Trygve Brauns Leergaard

• Abrams, Mathew; Denker, Michael; Depannemaecker, Damien; Ferreira, Joao Alves; Frings, Maren & Hashemi, Meysam [Show all 16 contributors for this article] (2026). The neuroscience education readiness checklist for digital tools and methods. Frontiers in Computational Neuroscience. 20, p. 1–11. doi: 10.3389/fncom.2026.1812915. Full text in Research Archive
• Dickscheid, Timo; Gui, Xiaoyun; Simsek, Ahmet N.; Schiffer, Christian; Mangin, Jean Francois & Leprince, Yann [Show all 11 contributors for this article] (2026). Siibra: a software tool suite for realizing a Multilevel Human Brain Atlas from complex data resources. Nature Methods. ISSN 1548-7091. doi: 10.1038/s41592-026-03159-x. Full text in Research Archive Show summary

  Computational technology opens new possibilities toward understanding the complexity of the human brain, but it requires integrating measurements from different modalities and scales in an anatomical context and exposing them in an 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. Here 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 application programming interface. 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.

• Puchades, Maja; Yates, Sharon Christine; Csucs, Gergely; Carey, Harry Alexander Chandler; Balkir, Arda & Leergaard, Trygve B. [Show all 7 contributors for this article] (2025). Software and pipelines for registration and analyses of rodent brain image data in reference atlas space. Frontiers in Neuroinformatics. 19, p. 1–15. doi: 10.3389/fninf.2025.1629388. Full text in Research Archive Show summary

  Advancements in methodologies for efficient 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 consistently identify, visualize, and quantify the location of observations within anatomically defined regions, ensuring 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.

• Carey, Harry Alexander Chandler; Kleven, Heidi; Øvsthus, Martin; Yates, Sharon Christine; Csucs, Gergely & Puchades, Maja A. [Show all 10 contributors for this article] (2025). DeMBA: a developmental atlas for navigating the mouse brain in space and time. Nature Communications. 16. doi: 10.1038/s41467-025-63177-9. Full text in Research Archive Show summary

  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 was created by using existing brain templates for six developmental time points and interpolating intermediate ages. DeMBA is incorporated in software for spatial registration and analysis, enabling brain-wide quantification of features of interest. Furthermore, we provide the software package 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.

• Puchades, Maja; Yates, Sharon Christine; Csucs, Gergely; Carey, Harry; Balkir, Arda & Leergaard, Trygve B. [Show all 7 contributors for this article] (2025). Software and pipelines for registration and analyses of rodent brain image data in reference atlas space. bioRxiv. ISSN 2692-8205. Full text in Research Archive
• Jelescu, Ileana O.; Grussu, Francesco; Ianus, Andrada; Hansen, Brian; Barrett, Rachel L. C. & Aggarwal, Manisha [Show all 57 contributors for this article] (2025). Considerations and recommendations from the ISMRM diffusion study group for preclinical diffusion MRI: Part 1: In vivo small-animal imaging. Magnetic Resonance in Medicine. ISSN 0740-3194. 93(6), p. 2507–2534. doi: 10.1002/mrm.30429. Full text in Research Archive Show summary

  Small-animal diffusion MRI (dMRI) has been used for methodological development and validation, characterizing the biological basis of diffusion phenomena, and comparative anatomy. The steps from animal setup and monitoring, to acquisition, analysis, and interpretation are complex, with many decisions that may ultimately affect what questions can be answered using the resultant data. This work aims to present selected considerations and recommendations from the diffusion community on best practices for preclinical dMRI of in vivo animals. We describe the general considerations and foundational knowledge that must be considered when designing experiments. We briefly describe differences in animal species and disease models and discuss why some may be more or less appropriate for different studies. We, then, give recommendations for in vivo acquisition protocols, including decisions on hardware, animal preparation, and imaging sequences, followed by advice for data processing including preprocessing, model-fitting, and tractography. Finally, we provide an online resource that lists publicly available preclinical dMRI datasets and software packages to promote responsible and reproducible research. In each section, we attempt to provide guides and recommendations, but also highlight areas for which no guidelines exist (and why), and where future work should focus. Although we mainly cover the central nervous system (on which most preclinical dMRI studies are focused), we also provide, where possible and applicable, recommendations for other organs of interest. An overarching goal is to enhance the rigor and reproducibility of small animal dMRI acquisitions and analyses, and thereby advance biomedical knowledge.

• Schilling, Kurt G.; Howard, Amy F. D.; Grussu, Francesco; Ianus, Andrada; Hansen, Brian & Barrett, Rachel L. C. [Show all 58 contributors for this article] (2025). Considerations and recommendations from the ISMRM Diffusion Study Group for preclinical diffusion MRI: Part 3—Ex vivo imaging: Data processing, comparisons with microscopy, and tractography. Magnetic Resonance in Medicine. ISSN 0740-3194. 93(6), p. 2561–2582. doi: 10.1002/mrm.30424. Full text in Research Archive
• Bjerke, Ingvild Elise; Carey, Harry Alexander Chandler; Bjaalie, Jan G.; Leergaard, Trygve B. & Kim, Jee Hyun (2025). The developing mouse dopaminergic system: Cortical-subcortical shift in D1/D2 receptor balance and increasing regional differentiation. Neurochemistry International. ISSN 0197-0186. 182. doi: 10.1016/j.neuint.2024.105899. Full text in Research Archive Show summary

  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 using validated transgenic mice expressing green fluorescent protein in cells producing D1 or D2 mRNA. After analyzing >4,500 coronal brain images, a cortico-subcortical shift in D1/D2 balance was discovered, 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.

• Carey, Harry Alexander Chandler; Kleven, Heidi; Øvsthus, Martin; Yates, Sharon Christine; Csucs, Gergely & Puchades, Maja [Show all 9 contributors for this article] (2024). DeMBA: a developmental atlas for navigating the mouse brain in space and time. bioRxiv. ISSN 2692-8205. doi: 10.1101/2024.06.14.598876. Full text in Research Archive Show summary

  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 was created by using existing brain templates for six developmental time points and interpolating intermediate ages. DeMBA is incorporated in software for spatial registration and analysis, enabling brain-wide quantification of features of interest. Furthermore, we provide the software package 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.

• Blixhavn, Camilla Hagen; Reiten, Ingrid; Kleven, Heidi; Øvsthus, Martin; Yates, Sharon Christine & Schlegel, Ulrike [Show all 11 contributors for this article] (2024). The Locare workflow: representing neuroscience data locations as geometric objects in 3D brain atlases. Frontiers in Neuroinformatics. 18. doi: 10.3389/fninf.2024.1284107. Full text in Research Archive Show summary

  Neuroscientists employ a range of methods and generate increasing amounts of data describing brain structure and function. The anatomical locations from which observations or measurements originate represent a common context for data interpretation, and a starting point for identifying data of interest. However, the multimodality and abundance of brain data pose a challenge for efforts to organize, integrate, and analyze data based on anatomical locations. While structured metadata allow faceted data queries, different types of data are not easily represented in a standardized and machine-readable way that allow comparison, analysis, and queries related to anatomical relevance. To this end, three-dimensional (3D) digital brain atlases provide frameworks in which disparate multimodal and multilevel neuroscience data can be spatially represented. We propose to represent the locations of different neuroscience data as geometric objects in 3D brain atlases. Such geometric objects can be specified in a standardized file format and stored as location metadata for use with different computational tools. We here present the Locare workflow developed for defining the anatomical location of data elements from rodent brains as geometric objects. We demonstrate how the workflow can be used to define geometric objects representing multimodal and multilevel experimental neuroscience in rat or mouse brain atlases. We further propose a collection of JSON schemas (LocareJSON) for specifying geometric objects by atlas coordinates, suitable as a starting point for co-visualization of different data in an anatomical context and for enabling spatial data queries.

