Biology subjects

Bjaalie, J. G.

Publications and source records attributed to Bjaalie, J. G..

12 recordsLinked to original sources

bioRxiv2026

An interactive 3D atlas of gene expression in the mouse brain

The Allen Mouse Brain Atlas provides gene expression data for over 20,000 genes and has been extensively used in neuroscience. However, its constrained by a resolution of 200 {micro}m3. We improved this to 25 {micro}m3 for 4,083 genes by re-registering 401,660 sections to atlas space. From this, we produced an atlas with regions defined by shared molecular signatures and built an interactive online platform allowing exploration of gene expression patterns.

neuroscience↗

bioRxiv2025

Siibra: A software tool suite for realizing a Multilevel Human Brain Atlas from complex data resources

Computational technology opens new possibilities towards understanding the complexity of the human brain, but it requires integrating measurements from different modalities and scales in anatomical context and exposing them in interoperable, actionable form. Especially with growing big data resources, accessing information from different scales and modalities coherently for visual exploration, reproducible analysis and application development remains challenging. We present siibra, a tool suite that connects diverse data from cloud resources to reference atlases and coordinate spaces. It supports different use cases by making contents accessible through a web viewer, Python library and HTTP API. Using siibra we implemented a Multilevel Human Brain Atlas linking macro-anatomical concepts and their inter-subject variability with measurements of the microstructural composition and intrinsic variance of brain regions, building on cytoarchitecture as a reference and supporting MRI-based and microscopic templates. The atlas is integrated with the EBRAINS research infrastructure. All software and content are openly accessible.

bioinformatics↗

bioRxiv2025

Software and pipelines for registration and analyses of rodent brain image data in reference atlas space

Advancements in methodologies for large-scale acquisition of high-resolution serial microscopy image data have opened new possibilities for experimental studies of cellular and subcellular features across whole brains in animal models. There is a high demand for open-source software and workflows for automated or semi-automated analysis of such data, facilitating anatomical, functional, and molecular mapping in healthy and diseased brains. These studies share a common need to precisely identify, visualize, and quantify the location of observations within anatomically defined regions, ensuring consistent and reproducible interpretation of anatomical locations and thereby allowing meaningful comparisons of results across multiple independent studies. Addressing this need, we have developed a suite of desktop and web-applications for registration of serial brain section images to three-dimensional brain reference atlases (QuickNII, VisuAlign, WebAlign, WebWarp, and DeepSlice) and for performing data analysis in a spatial context provided by an atlas (Nutil, QCAlign, SeriesZoom, LocaliZoom, and MeshView). The software can be utilized in various combinations, creating customized analytical pipelines suited to specific research needs. The web-applications are integrated in the EBRAINS research infrastructure and coupled to the EBRAINS data platform, establishing the foundation for an online analytical workbench. We here present our software ecosystem, exemplify its use by the research community, and discuss possible directions for future developments.

bioinformatics↗

bioRxiv2024

An extended and improved CCFv3 annotation and Nissl atlas of the entire mouse brain

Brain atlases are essential for quantifying cellular composition in mouse brain regions. The Allen Institutes Common Coordinate Framework version 3 (CCFv3) is widely used, delineating over 600 anatomical regions, but it lacks coverage for the most rostral and caudal brain parts, including the main olfactory bulb, cerebellum, and medulla. Additionally, the CCFv3 omits key cerebellar layers, and its corresponding Nissl-stained reference volume is not precisely aligned, limiting its utilisability. To address these issues, we developed an extended atlas, the Blue Brain Project CCFv3 augmented (CCFv3aBBP), which includes a fully annotated mouse brain and an improved Nissl reference aligned in the CCFv3. This enhanced atlas also features the central nervous system annotation (CCFv3cBBP). Using this resource, we aligned 734 Nissl-stained brains to produce an average Nissl template, enabling an updated distribution of neuronal soma positions. These data are available as an open-source resource, broadening applications such as improved alignment precision, cell type mapping, and multimodal data integration.

