D Light Microscopy Pipelines for Cell Type Mapping in the Mouse Brain

The brain is composed of diverse neuronal and non-neuronal cell types with complex regional connectivity patterns that create the anatomical infrastructure underlying cognition. Remarkable advances in neuroscience techniques enable labeling and imaging of these individual cell types and their interactions throughout intact mammalian brains at a cellular resolution allowing neuroscientists to examine microscopic details in macroscopic brain circuits. Nevertheless, implementing these tools is fraught with many technical and analytical challenges with a need for high-level data analysis. Here we review key technical considerations for implementing a brain mapping pipeline using the mouse brain as a primary model system. Specifically, we provide practical details for choosing methods including cell type specific labeling, sample preparation (e.g., tissue clearing), microscopy modalities, image processing, and data analysis (e.g., image registration to standard atlases). We also highlight the need to develop better 3D atlases with standardized anatomical labels and nomenclature across species and developmental time points to extend the mapping to other species including humans and to facilitate data sharing, confederation, and integrative analysis. In summary, this review provides key elements and currently available resources to consider while developing and implementing high-resolution mapping methods.

Towards an Architecture of a Multi-purpose, User-Extendable Reference Human Brain Atlas

Human brain atlas development is predominantly research-oriented and the use of atlases in clinical practice is limited. Here I introduce a new definition of a reference human brain atlas that serves education, research and clinical applications, and is extendable by its user. Subsequently, an architecture of a multi-purpose, user-extendable reference human brain atlas is proposed and its implementation discussed. The human brain atlas is defined as a vehicle to gather, present, use, share, and discover knowledge about the human brain with highly organized content, tools enabling a wide range of its applications, massive and heterogeneous knowledge database, and means for content and knowledge growing by its users. The proposed architecture determines major components of the atlas, their mutual relationships, and functional roles. It contains four functional units, core cerebral models, knowledge database, research and clinical data input and conversion, and toolkit (supporting processing, content extension, atlas individualization, navigation, exploration, and display), all united by a user interface. Each unit is described in terms of its function, component modules and sub-modules, data handling, and implementation aspects. This novel architecture supports brain knowledge gathering, presentation, use, sharing, and discovery and is broadly applicable and useful in student- and educator-oriented neuroeducation for knowledge presentation and communication, research for knowledge acquisition, aggregation and discovery, and clinical applications in decision making support for prevention, diagnosis, treatment, monitoring, and prediction. It establishes a backbone for designing and developing new, multi-purpose and user-extendable brain atlas platforms, serving as a potential standard across labs, hospitals, and medical schools.

Ratlas-LH: An MRI template of the Lister hooded rat brain with stereotaxic coordinates for neurosurgical implantations

There is currently no brain atlas available to specifically determine stereotaxic coordinates for neurosurgery in Lister hooded rats despite the popularity of this strain for behavioural neuroscience studies in the United Kingdom and elsewhere. We have created a dataset, which we refer to as ‘Ratlas-LH’ (for Lister hooded). Ratlas-LH combines in vivo magnetic resonance images of the brain of young adult male Lister hooded rats with ex vivo micro-computed tomography images of the ex vivo skull, as well as a set of delineations of brain regions, adapted from the Waxholm Space Atlas of the Sprague Dawley Rat Brain. Ratlas-LH was produced with an isotropic resolution of 0.15 mm. It has been labelled in such a way as to provide a stereotaxic coordinate system for the determination of distances relative to the skull landmark of bregma. We have demonstrated that the atlas can be used to determine stereotaxic coordinates to accurately target brain regions in the Lister hooded rat brain. Ratlas-LH is freely available to facilitate neurosurgical procedures in the Lister hooded rat.

Diffusion Tensor Imaging Reveals Whole-Brain Microstructural Changes in the P301L Mouse Model of Tauopathy

INTRODUCTION

Increased expression of hyperphosphorylated tau and the formation of neurofibrillary tangles are associated with neuronal loss and white matter damage. Using high-resolution ex vivo diffusion tensor imaging (DTI), we investigated microstructural changes in the white and grey matter in the P301L mouse model of human tauopathy at 8.5 months of age. For unbiased computational analysis, we implemented a pipeline for voxel-based analysis (VBA) and atlas-based analysis (ABA) of DTI mouse brain data.