• Øvsthus, Martin; Swieten, Maaike Margot Helène van; Puchades, Maja; Tocco, Chiara; Studer, Michèle & Bjaalie, Jan G. [Show all 7 contributors for this article] (2024). Spatially integrated cortico-subcortical tracing data for analyses of rodent brain topographical organization. Scientific Data. 11. doi: 10.1038/s41597-024-04060-y. Full text in Research Archive Show summary

  The cerebral cortex extends axonal projections to several subcortical brain regions, including the striatum, thalamus, superior colliculus, and pontine nuclei. Experimental tract-tracing studies have shown that these subcortical projections are topographically organized, reflecting the spatial organization of sensory surfaces and body parts. Several public collections of mouse- and rat- brain tract-tracing data are available, with the Allen mouse brain connectivity atlas being most prominent. There, a large body of image data can be inspected, but it is difficult to combine data from different experiments and compare spatial distribution patterns. To enable co-visualization and comparison of topographical organization in mouse brain cortico-subcortical projections across experiments, we represent axonal labelling data as point data in a common 3D brain atlas space. We here present a collection of point-cloud data representing spatial distribution of corticostriatal, corticothalamic, corticotectal, and cortico

• Gurdon, Brianna; Yates, Sharon Christine; Csucs, Gergely; Groeneboom, Nicolaas Ervik; Hadad, Niran & Telpoukhovskaia, Maria [Show all 19 contributors for this article] (2024). Detecting the effect of genetic diversity on brain composition in an Alzheimer’s disease mouse model. Communications Biology. 7(1). doi: 10.1038/s42003-024-06242-1. Full text in Research Archive Show summary

  Alzheimer’s disease (AD) is broadly characterized by neurodegeneration, pathology accumulation, and cognitive decline. There is considerable variation in the progression of clinical symptoms and pathology in humans, highlighting the importance of genetic diversity in the study of AD. To address this, we analyze cell composition and amyloid-beta deposition of 6- and 14-month-old AD-BXD mouse brains. We utilize the analytical QUINT workflow- a suite of software designed to support atlas-based quantification, which we expand to deliver a highly effective method for registering and quantifying cell and pathology changes in diverse disease models. In applying the expanded QUINT workflow, we quantify near-global age-related increases in microglia, astrocytes, and amyloid-beta, and we identify strain-specific regional variation in neuron load. To understand how individual differences in cell composition affect the interpretation of bulk gene expression in AD, we combine hippocampal immunohistochemistry analyses with bulk RNA-sequencing data. This approach allows us to categorize genes whose expression changes in response to AD in a cell and/or pathology load-dependent manner. Ultimately, our study demonstrates the use of the QUINT workflow to standardize the quantification of immunohistochemistry data in diverse mice, - providing valuable insights into regional variation in cellular load and amyloid deposition in the AD-BXD model.

• Kleven, Heidi; Schlegel, Ulrike; Groenewegen, Henk J.; Leergaard, Trygve Brauns & Bjerke, Ingvild Elise (2024). Comparison of basal ganglia regions across murine brain atlases using metadata models and the Waxholm Space. Scientific Data. 11. doi: 10.1038/s41597-024-03863-3. Full text in Research Archive Show summary

  The murine basal ganglia regions are targets for research into complex brain functions such as motor control and habit formation. However, there are several ways to name and annotate these regions, posing challenges for interpretation and comparison of data across studies. Here, we give an overview of basal ganglia terms and boundaries in the literature and reference atlases, and describe the criteria used for annotating these regions in the Waxholm Space rat brain atlas. We go on to compare basal ganglia annotations in stereotaxic rat brain atlases and the Allen Mouse brain Common Coordinate Framework to those in the Waxholm Space rat brain atlas. We demonstrate and describe considerable differences in the terms and boundaries of most basal ganglia regions across atlases and their versions. We also register information about atlases and regions in the openMINDS metadata framework, facilitating integration of data in neuroscience databases. The comparisons of terms and boundaries across rat and mouse atlases support analysis and interpretation of existing and new data from the basal ganglia.

• Kleven, Heidi; Reiten, Ingrid; Blixhavn, Camilla Hagen; Schlegel, Ulrike; Øvsthus, Martin & Papp, Eszter Agnes [Show all 10 contributors for this article] (2023). A neuroscientist’s guide to using murine brain atlases for efficient analysis and transparent reporting. Frontiers in Neuroinformatics. 17. doi: 10.3389/fninf.2023.1154080. Full text in Research Archive Show summary

  Brain atlases are widely used in neuroscience as resources for conducting experimental studies, and for integrating, analyzing, and reporting data from animal models. A variety of atlases are available, and it may be challenging to find the optimal atlas for a given purpose and to perform efficient atlas-based data analyses. Comparing findings reported using different atlases is also not trivial, and represents a barrier to reproducible science. With this perspective article, we provide a guide to how mouse and rat brain atlases can be used for analyzing and reporting data in accordance with the FAIR principles that advocate for data to be findable, accessible, interoperable, and re-usable. We first introduce how atlases can be interpreted and used for navigating to brain locations, before discussing how they can be used for different analytic purposes, including spatial registration and data visualization. We provide guidance on how neuroscientists can compare data mapped to different atlases and ensure transparent reporting of findings. Finally, we summarize key considerations when choosing an atlas and give an outlook on the relevance of increased uptake of atlas-based tools and workflows for FAIR data sharing.

• Kleven, Heidi; Bjerke, Ingvild Elise; Clascá, Francisco; Groenewegen, Henk J.; Bjaalie, Jan G. & Leergaard, Trygve B. (2023). Waxholm Space atlas of the rat brain: A 3D atlas supporting data analysis and integration. Nature Methods. ISSN 1548-7091. 20, p. 1822–1829. doi: 10.1038/s41592-023-02034-3. Full text in Research Archive Show summary

  Volumetric brain atlases are increasingly used to integrate and analyze diverse experimental neuroscience data acquired from animal models, but until recently a publicly available digital atlas with complete coverage of the rat brain has been missing. Here we present an update of the Waxholm Space rat brain atlas, a comprehensive open-access volumetric atlas resource. This brain atlas features annotations of 222 structures, of which 112 are new and 57 revised compared to previous versions. It provides a detailed map of the cerebral cortex, hippocampal region, striatopallidal areas, midbrain dopaminergic system, thalamic cell groups, the auditory system and main fiber tracts. We document the criteria underlying the annotations and demonstrate how the atlas with related tools and workflows can be used to support interpretation, integration, analysis and dissemination of experimental rat brain data.

• Bjerke, Ingvild Elise; Yates, Sharon Christine; Carey, Harry; Bjaalie, Jan G. & Leergaard, Trygve B. (2023). Scaling up cell-counting efforts in neuroscience through semi-automated methods. iScience. 26(9). doi: 10.1016/j.isci.2023.107562. Full text in Research Archive Show summary

  Quantifying how the cellular composition of brain regions vary across development, aging, sex, and disease, is crucial in experimental neuroscience, and the accuracy of different counting methods is continuously debated. Due to the tedious nature of most counting procedures, studies are often restricted to one or a few brain regions. Recently, there have been considerable methodological advances in combining semi-automated feature extraction with brain atlases for cell quantification. Such methods hold great promise for scaling up cell-counting efforts. However, little focus has been paid to how these methods should be implemented and reported to support reproducibility. Here, we provide an overview of practices for conducting and reporting cell counting in mouse and rat brains, showing that critical details for interpretation are typically lacking. We go on to discuss how novel methods may increase efficiency and reproducibility of cell counting studies. Lastly, we provide practical recommendations for researchers planning cell counting.