bioinformatics↗

bioRxiv2024

DeMBA: a developmental atlas for navigating the mouse brain in space and time

Studies of the adult mouse brain have benefited from three-dimensional (3D) atlases providing standardised frameworks for data analysis and integration. However, few 3D atlases exist for the developing mouse brain, and none cover more than a few ages. This fails to represent the dynamic nature of development and is insufficient for researchers whose data fall between the ages of existent atlases. Existing atlases also neglect the spatial correspondence between ages, making comparison across ages difficult. We present the Developmental Mouse Brain Atlas (DeMBA), a 4D atlas encompassing every postnatal day from 4 to 56. DeMBA is incorporated in software for spatial registration and analysis, enabling brain-wide quantification of features of interest. Furthermore, we provide a software package, the CCF translator, allowing coordinates or image volumes to be transformed between ages for comparison. These resources provide age-specific spatial frameworks incorporated in accessible analytic pipelines for developmental mouse brain data.

neuroscience↗

bioRxiv2024

The developing mouse dopaminergic system: Cortical-subcortical shift in D1/D2 receptor balance and increasing regional differentiation

The dopaminergic system of the brain is involved in complex cognitive functioning and undergoes extensive reorganization during development. Yet, these changes are poorly characterized. We have quantified the density of dopamine 1- and 2-receptor (D1 and D2) positive cells across the forebrain of male and female mice at five developmental stages. Our findings show a cortico-subcortical shift in D1/D2 balance, with increasing D1 dominance in cortical regions as a maturational pattern that occurs earlier in females. We describe postnatal trajectories of D1 and D2 cell densities across major brain regions and observe increasing regional differentiation of D1 densities through development. Our results provide the most comprehensive overview of the developing dopaminergic system to date, and an empirical foundation for further experimental and computational investigations of dopaminergic signaling.

neuroscience↗

bioRxiv2023

Detecting the effect of genetic diversity on brain composition in an Alzheimer's disease mouse model

Alzheimers disease (AD) is characterized by neurodegeneration, pathology accumulation, and progressive cognitive decline. There is significant variation in age at onset and severity of symptoms highlighting the importance of genetic diversity in the study of AD. To address this, we analyzed cell and pathology composition of 6- and 14-month-old AD-BXD mouse brains using the semi-automated workflow (QUINT); which we expanded to allow for nonlinear refinement of brain atlas-registration, and quality control assessment of atlas-registration and brain section integrity. Near global age-related increases in microglia, astrocyte, and amyloid-beta accumulation were measured, while regional variation in neuron load existed among strains. Furthermore, hippocampal immunohistochemistry analyses were combined with bulk RNA- sequencing results to demonstrate the relationship between cell composition and gene expression. Overall, the additional functionality of the QUINT workflow delivers a highly effective method for registering and quantifying cell and pathology changes in diverse disease models.

neuroscience↗

bioRxiv2023

AtOM, an ontology model for standardizing use of brain atlases in tools, workflows, and data infrastructures

Brain atlases are important reference resources for accurate anatomical description of neuroscience data. Open access, three-dimensional atlases serve as spatial frameworks for integrating experimental data and defining regions-of-interest in analytic workflows. However, naming conventions, parcellation criteria, area definitions, and underlying mapping methodologies differ considerably between atlases and across atlas versions. This lack of standardization impedes use of atlases in analytic tools and registration of data to different atlases. To establish a machine-readable standard for representing brain atlases, we identified four fundamental atlas elements, defined their relations, and created an ontology model. Here we present our Atlas Ontology Model (AtOM) and exemplify its use by applying it to mouse, rat, and human brain atlases. We propose minimum requirements for FAIR atlases and discuss how AtOM may facilitate atlas interoperability and data integration. AtOM provides a standardized framework for communication and use of brain atlases to create, use, and refer to specific atlas elements and versions. We argue that AtOM will accelerate analysis, sharing, and reuse of neuroscience data.

neuroscience↗

bioRxiv2022

The BRAIN Initiative Cell Census Data Ecosystem: A User's Guide

Characterizing cellular diversity at different levels of biological organization across data modalities is a prerequisite to understanding the function of cell types in the brain. Classification of neurons is also required to manipulate cell types in controlled ways, and to understand their variation and vulnerability in brain disorders. The BRAIN Initiative Cell Census Network (BICCN) is an integrated network of data generating centers, data archives and data standards developers, with the goal of systematic multimodal brain cell type profiling and characterization. Emphasis of the BICCN is on the whole mouse brain and demonstration of prototypes for human and non-human primate (NHP) brains. Here, we provide a guide to the cellular and spatial approaches employed, and to accessing and using the BICCN data and its extensive resources, including the BRAIN Cell Data Center (BCDC) which serves to manage and integrate data across the ecosystem. We illustrate the power of the BICCN data ecosystem through vignettes highlighting several BICCN analysis and visualization tools. Finally, we present emerging standards that have been developed or adopted by the BICCN toward FAIR (Wilkinson et al. 2016a) neuroscience. The combined BICCN ecosystem provides a comprehensive resource for the exploration and analysis of cell types in the brain.