METHODS

Hemizygous and homozygous transgenic P301L mice and non-transgenic littermates were used. DTI data were acquired for generation of fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) maps. VBA on the entire brain was performed using SPM8 and the SPM Mouse toolbox. Initially, all DTI maps were coregistered with the Allen mouse brain atlas to bring them to one common coordinate space. In VBA, coregistered DTI maps were normalized and smoothed in order to perform two-sample and unpaired t tests with false discovery rate correction to compare hemizygotes with non-transgenic littermates, homozygotes with non-transgenic littermates, and hemizygotes with homozygotes on each DTI parameter map. In ABA, the average values for selected regions of interests were computed with coregistered DTI maps and labels in Allen mouse brain atlas. Afterwards, a Kruskal-Wallis one-way ANOVA on ranks with a Tukey post hoc test was executed on the estimated average values.

RESULTS

With VBA, we found pronounced and brain-wide spread changes when comparing homozygous, P301L mice with non-transgenic littermates, which were not seen when comparing hemizygous P301L with non-transgenic animals. Statistical comparison of DTI metrics in selected brain regions by ABA corroborated findings from VBA. FA was found to be decreased in most brain regions, while MD, RD, and AD were increased in homozygotes compared to hemizygotes and non-transgenic littermates.

DISCUSSION/CONCLUSION

High-resolution ex vivo DTI demonstrated brain-wide microstructural and gene-dose-dependent changes in the P301L mouse model of human tauopathy. The DTI analysis pipeline may serve for the phenotyping of models of tauopathy and other brain diseases.

Constructing the rodent stereotaxic brain atlas: a survey

The stereotaxic brain atlas is a fundamental reference tool commonly used in the field of neuroscience. Here we provide a brief history of brain atlas development and clarify three key conceptual elements of stereotaxic brain atlasing: brain image, atlas, and stereotaxis. We also refine four technical indices for evaluating the construction of atlases: the quality of staining and labeling, the granularity of delineation, spatial resolution, and the precision of spatial location and orientation. Additionally, we discuss state-of-the-art technologies and their trends in the fields of image acquisition, stereotaxic coordinate construction, image processing, anatomical structure recognition, and publishing: the procedures of brain atlas illustration. We believe that the use of single-cell resolution and micron-level location precision will become a future trend in the study of the stereotaxic brain atlas, which will greatly benefit the development of neuroscience.

Flexible annotation atlas of the mouse brain: combining and dividing brain structures of the Allen Brain Atlas while maintaining anatomical hierarchy

A brain atlas is necessary for analyzing structure and function in neuroimaging research. Although various annotation volumes (AVs) for the mouse brain have been proposed, it is common in magnetic resonance imaging (MRI) of the mouse brain that regions-of-interest (ROIs) for brain structures (nodes) are created arbitrarily according to each researcher's necessity, leading to inconsistent ROIs among studies. One reason for such a situation is the fact that earlier AVs were fixed, i.e. combination and division of nodes were not implemented. This report presents a pipeline for constructing a flexible annotation atlas (FAA) of the mouse brain by leveraging public resources of the Allen Institute for Brain Science on brain structure, gene expression, and axonal projection. A mere two-step procedure with user-specified, text-based information and Python codes constructs FAA with nodes which can be combined or divided objectively while maintaining anatomical hierarchy of brain structures. Four FAAs with total node count of 4, 101, 866, and 1381 were demonstrated. Unique characteristics of FAA realized analysis of resting-state functional connectivity (FC) across the anatomical hierarchy and among cortical layers, which were thin but large brain structures. FAA can improve the consistency of whole brain ROI definition among laboratories by fulfilling various requests from researchers with its flexibility and reproducibility.