• Kleven, Heidi; Gillespie, Thomas; Zehl, Lyuba; Dickscheid, Timo; Bjaalie, Jan G. & E., Martone Maryann [Show all 7 contributors for this article] (2023). AtOM, an ontology model to standardize use of brain atlases in tools, workflows, and data infrastructures. Scientific Data. 10(1). doi: 10.1038/s41597-023-02389-4. Full text in Research Archive Show summary

  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 standardized description 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 discuss how AtOM can facilitate atlas interoperability and data integration, thereby increasing compliance with the FAIR guiding principles. 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.

• Gurdon, Brianna; Yates, Sharon Christine; Csucs, Gergely; Groeneboom, Nicolaas; Hadad, Niran & Telpoukhovskaia, Maria [Show all 19 contributors for this article] (2023). Detecting the effect of genetic diversity on brain composition in an Alzheimer's disease mouse model. bioRxiv. ISSN 2692-8205. doi: 10.1101/2023.02.27.530226. Full text in Research Archive
• Blixhavn, Camilla Hagen; Haug, Finn-Mogens Smejda; Kleven, Heidi; Puchades, Maja; Bjaalie, Jan G. & Leergaard, Trygve B. (2023). A Timm-Nissl multiplane microscopic atlas of rat brain zincergic terminal fields and metal-containing glia. Scientific Data. 10(150). doi: 10.1038/s41597-023-02012-6. Full text in Research Archive Show summary

  The ability of Timm’s sulphide silver method to stain zincergic terminal fields has made it a useful neuromorphological marker. Beyond its roles in zinc-signalling and neuromodulation, zinc is involved in the pathophysiology of ischemic stroke, epilepsy, degenerative diseases and neuropsychiatric conditions. In addition to visualising zincergic terminal fields, the method also labels transition metals in neuronal perikarya and glial cells. To provide a benchmark reference for planning and interpretation of experimental investigations of zinc-related phenomena in rat brains, we have established a comprehensive repository of serial microscopic images from a historical collection of coronally, horizontally and sagittally oriented rat brain sections stained with Timm’s method. Adjacent Nissl-stained sections showing cytoarchitecture, and customised atlas overlays from a three-dimensional rat brain reference atlas registered to each section image are included for spatial reference and guiding identification of anatomical boundaries. The Timm-Nissl atlas, available from EBRAINS, enables experimental researchers to navigate normal rat brain material in three planes and investigate the spatial distribution and density of zincergic terminal fields across the entire brain.

• Reiten, Ingrid; Olsen, Grethe Mari; Bjaalie, Jan G.; Witter, Menno Peter & Leergaard, Trygve B. (2023). The efferent connections of theorbitofrontal, posterior parietal,and insular cortex of the rat brain. Scientific Data. 10(645), p. 1–17. doi: 10.1038/s41597-023-02527-y. Full text in Research Archive Show summary

  The orbitofrontal, posterior parietal, and insular cortices are sites of higher-order cognitive processing implicated in a wide range of behaviours, including working memory, attention guiding, decision making, and spatial navigation. To better understand how these regions contribute to such functions, we need detailed knowledge about the underlying structural connectivity. Several tract-tracing studies have investigated specific aspects of orbitofrontal, posterior parietal and insular connectivity, but a digital resource for studying the cortical and subcortical projections from these areas in detail is not available. We here present a comprehensive collection of brightfield and fluorescence microscopic images of serial coronal sections from 49 rat brain tract-tracing experiments, in which discrete injections of the anterograde tracers biotinylated dextran amine and/or Phaseolus vulgaris leucoagglutinin were placed in the orbitofrontal, parietal, or insular cortex. The images are spatially registered to the Waxholm Space Rat brain atlas. The image collection, with corresponding reference atlas maps, is suitable as a reference framework for investigating the brain-wide efferent connectivity of these cortical association areas.

• Blackstad, Jan Sigurd Beddari; Osen, Kirsten Kjelsberg & Leergaard, Trygve Brauns (2022). The fibro- and cyto-architecture demarcating the border between the dentate gyrus and CA3 in sheep (Ovis aries) and domestic pig (Sus scrofa domesticus). Hippocampus. ISSN 1050-9631. 32(9), p. 639–659. doi: 10.1002/hipo.23457. Full text in Research Archive Show summary

  The hippocampal formation is essential for spatial navigation and episodic memory. The anatomical structure is largely similar across mammalian species, apart from the deep polymorphic layer of the dentate gyrus and the adjacent part of cornu ammonis 3 (CA3) which feature substantial variations. In rodents, the polymorphic layer has a triangular cross-section abutting on the end of the CA3 pyramidal layer, while in primates it is long and band-shaped capping the expanded CA3 end, which here lacks a distinct pyramidal layer. This structural variation has resulted in a confusing nomenclature and unclear anatomical criteria for the definition of the dentate-ammonic border. Seeking to clarify the border, we present here a light microscopic investigation based on Golgi-impregnated and Timm–thionin-stained sections of the Artiodactyla sheep and domestic pig, in which the dentate gyrus and CA3 end have some topographical features in common with primates. In short, the band-shaped polymorphic layer coincides with the Timm-positive mossy fiber collateral plexus and the Timm-negative subgranular zone. While the soma and excrescence-covered proximal dendrites of the mossy cells are localized within the plexus, the peripheral mossy cell dendrites extend outside the plexus, both into the granular and molecular layers, and the CA3. The main mossy fibers leave the collateral plexus in a scattered formation to converge gradually through the CA3 end in between the dispersed pyramidal cells, which are of three subtypes, as in monkey, with the classical apical subtype dominating near the hidden blade, the nonapical subtype near the exposed blade, and the dentate subtype being the only pyramidal cells that extend dendrites into the dentate gyrus. In agreement with our previous study in mink, the findings show that the border between the dentate gyrus and the CA3 end can be more accurately localized by the mossy fiber system than by cyto-architecture alone.

• Leergaard, Trygve B. & Bjaalie, Jan G. (2022). Atlas-based data integration for mapping the connections and architecture of the brain. Science. ISSN 0036-8075. 378(6619), p. 488–492. doi: 10.1126/science.abq2594. Full text in Research Archive Show summary

  Detailed knowledge about the neural connections among regions of the brain is key for advancing our understanding of normal brain function and changes that occur with aging and disease. Researchers use a range of experimental techniques to map connections at different levels of granularity in rodent animal models, but the results are often challenging to compare and integrate. Three-dimensional reference atlases of the brain provide new opportunities for cumulating, integrating, and reinterpreting research findings across studies. Here, we review approaches for integrating data describing neural connections and other modalities in rodent brain atlases and discuss how atlas-based workflows can facilitate brainwide analyses of neural network organization in relation to other facets of neuroarchitecture.