bioinformatics↗

bioRxiv2022

DeepSlice: rapid fully automatic registration of mouse brain imaging to a volumetric atlas

Registration of data to a common frame of reference is an essential step in the analysis and integration of diverse neuroscientific data modalities. To this end, volumetric brain atlases enable histological datasets to be spatially registered and analysed, yet accurate registration remains expertise-dependent and slow. We have trained a neural network, DeepSlice, to register mouse brain histology to the Allen Brain Atlas, retaining accuracy while improving speed by >1000 fold.

neuroscience↗

bioRxiv2021

3D atlas of the pituitary gland of the model fish medaka

In vertebrates, the anterior pituitary plays a crucial role in regulating several essential physiological processes via the secretion of at least seven peptide hormones by different endocrine cell types. Comparative and comprehensive knowledge of the spatial distribution of those endocrine cell types is required to better understand their role during the animal life. Using medaka as the model and several combinations of multi-color fluorescence in situ hybridization, we present the first 3D atlas revealing the gland-wide distribution of seven endocrine cell populations: lactotropes, thyrotropes, Lh and Fsh gonadotropes, somatotropes, and pomca-expressing cells (corticotropes and melanotropes) in the anterior pituitary of a teleost fish. By combining in situ hybridization and immunofluorescence techniques, we deciphered the location of corticotropes and melanotropes within the pomca-expressing cell population. The 3D localization approach reveals sexual dimorphism of tshba- and pomca-expressing cells in the adult medaka pituitary. Finally, we show the existence of bi-hormonal cells co-expressing lhb-fshb, fshb-tshba and lhb-sl using single-cell transcriptomics analysis and in situ hybridization. This study offers a solid basis for future comparative studies of the teleost pituitary and its developmental plasticity. Highlights- We offer the first 3D atlas of a teleost pituitary, which presents a valuable resource to the endocrinology and model fish community. - The atlas reveals the 3D spatial distribution of the seven endocrine cell types and blood vessels in the juvenile/adult male and female pituitary. - Gene expression for tshba and pomca, as well as the population size of cells expressing these genes, displays obvious sexual dimorphism in the adult medaka pituitary. - Multi-color in situ hybridization and single cell RNA-seq reveal the existence of bi-hormonal cells, co-expressing lhb-fshb, fshb-tshba, lhb-sl, and a few multi-hormonal cells. - An online version of the atlas is available at https://www.nmbu.no/go/mpg-atlas.

neuroscience↗

bioRxiv2021

Topography of corticopontine projections is controlled by postmitotic expression of the area-mapping gene Nr2f1

Axonal projections from layer V neurons of distinct neocortical areas are topographically organized into discrete clusters within the pontine nuclei during the establishment of voluntary movements. However, the molecular determinants controlling corticopontine connectivity are insufficiently understood. Here, we show that an intrinsic cortical genetic program driven by Nr2f1 graded expression is directly implicated in the organization of corticopontine topographic mapping. Transgenic mice lacking cortical expression of Nr2f1 and exhibiting areal organization defects were used as model systems to investigate the arrangement of corticopontine projections. Combining three-dimensional digital brain atlas tools, Cre-dependent mouse lines, and axonal tracing, we show that Nr2f1 expression in postmitotic neurons spatially and temporally controls somatosensory topographic projections, whereas expression in progenitor cells influences the ratio between corticopontine and corticospinal fibres passing the pontine nuclei. We conclude that cortical gradients of area patterning genes are directly implicated in the establishment of a topographic somatotopic mapping from the cortex onto pontine nuclei. Summary statementCortical gradient expression of the area patterning gene Nr2f1 spatially and temporally controls corticopontine topographic connectivity in layer V projection neurons.

neuroscience↗