Evolution of Human Brain Atlases in Terms of Content, Applications, Functionality, and Availability

Human brain atlases have been evolving tremendously, propelled recently by brain big projects, and driven by sophisticated imaging techniques, advanced brain mapping methods, vast data, analytical strategies, and powerful computing. We overview here this evolution in four categories: content, applications, functionality, and availability, in contrast to other works limited mostly to content. Four atlas generations are distinguished: early cortical maps, print stereotactic atlases, early digital atlases, and advanced brain atlas platforms, and 5 avenues in electronic atlases spanning the last two generations. Content-wise, new electronic atlases are categorized into eight groups considering their scope, parcellation, modality, plurality, scale, ethnicity, abnormality, and a mixture of them. Atlas content developments in these groups are heading in 23 various directions. Application-wise, we overview atlases in neuroeducation, research, and clinics, including stereotactic and functional neurosurgery, neuroradiology, neurology, and stroke. Functionality-wise, tools and functionalities are addressed for atlas creation, navigation, individualization, enabling operations, and application-specific. Availability is discussed in media and platforms, ranging from mobile solutions to leading-edge supercomputers, with three accessibility levels. The major application-wise shift has been from research to clinical practice, particularly in stereotactic and functional neurosurgery, although clinical applications are still lagging behind the atlas content progress. Atlas functionality also has been relatively neglected until recently, as the management of brain data explosion requires powerful tools. We suggest that the future human brain atlas-related research and development activities shall be founded on and benefit from a standard framework containing the core virtual brain model cum the brain atlas platform general architecture.

A multimodal computational pipeline for 3D histology of the human brain

Ex vivo imaging enables analysis of the human brain at a level of detail that is not possible in vivo with MRI. In particular, histology can be used to study brain tissue at the microscopic level, using a wide array of different stains that highlight different microanatomical features. Complementing MRI with histology has important applications in ex vivo atlas building and in modeling the link between microstructure and macroscopic MR signal. However, histology requires sectioning tissue, hence distorting its 3D structure, particularly in larger human samples. Here, we present an open-source computational pipeline to produce 3D consistent histology reconstructions of the human brain. The pipeline relies on a volumetric MRI scan that serves as undistorted reference, and on an intermediate imaging modality (blockface photography) that bridges the gap between MRI and histology. We present results on 3D histology reconstruction of whole human hemispheres from two donors.

An MRI-Derived Neuroanatomical Atlas of the Fischer 344 Rat Brain

This paper reports the development of a high-resolution 3-D MRI atlas of the Fischer 344 adult rat brain. The atlas is a 60 μm isotropic image volume composed of 256 coronal slices with 71 manually delineated structures and substructures. The atlas was developed using Pydpiper image registration pipeline to create an average brain image of 41 four-month-old male and female Fischer 344 rats. Slices in the average brain image were then manually segmented, individually and bilaterally, on the basis of image contrast in conjunction with Paxinos and Watson's (2007) stereotaxic rat brain atlas. Summary statistics (mean and standard deviation of regional volumes) are reported for each brain region across the sample used to generate the atlas, and a statistical comparison of a chosen subset of regional brain volumes between male and female rats is presented. On average, the coefficient of variation of regional brain volumes across all rats in our sample was 4%, with no individual brain region having a coefficient of variation greater than 13%. A full description of methods used, as well as the atlas, the template that the atlas was derived from, and a masking file, can be found on Zenodo at www.zenodo.org/record/3700210. To our knowledge, this is the first MRI atlas created using Fischer 344 rats and will thus provide an appropriate neuroanatomical model for researchers working with this strain.