• Mehlum, Camilla Sivesind; Mahmood, Hanan; Ellingsen, Kristoffer Glenne; Øyen, Ole Morten; Leergaard, Trygve B. & Spurkland, Anne (2022). Self-reported anatomy skills among Norwegian physicians - Need for improved postgraduate teaching provision. European Journal of Anatomy (EJA). ISSN 1136-4890. 26(4), p. 465–476. doi: 10.52083/GQLP6804. Full text in Research Archive Show summary

  Anatomy skills are considered essential in all aspects of medical practice, and more so now than before with increasing use of diagnostic imaging techniques and advanced surgery. In conjunction with the revision of the medical study curriculum at the University of Oslo in 2014, we investigated Norwegian physicians’ assessment of their own anatomy knowledge and the educational provision of anatomical skills during and after specialization. A total of 902 Norwegian physicians divided into the specialties of general medicine, internal medicine, surgery, neurology and radiology responded to an anonymous survey. As many as 73% of the physicians had at some time point experienced insufficient anatomy knowledge in their own practice, most commonly among surgeons and neurologists. The respondents expressed a need for supplementary educational provision in anatomy during and after specialization, and 36% were unfamiliar with such offers. Notably, dissection courses seemed unavailable during specialization. Our findings demonstrate a requirement for an improved supply of anatomy education during and after specialization. Anatomy courses that combine dissection, radiological images and clinical application would seem desirable.

• Kim, Jeong-Yeon; Manna, Dipankar; Etscheid, Michael; Leergaard, Trygve Brauns & Kanse, Sandip (2022). Factor VII activating protease (FSAP) inhibits the outcome of ischemic stroke in mouse models. The FASEB Journal. ISSN 0892-6638. 36(10). doi: 10.1096/fj.202200828r. Full text in Research Archive Show summary

  The outcome of ischemic stroke can be improved by further refinements of thrombolysis and reperfusion strategies. Factor VII activating protease (FSAP) is a circulating serine protease that could be important in this context. Its levels are raised in patients as well as mice after stroke and a single nucleotide polymorphism (SNP) in the coding sequence, which results in an inactive enzyme, is linked to an increased risk of stroke. In vitro, FSAP cleaves fibrinogen to promote fibrinolysis, activates protease-activated receptors, and decreases the cellular cytotoxicity of histones. Based on these facts, we hypothesized that FSAP can be used as a treatment for ischemic stroke. A combination of tissue plasminogen activator (tPA), a thrombolytic drug, and recombinant serine protease domain of FSAP (FSAP-SPD) improved regional cerebral perfusion and neurological outcome and reduced infarct size in a mouse model of thromboembolic stroke. FSAP-SPD also improved stroke outcomes and diminished the negative consequences of co-treatment with tPA in the transient middle cerebral artery occlusion model of stroke without altering cerebral perfusion. The inactive MI-isoform of FSAP had no impact in either model. FSAP enhanced the lysis of blood clots in vitro, but in the tail transection model of hemostasis, FSAP-SPD treatment provoked a faster clotting time indicating that it also has pro-coagulant actions. Thus, apart from enhancing thrombolysis, FSAP has multiple effects on stroke progression and represents a promising novel therapeutic strategy in the treatment of ischemic stroke.

• Tocco, Chiara; Øvsthus, Martin; Bjaalie, Jan G.; Leergaard, Trygve B. & Studer, Michèle (2022). The topography of corticopontine projections is controlled by postmitotic expression of the area-mapping gene Nr2f1. Development. ISSN 0950-1991. 149(5). doi: 10.1242/dev.200026. Full text in Research Archive Show summary

  ABSTRACT 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. By 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.

• Bjerke, Ingvild Elise; Cullity, E. R.; Kjelsberg, Kasper; Charan, K M; Leergaard, Trygve B. & Kim, J. H. (2022). DOPAMAP, high-resolution images of dopamine 1 and 2 receptor expression in developing and adult mouse brains. Scientific Data. 9, p. 1–11. doi: 10.1038/s41597-022-01268-8. Full text in Research Archive Show summary

  Abstract The dopaminergic system undergoes major reorganization during development, a period especially vulnerable to mental disorders. Forebrain neurons expressing dopamine 1 and 2 receptors (D1R and D2R, respectively) play a key role in this system. However, neuroanatomical information about the typical development of these neurons is sparse and scattered across publications investigating one or a few brain regions. We here present a public online collection of microscopic images of immunohistochemically stained serial sections from male and female mice at five stages of development (postnatal day 17 (P17), P25, P35, P49, and adult), showing the distribution of D1R and D2R expressing neurons across the forebrain. All images from adult brains are registered to the Allen Mouse brain Common Coordinate Framework, while images from P17-P35 age groups are registered to spatially modified atlas versions matching the morphology of young brains. This online resource provides microscopic visualization of the developing dopaminergic system in mice, which is suitable as a benchmark reference for performing new experiments and building computational models of the brain.

• Abrams, Mathew Birdsall; Bjaalie, Jan G.; Das, Samir; Egan, Gary F.; Ghosh, Satrajit S. & Goscinski, Wojtek J. [Show all 23 contributors for this article] (2021). A Standards Organization for Open and FAIR Neuroscience: the International Neuroinformatics Coordinating Facility. Neuroinformatics. ISSN 1539-2791. doi: 10.1007/s12021-020-09509-0. Full text in Research Archive Show summary

  Abstract There is great need for coordination around standards and best practices in neuroscience to support efforts to make neuroscience a data-centric discipline. Major brain initiatives launched around the world are poised to generate huge stores of neuroscience data. At the same time, neuroscience, like many domains in biomedicine, is confronting the issues of transparency, rigor, and reproducibility. Widely used, validated standards and best practices are key to addressing the challenges in both big and small data science, as they are essential for integrating diverse data and for developing a robust, effective, and sustainable infrastructure to support open and reproducible neuroscience. However, developing community standards and gaining their adoption is difficult. The current landscape is characterized both by a lack of robust, validated standards and a plethora of overlapping, underdeveloped, untested and underutilized standards and best practices. The International Neuroinformatics Coordinating Facility (INCF), an independent organization dedicated to promoting data sharing through the coordination of infrastructure and standards, has recently implemented a formal procedure for evaluating and endorsing community standards and best practices in support of the FAIR principles. By formally serving as a standards organization dedicated to open and FAIR neuroscience, INCF helps evaluate, promulgate, and coordinate standards and best practices across neuroscience. Here, we provide an overview of the process and discuss how neuroscience can benefit from having a dedicated standards body.

• Syverstad, Gry-Helen Enger; Melbye, Christoffer; Puchades, Maja; Leung, Siu Yi Doreen; Jacobsen, Øyvind & Shreyas, Rao [Show all 9 contributors for this article] (2021). Cerebral Amyloid Angiopathy in a Mouse Model of Alzheimer’s Disease Associates with Upregulated Angiopoietin and Downregulated Hypoxia-Inducible Factor. Journal of Alzheimer's Disease. ISSN 1387-2877. 83(4), p. 1651–1663. doi: 10.3233/JAD-210571. Full text in Research Archive Show summary

  Background: Vascular pathology is a common feature in patients with advanced Alzheimer’s disease, with cerebral amyloid angiopathy (CAA) and microvascular changes commonly observed at autopsies and in genetic mouse models. However, despite a plethora of studies addressing the possible impact of CAA on brain vasculature, results have remained contradictory, showing reduced, unchanged, or even increased capillary densities in human and rodent brains overexpressing amyloid-β in Alzheimer’s disease and Down’s syndrome. Objective: We asked if CAA is associated with changes in angiogenetic factors or receptors and if so, whether this would translate into morphological alterations in pericyte coverage and vessel density. Methods: We utilized the transgenic mice carrying the Arctic (E693G) and Swedish (KM670/6701NL) amyloid precursor protein which develop severe CAA in addition to parenchymal plaques. Results: The main finding of the present study was that CAA in Tg-ArcSwe mice is associated with upregulated angiopoietin and downregulated hypoxia-inducible factor. In the same mice, we combined immunohistochemistry and electron microscopy to quantify the extent of CAA and investigate to which degree vessels associated with amyloid plaques were pathologically affected. We found that despite a severe amount of CAA and alterations in several angiogenetic factors in Tg-ArcSwe mice, this was not translated into significant morphological alterations like changes in pericyte coverage or vessel density. Conclusion: Our data suggest that CAA does not impact vascular density but might affect capillary turnover by causing changes in the expression levels of angiogenetic factors.

• Bjerke, Ingvild Elise; Yates, Sharon Christine; Laja, Arthur; Witter, Menno; Puchades, Maja & Bjaalie, Jan G. [Show all 7 contributors for this article] (2020). Densities and numbers of calbindin and parvalbumin positive neurons across the rat and mouse brain. iScience. 24:101906(1), p. 1–52. doi: 10.1016/j.isci.2020.101906. Full text in Research Archive Show summary

  The calcium-binding proteins parvalbumin and calbindin are expressed in neuronal populations regulating brain networks involved in spatial navigation, memory processes, and social interactions. Information about the numbers of these neurons across brain regions is required to understand their functional roles but is scarcely available. Employing semi-automated image analysis, we performed brain-wide analysis of immunohistochemically stained parvalbumin and calbindin sections and show that these neurons distribute in complementary patterns across the mouse brain. Parvalbumin neurons dominate in areas related to sensorimotor processing and navigation, whereas calbindin neurons prevail in regions reflecting behavioral states. We also find that parvalbumin neurons distribute according to similar principles in the hippocampal region of the rat and mouse brain. We validated our results against manual counts and evaluated variability of results among researchers. Comparison of our results to previous reports showed that neuron numbers vary, whereas patterns of relative densities and numbers are consistent.

• Bjerke, Ingvild Elise; Puchades, Maja; Bjaalie, Jan G. & Leergaard, Trygve B. (2020). Database of literature derived cellular measurements from the murine basal ganglia. Scientific Data. 7. doi: 10.6084/m9.figshare.12199088. Full text in Research Archive
• Mascaro, A. L. Allegra; Falotico, E.; Petkosi, S.; Pasquini, M.; Vannucci, L. & Tort-Colet, N. [Show all 23 contributors for this article] (2020). Experimental and Computational Study on Motor Control and Recovery After Stroke: Toward a Constructive Loop Between Experimental and Virtual Embodied Neuroscience. Frontiers in Systems Neuroscience. 14. doi: 10.3389/fnsys.2020.00031. Full text in Research Archive Show summary

  Being able to replicate real experiments with computational simulations is a unique opportunity to refine and validate models with experimental data and redesign the experiments based on simulations. However, since it is technically demanding to model all components of an experiment, traditional approaches to modeling reduce the experimental setups as much as possible. In this study, our goal is to replicate all the relevant features of an experiment on motor control and motor rehabilitation after stroke. To this aim, we propose an approach that allows continuous integration of new experimental data into a computational modeling framework. First, results show that we could reproduce experimental object displacement with high accuracy via the simulated embodiment in the virtual world by feeding a spinal cord model with experimental registration of the cortical activity. Second, by using computational models of multiple granularities, our preliminary results show the possibility of simulating several features of the brain after stroke, from the local alteration in neuronal activity to long-range connectivity remodeling. Finally, strategies are proposed to merge the two pipelines. We further suggest that additional models could be integrated into the framework thanks to the versatility of the proposed approach, thus allowing many researchers to achieve continuously improved experimental design.

• Yates, Sharon Christine; Groeneboom, Nicolaas Ervik; Coello, Christopher; Lichtenthaler, Stefan F.; Kuhn, Peer-Hendrik & Demuth, Hans-Ulrich [Show all 12 contributors for this article] (2019). QUINT: Workflow for Quantification and Spatial Analysis of Features in Histological Images From Rodent Brain. Frontiers in Neuroinformatics. 13. doi: 10.3389/fninf.2019.00075. Full text in Research Archive Show summary

  Transgenic animal models are invaluable research tools for elucidating the pathways and mechanisms involved in the development of neurodegenerative diseases. Mechanistic clues can be revealed by applying labelling techniques such as immunohistochemistry or in situ hybridisation to brain tissue sections. Precision in both assigning anatomical location to the sections and quantifying labelled features is crucial for output validity, with a stereological approach or image-based feature extraction typically used. However, both approaches are restricted by the need to manually delineate anatomical regions. To circumvent this limitation, we present the QUINT workflow for quantification and spatial analysis of labelling in series of rodent brain section images based on available 3D reference atlases. The workflow is semi-automated, combining three open source software that can be operated without scripting knowledge, making it accessible to most researchers. As an example, a brain region-specific quantification of amyloid plaques across whole transgenic Tg2576 mouse brain series, immunohistochemically labelled for three amyloid-related antigens is demonstrated. First, the whole brain image series were registered to the Allen Mouse Brain Atlas to produce customised atlas maps adapted to match the cutting plan and proportions of the sections (QuickNII software). Second, the labelling was segmented from the original images by the Random Forest Algorithm for supervised classification (ilastik software). Finally, the segmented images and atlas maps were used to generate plaque quantifications for each region in the reference atlas (Nutil software). The method yielded comparable results to manual delineations and to the output of a stereological method. While the use case demonstrates the QUINT workflow for quantification of amyloid plaques only, the workflow is suited to all mouse or rat brain series with labelling that is visually distinct from the background, for example for the quantification of cells or labelled proteins.

• Osen, Kirsten Kjelsberg; Imad, Jala; Wennberg, Arvind Eirik; Papp, Eszter Agnes & Leergaard, Trygve Brauns (2019). Waxholm Space atlas of the rat brain auditory system: Three-dimensional delineations based on structural and diffusion magnetic resonance imaging. NeuroImage. ISSN 1053-8119. 199, p. 38–56. doi: 10.1016/j.neuroimage.2019.05.016. Full text in Research Archive Show summary

  The mammalian auditory system comprises a complex network of brain regions. Interpretations and comparisons of experimental results from this system depend on appropriate anatomical identification of auditory structures. The Waxholm Space (WHS) atlas of the Sprague Dawley rat brain (Papp et al., Neuroimage 97:374-86, 2014) is an open access, three-dimensional reference atlas defined in an ex-vivo magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) volume. Version 2.0 of the atlas (Kjonigsen et al., Neuroimage 108:441-9, 2015) includes detailed delineations of the hippocampus and several major subcortical regions, but only few auditory structures. To amend this, we have delineated the complete ascending auditory system from the cochlea to the cerebral cortex. 40 new brain structure delineations have been added, and the delineations of 10 regions have been revised based on the interpretation of image features in the WHS rat brain MRI/DTI volumes. We here describe and validate the new delineations in relation to corresponding cell- and myelin-stained histological sections and previous literature. We found it possible to delineate all main regions and the majority of subregions and fibre tracts of the ascending auditory pathway, apart from the auditory cortex, for which delineations were extrapolated from a conventional two-dimensional atlas. By contrast, only parts of the descending pathways were discernible in the template. Version 3.0 of the atlas, with altogether 118 anatomical delineations, is shared via the NeuroImaging Tools and Resources Collaboratory (www.nitrc.org).