Anatomical variations of the dentate gyrus in normal adult brain

Recent scientific papers indicate the clinical significance of the dentate gyrus. However, a detailed knowledge of the anatomical variations of this structure in normal adult brain is still lacking. An understanding of the variable morphology of the dentate gyrus may be important for diagnostic neuroimaging. Thus, the purpose of this macroscopic cadaveric study was to describe the anatomical variations of the dentate gyrus. Forty formalin-fixed human cerebral hemispheres, obtained from bodies of donors without the history of neuropathological diseases, were included in the study. The dentate gyrus was classified as well-developed, when it protruded completely from under the fimbria of the hippocampus. The gyrus was classified as underdeveloped, when it was covered by the fimbria of the hippocampus (but clearly visible at the coronal section of the hippocampal formation), while the hypoplastic gyrus was not visible macroscopically under the fimbria of the hippocampus. The well-developed type was observed in 27 cases (67.5%). The thickness of well-developed type of the dentate gyrus, measured between the fimbriodentate sulcus and hippocampal sulcus, varied from 2.74 to 5.21 mm (mean = 3.67 mm, median = 5.54 mm, SD 0.65 mm). In the next nine cases (22.5%), the dentate gyrus was underdeveloped. The thickness of underdeveloped type of the dentate gyrus varied from 1.75 to 2.37 mm (mean = 2.02 mm, median = 2.16 mm, SD 0.33 mm). In the remaining four cases (10%), the dentate gyrus was hypoplastic and could not be distinguished macroscopically. In all injected hemispheres, arterial supply of the dentate gyrus was provided by the branches of the posterior cerebral artery. Awareness of normal variations of the dentate gyrus may allow for better correlation of anatomical knowledge with radiological data and for use this knowledge to describe abnormal conditions.

Processing Pipeline for Atlas-Based Imaging Data Analysis of Structural and Functional Mouse Brain MRI (AIDAmri)

Magnetic resonance imaging (MRI) is a key technology in multimodal animal studies of brain connectivity and disease pathology. In vivo MRI provides non-invasive, whole brain macroscopic images containing structural and functional information, thereby complementing invasive in vivo high-resolution microscopy and ex vivo molecular techniques. Brain mapping, the correlation of corresponding regions between multiple brains in a standard brain atlas system, is widely used in human MRI. For small animal MRI, however, there is no scientific consensus on pre-processing strategies and atlas-based neuroinformatics. Thus, it remains difficult to compare and validate results from different pre-clinical studies which were processed using custom-made code or individual adjustments of clinical MRI software and without a standard brain reference atlas. Here, we describe AIDAmri, a novel Atlas-based Imaging Data Analysis pipeline to process structural and functional mouse brain data including anatomical MRI, fiber tracking using diffusion tensor imaging (DTI) and functional connectivity analysis using resting-state functional MRI (rs-fMRI). The AIDAmri pipeline includes automated pre-processing steps, such as raw data conversion, skull-stripping and bias-field correction as well as image registration with the Allen Mouse Brain Reference Atlas (ARA). Following a modular structure developed in Python scripting language, the pipeline integrates established and newly developed algorithms. Each processing step was optimized for efficient data processing requiring minimal user-input and user programming skills. The raw data is analyzed and results transferred to the ARA coordinate system in order to allow an efficient and highly-accurate region-based analysis. AIDAmri is intended to fill the gap of a missing open-access and cross-platform toolbox for the most relevant mouse brain MRI sequences thereby facilitating data processing in large cohorts and multi-center studies.

A framework for multi-component analysis of diffusion MRI data over the neonatal period

We describe a framework for creating a time-resolved group average template of the developing brain using advanced multi-shell high angular resolution diffusion imaging data, for use in group voxel or fixel-wise analysis, atlas-building, and related applications. This relies on the recently proposed multi-shell multi-tissue constrained spherical deconvolution (MSMT-CSD) technique. We decompose the signal into one isotropic component and two anisotropic components, with response functions estimated from cerebrospinal fluid and white matter in the youngest and oldest participant groups, respectively. We build an orientationally-resolved template of those tissue components from data acquired from 113 babies between 33 and 44 weeks postmenstrual age, imaged as part of the Developing Human Connectome Project. These data were split into weekly groups, and registered to the corresponding group average templates using a previously-proposed non-linear diffeomorphic registration framework, designed to align orientation density functions (ODF). This framework was extended to allow the use of the multiple contrasts provided by the multi-tissue decomposition, and shown to provide superior alignment. Finally, the weekly templates were registered to the same common template to facilitate investigations into the evolution of the different components as a function of age. The resulting multi-tissue atlas provides insights into brain development and accompanying changes in microstructure, and forms the basis for future longitudinal investigations into healthy and pathological white matter maturation.