• Puchades, Maja; Csúcs, Gergely; Ledergerber, Debora; Leergaard, Trygve B. & Bjaalie, Jan G. (2019). Spatial registration of serial microscopic brain images to three-dimensional reference atlases with the QuickNII tool. PLOS ONE. 14(5). doi: 10.1371/journal.pone.0216796. Full text in Research Archive Show summary

  Modern high throughput brain wide profiling techniques for cells and their morphology, connectivity, and other properties, make the use of reference atlases with 3D coordinate frameworks essential. However, anatomical location of observations made in microscopic sectional images from rodent brains is typically determined by comparison with 2D anatomical reference atlases. A major challenge in this regard is that microscopic sections often are cut with orientations deviating from the standard planes used in the reference atlases, resulting in inaccuracies and a need for tedious correction steps. Overall, efficient tools for registration of large series of section images to reference atlases are currently not widely available. Here we present QuickNII, a stand-alone software tool for semi-automated affine spatial registration of sectional image data to a 3D reference atlas coordinate framework. A key feature in the tool is the capability to generate user defined cut planes through the reference atlas, matching the orientation of the cut plane of the sectional image data. The reference atlas is transformed to match anatomical landmarks in the corresponding experimental images. In this way, the spatial relationship between experimental image and atlas is defined, without introducing distortions in the original experimental images. Following anchoring of a limited number of sections containing key landmarks, transformations are propagated across the entire series of sectional images to reduce the amount of manual steps required. By having coordinates assigned to the experimental images, further analysis of the distribution of features extracted from the images is greatly facilitated.

• Lillehaug, Sveinung; Yetman, Michael J.; Puchades, Maja; Checinska, Martyna; Kleven, Heidi & Jankowsky, Joanna L. [Show all 8 contributors for this article] (2019). Data Descriptor: Brain-wide distribution of reporter expression in five transgenic tetracyclinetransactivator mouse lines. Scientific Data. 6, p. 1–15. doi: 10.1038/sdata.2019.28. Full text in Research Archive
• Post, Joakim Iver; Leergaard, Trygve B.; Ratz, Veronika; Walaas, S. Ivar; Hörsten, Stephan von & Nissen-Meyer, Lise Sofie Haug (2019). Differential Levels and Phosphorylation of Type 1 Inositol 1,4,5-Trisphosphate Receptor in Four Different Murine Models of Huntington Disease. Journal of Huntington's Disease. ISSN 1879-6397. 8(3), p. 271–289. doi: 10.3233/JHD-180301. Full text in Research Archive
• Mughal, Awais; Zhang, Lili; Fayzullin, Artem; Server, Andrés; Li, Yuping & Wu, Yingxi [Show all 11 contributors for this article] (2018). Patterns of Invasive Growth in Malignant Gliomas - The Hippocampus Emerges as an Invasion-Spared Brain Region. Neoplasia. ISSN 1522-8002. 20(7), p. 643–656. doi: 10.1016/j.neo.2018.04.001. Full text in Research Archive Show summary

  BACKGROUND: Widespread infiltration of tumor cells into surrounding brain parenchyma is a hallmark of malignant gliomas, but little data exist on the overall invasion pattern of tumor cells throughout the brain. METHODS: We have studied the invasive phenotype of malignant gliomas in two invasive mouse models and patients. Tumor invasion patterns were characterized in a patient-derived xenograft mouse model using brain-wide histological analysis and magnetic resonance (MR) imaging. Findings were histologically validated in a cdkn2a−/− PDGF-β lentivirus-induced mouse glioblastoma model. Clinical verification of the results was obtained by analysis of MR images of malignant gliomas. RESULTS: Histological analysis using human-specific cellular markers revealed invasive tumors with a non-radial invasion pattern. Tumors cells accumulated in structures located far from the transplant site, such as the optic white matter and pons, whereas certain adjacent regions were spared. As such, the hippocampus was remarkably free of infiltrating tumor cells despite the extensive invasion of surrounding regions. Similarly, MR images of xenografted mouse brains displayed tumors with bihemispheric pathology, while the hippocampi appeared relatively normal. In patients, most malignant temporal lobe gliomas were located lateral to the collateral sulcus. Despite widespread pathological fluid-attenuated inversion recovery signal in the temporal lobe, 74% of the “lateral tumors” did not show signs of involvement of the amygdalo-hippocampal complex. CONCLUSIONS: Our data provide clear evidence for a compartmental pattern of invasive growth in malignant gliomas. The observed invasion patterns suggest the presence of preferred migratory paths, as well as intra-parenchymal boundaries that may be difficult for glioma cells to traverse supporting the notion of compartmental growth. In both mice and human patients, the hippocampus appears to be a brain region that is less prone to tumor invasion.

• Bjerke, Ingvild Elise; Øvsthus, Martin; Andersson, Krister Andreas; Blixhavn, Camilla Hagen; Kleven, Heidi & Yates, Sharon Christine [Show all 9 contributors for this article] (2018). Navigating the Murine Brain: Toward Best Practices for Determining and Documenting Neuroanatomical Locations in Experimental Studies. Frontiers in Neuroanatomy. 12. doi: 10.3389/fnana.2018.00082. Full text in Research Archive Show summary

  In experimental neuroscientific research, anatomical location is a key attribute of experimental observations and critical for interpretation of results, replication of findings, and comparison of data across studies. With steadily rising numbers of publications reporting basic experimental results, there is an increasing need for integration and synthesis of data. Since comparison of data relies on consistently defined anatomical locations, it is a major concern that practices and precision in the reporting of location of observations from different types of experimental studies seem to vary considerably. To elucidate and possibly meet this challenge, we have evaluated and compared current practices for interpreting and documenting the anatomical location of measurements acquired from murine brains with different experimental methods. Our observations show substantial differences in approach, interpretation and reproducibility of anatomical locations among reports of different categories of experimental research, and strongly indicate that ambiguous reports of anatomical location can be attributed to missing descriptions. Based on these findings, we suggest a set of minimum requirements for documentation of anatomical location in experimental murine brain research. We furthermore demonstrate how these requirements have been applied in the EU Human Brain Project to optimize workflows for integration of heterogeneous data in common reference atlases. We propose broad adoption of some straightforward steps for improving the precision of location metadata and thereby facilitating interpretation, reuse and integration of data.

• Bjerke, Ingvild Elise; Øvsthus, Martin; Papp, Eszter Agnes; Yates, Sharon Christine; Silvestri, L & Fiorilli, J [Show all 11 contributors for this article] (2018). Data integration through brain atlasing: Human Brain Project tools and strategies. European psychiatry. ISSN 0924-9338. 50, p. 70–76. doi: 10.1016/j.eurpsy.2018.02.004. Full text in Research Archive Show summary

  The Human Brain Project (HBP), an EU Flagship Initiative, is currently building an infrastructure that will allow integration of large amounts of heterogeneous neuroscience data. The ultimate goal of the project is to develop a unified multi-level understanding of the brain and its diseases, and beyond this to emulate the computational capabilities of the brain. Reference atlases of the brain are one of the key components in this infrastructure. Based on a new generation of three-dimensional (3D) reference atlases, new solutions for analyzing and integrating brain data are being developed. HBP will build services for spatial query and analysis of brain data comparable to current online services for geospatial data. The services will provide interactive access to a wide range of data types that have information about anatomical location tied to them. The 3D volumetric nature of the brain, however, introduces a new level of complexity that requires a range of tools for making use of and interacting with the atlases. With such new tools, neuroscience research groups will be able to connect their data to atlas space, share their data through online data systems, and search and find other relevant data through the same systems. This new approach partly replaces earlier attempts to organize research data based only on a set of semantic terminologies describing the brain and its subdivisions.

• Stahl, Katja; Rahmani, Soulmaz; Prydz, Agnete; Skauli, Nadia; MacAulay, Nanna & Mylonakou, Maria-Niki [Show all 13 contributors for this article] (2018). Targeted deletion of the aquaglyceroporin AQP9 is protective in a mouse model of Parkinson's disease. PLOS ONE. 13(3). doi: 10.1371/journal.pone.0194896. Full text in Research Archive Show summary

  More than 90% of the cases of Parkinson’s disease have unknown etiology. Gradual loss of dopaminergic neurons of substantia nigra is the main cause of morbidity in this disease. External factors such as environmental toxins are believed to play a role in the cell loss, although the cause of the selective vulnerability of dopaminergic neurons remains unknown. We have previously shown that aquaglyceroporin AQP9 is expressed in dopaminergic neurons and astrocytes of rodent brain. AQP9 is permeable to a broad spectrum of substrates including purines, pyrimidines, and lactate, in addition to water and glycerol. Here we test our hypothesis that AQP9 serves as an influx route for exogenous toxins and, hence, may contribute to the selective vulnerability of nigral dopaminergic (tyrosine hydroxylase-positive) neurons. Using Xenopus oocytes injected with Aqp9 cRNA, we show that AQP9 is permeable to the parkinsonogenic toxin 1-methyl-4-phenylpyridinium (MPP+). Stable expression of AQP9 in HEK cells increases their vulnerability to MPP+ and to arsenite—another parkinsonogenic toxin. Conversely, targeted deletion of Aqp9 in mice protects nigral dopaminergic neurons against MPP+ toxicity. A protective effect of Aqp9 deletion was demonstrated in organotypic slice cultures of mouse midbrain exposed to MPP+ in vitro and in mice subjected to intrastriatal injections of MPP+ in vivo. Seven days after intrastriatal MPP+ injections, the population of tyrosine hydroxylase-positive cells in substantia nigra is reduced by 48% in Aqp9 knockout mice compared with 67% in WT littermates. Our results show that AQP9 –selectively expressed in catecholaminergic neurons—is permeable to MPP+ and suggest that this aquaglyceroporin contributes to the selective vulnerability of nigral dopaminergic neurons by providing an entry route for parkinsonogenic toxins. To our knowledge this is the first evidence implicating a toxin permeable membrane channel in the pathophysiology of Parkinson’s disease.

View all works in NVA

• Golla, Archana; Pieschnik, Sophia; Kobchenko, Maya; Reiten, Ingrid; Chatzopoulos, Serafeim & Rojas, César Parra [Show all 16 contributors for this article] (2026). Building an Integrated Scientific Knowledge Graph for Neuroscience: Enhancing Research Impact Analysis and Optimizing Data Curation. doi: 10.5281/ZENODO.18864403. Full text in Research Archive Show summary

  The Neuroscience pilot of the EU-funded SciLake project seeks to tackle the complexities of fragmented and disorganized open research data. This initiative has united partners with expertise in knowledge management with curators from EBRAINS (RRID: SCR_019260), an open research infrastructure focused on brain-related studies. The innovative Scientific Knowledge Graph (SKG) (https://bip.imsi.athenarc.gr/search/neuroscience-pilot) created through this pilot serves as a cohesive framework for data integration while enabling the use of value-added services provided by SciLake. The developed SKG combines curated datasets from EBRAINS with extensive neuroscience research products from the OpenAIRE neuroscience gateway (https://neuroscience.openaire.eu/). The SKG incorporates controlled terms from openMINDS (RRID: SCR_023173) as nodes and utilizes an entity recognition model to classify and map these terms in relevant texts, enriching the connections among research products. Additionally, the SciLake services deploy language models to extract mentions of research artifacts (RAs) and enhance the interlinking of research products. Fully integrated with impact-driven discovery and reproducibility tools and leveraging the analytical capabilities of SciLake, the SKG serves as a powerful resource for contextualizing curation efforts and exploring research trends, ultimately optimizing curation processes in the neuroscientific landscape.

• Pieschnik, Sophia; Benediktsdottir, Signy; Karadag, Naz; Papp, Eszter Agnes; Puchades, Maja & Leergaard, Trygve B. [Show all 7 contributors for this article] (2026). Digital data collections for discovery-driven neuroscience. doi: https:/fens2026.abstractserver.com/program/#%2Fdetails%2Fpresentations%2F4724. Full text in Research Archive Show summary

  The transition to open science has led to a growing volume of shared neuroscience data in different data repositories. While the amount and diversity of research data available is extensive, data reusability is often limited by a lack of appropriate metadata annotations according to the FAIR guiding principles (Wilkinson et al., 2016). The EBRAINS Research Infrastructure (RRID:SCR_019260) shares well-annotated datasets to facilitate data discovery and reuse across studies and modalities via the EBRAINS Knowledge Graph (KG; RRID:SCR_017612). The EBRAINS KG currently indexes 1100+ heterogeneous datasets, annotated with standardised metadata following the openMINDS metadata framework (RRID:SCR_023173). We present two examples for building data collections via the KG Search functionality using a combination of multi-term text queries and faceted filtering to exemplify the potential of data driven workflows. First, we explore the brain-wide distribution of calbindin- and parvalbumin-positive neurons in rodent brains, identifying a comprehensive data collection generated using the QUINT workflow (Yates et al., 2019). Related datasets are connected through metadata including species and techniques. Second, we collect BIDS-compliant macaque datasets, containing NIfTI files, enabling the combination of neuroimaging data from different laboratories. Filtering and query options for experimental methods, content types and data organisation standards enable the selection of data for viewing and analysis using EBRAINS tools, highlighting their interoperability. These examples demonstrate how discovery-driven neuroscience is facilitated by FAIR annotated data across a range of studies.

• Balkir, Arda; Yates, Sharon Christine; Csucs, Gergely; Leergaard, Trygve B.; Puchades, Maja & Bjaalie, Jan G. (2026). QUINT-ONLINE WORKFLOW: PERSONALISED WORKING ENVIRONMENT FOR ATLAS-BASED ANALYSES OF BRAIN SECTION IMAGES IN RODENTS. doi: https:/fens2026.abstractserver.com/program/#%2Fdetails%2Fpresentations%2F4213. Full text in Research Archive Show summary

  Studies of the cellular architecture and neural connections in the brain often rely on histology-based methods in rodent wild type and disease models. Registration of brain section images to a reference brain atlas has become the standard for obtaining high quality and precise data, allowing comparison and integration of disparate data within a standardised coordinate system. While a few analytical tools are available to researchers, barriers to uptake, such as coding skill requirements, data type limitations, and insufficient documentation are still present. We have developed an intuitive, reliable and versatile solution for enabling such analyses. The QUINT-online workflow combines the use of a series of web-applications (CreateZoom, WebAlign, WebWarp, Webilastik, WebNutil and MeshView) integrated in an online platform, accessible with an EBRAINS account. It builds on the QUINT workflow (Yates et al. 2019, doi: 10.3389/fninf.2019.00075) using desktop applications, which has been used widely by the research community for cell counting, tract tracing studies and for analysis of tissue clearing data. This new online solution allows researchers to register heterogeneous image series to reference brain atlases, to identify features to quantify, and to perform brain-wide mapping and quantification, on a user-friendly platform. The QUINT-online workflow benefits from simplified file management steps and new features such as microscopy viewer links and automated mapping of selected objects. EBRAINS users can already access a beta version at https://quint-online.apps.ebrains.eu/.

• Morabit, Oumnia; Kleven, Heidi; Giacometti, Camille; Palomero-Gallagher, Nicola & Leergaard, Trygve B. (2026). Anatomical subdivisions of the rat amygdaloid complex: an empirical basis for unifying MRI, DTI and histology-based boundary criteria in the Waxholm Space rat brain atlas. Full text in Research Archive Show summary

  The amygdaloid complex is part of the limbic system governing emotion, learning, implicit memory and social behaviour. Its implication in neuropsychiatric disease has motivated extensive experimental preclinical research in animal models, particularly in rodents and non-human primates. For investigations in rat models, the Waxholm Space (WHS) rat brain atlas provides three-dimensional standardized representations of brain regions and is increasingly used for data integration, spatial analysis, and comparisons across studies. While this atlas includes detailed delineations for most major brain structures, it lacks subdivisions of the amygdaloid complex. Addressing this, we have manually delineated nuclei of the rat amygdala on the basis of high-resolution structural magnetic resonance imaging (sMRI) and diffusion tensor imaging (DTI) data, combined with co-registered cytoarchitectural, myeloarchitectural, and chemoarchitectural features derived from histological datasets. These multimodal data were interpreted and compared using available literature. We here present 3D delineations of the rat pallial and subpallial subdivisions of the amygdaloid complex, together with detailed documentation of delineation criteria. To facilitate cross-species translation, we also compared our delineation criteria and delineations to corresponding data from primates. This work represents an empirical basis for combining multimodal MRI and histological data to extend the anatomical delineations of the WHS rat brain atlas and to strengthen its role as a neuroinformatics resource for data integration, translational research, brain wide analyses and cross-species comparison particularly for future investigations into the neural mechanisms involving the amygdaloid complex. Funded from the European Union’s Research and Innovation Program Horizon Grant Agreement No. 101147319 (EBRAINS 2.0)

• Pieschnik, Sophia; Najafi, Peyman; Pernet, Cyril; Bjaalie, Jan G.; Leergaard, Trygve B. & Davison, Andrew [Show all 7 contributors for this article] (2025). bids2openminds: facilitating automated conversion between neuroscience data standards. Full text in Research Archive Show summary

  BIDS and openMINDS are expert- and community-driven standards that facilitate FAIR data management in the field of neuroscience. BIDS is a commonly adopted data model that standardizes the file organization and metadata annotations per dataset within a data repository, such as openNeuro.org or publicneuro.eu. The openMINDS metadata framework provides integrated metadata models for Linked Data, libraries of ontology-based metadata instances and supports rich search capabilities in graph database systems, such as the EBRAINS Knowledge Graph. To facilitate ingestion of metadata from BIDS datasets into such graph database systems, we developed the bids2openminds converter. bids2openminds is an open-source project, provided as a python package with a command line interface (https://github.com/openMetadataInitiative/bids2openminds). It builds on the functionalities of, pyBIDS and openMINDS_Python. However semantic mapping between BIDS and openMINDS terminologies had to be hard coded. Currently, the converter supports the BIDS modalities structural and functional Magnetic Resonance Imaging (MRI), Electroencephalography (EEG), and Intracranial Electroencephalography (iEEG). We demonstrate the metadata conversion using bids2openminds on BIDS compliant, open access datasets. Converted to openMINDS and registered in the EBRAINS Knowledge Graph, data and metadata have an increased findability via the search user interface and advanced query options. Through the semantic integration data are linked to other datasets within and beyond the EBRAINS database, increasing their interoperability and reusability. The bids2openminds converter facilitates automatic registration of BIDS compliant datasets in openMINDS-based graph databases, fostering interoperability and alliances across different data management systems (e.g., publicneuro.eu and EBRAINS).

• Schilling, Kurt G.; Grussu, Francesco; Ianus, Andrada; Hansen, Brian; Howard, Amy F.D. & Barrett, Rachel L.C. [Show all 58 contributors for this article] (2025). Considerations and recommendations from the ISMRM diffusion study group for preclinical diffusion MRI: Part 2—Ex vivo imaging: Added value and acquisition. Magnetic Resonance in Medicine. ISSN 0740-3194. 93(6), p. 2535–2560. doi: 10.1002/mrm.30435. Full text in Research Archive
• Puchades, Maja; Bjerke, Ingvild Elise; Carey, Harry Alexander Chandler; Kleven, Heidi; Øvsthus, Martin & Yates, Sharon Christine [Show all 10 contributors for this article] (2025). QUINT workflow now supports whole brain analysis using the Developmental Mouse Brain Atlas (DeMBA). Full text in Research Archive Show summary

  INTRODUCTION: Three-dimensional, open access digital brain atlases are important resources in neuroscience research, opening new possibilities for automated analyses in atlas defined regions of interest. The EBRAINS QUINT workflow [1,2] has been developed to support standardized atlas-based analysis of sectioned tissue without the need for coding ability. It features integrated brain atlases for the adult rat and mouse brain and is increasingly used in the neuroscience community. However, a recurrent request from many QUINT users interested in understanding brain development, has been to include brain atlases representing different developmental ages, to so achieve better spatial registration for brains from young individuals. METHODS: To meet this need, we have now integrated the novel Developmental Mouse Brain Atlas (DeMBA), a four-dimensional atlas covering every postnatal day from 4 to 56 [3]. This atlas features segmentations from the widely adopted Allen Mouse Brain CCF and the Kim developmental atlases, that have been transformed and interpolated to the same ages, ensuring comparable region definitions across ages [4]. RESULTS AND DISCUSSION: The DeMBA atlas was implemented in the registration software QuickNII and VisuAlign and shared as specific packages together with the atlas itself on EBRAINS [4]. Those versions require usage of the specific Filebuilder utility shared within the packages. Next, the DeMBA atlas was implemented in a new Nutil Quantifier version (v1.1) and thereby the complete QUINT analysis can now be performed on young mouse brains. All the software tools and the DeMBA atlas are shared through the EBRAINS Knowledge graph [5]. We here present the updated QUINT workflow and give examples of preliminary developmental data analysis. References: 1.Yates, S. et al. (2019) QUINT: Workflow for Quantification and Spatial Analysis of Features in Histological Images From Rodent Brain. Front. Neuroinform. 13, 1–14. https://doi.org/10.3389/fninf.2019.00075 2. Puchades MA, Yates SC, Csucs G, Carey H, Balkir A, Leergaard TB and Bjaalie JG (2025) Software and pipelines for registration and analyses of rodent brain image data in reference atlas space. Front. Neuroinform. 19:1629388. https://doi.org/10.3389/fninf.2025.1629388 3.Carey, H., Ovsthus, M., Kleven, H., Yates, S. C., Csucs, G., Puchades, M. A., Bjaalie, J. G., Leergaard, T. B., & Bjerke, I. E. (2024). Developmental mouse brain atlas (DeMBA) with continuous coverage of postnatal day 4 to 56 (v1) [Data set]. EBRAINS. https://doi.org/10.25493/V3AH-HK7 4.Carey, H., Kleven, H., Øvsthus, M. et al. DeMBA: a developmental atlas for navigating the mouse brain in space and time. Nat Commun 16, 8108 (2025). https://doi.org/10.1038/s41467-025-63177-9 5.https://search.kg.ebrains.eu Acknowledgeme

• Blackstad, Jan Sigurd Beddari; Osen, Kirsten; Storm-Mathisen, Jon & Leergaard, Trygve Brauns (2025). The Evolutionary Reorganization of the Dentate Gyrus and CA3 in an Ontogenetic Perspective. Full text in Research Archive
• Benediktsdottir, Signy; Golla, Archana; Blixhavn, Camilla Hagen; Hennestad, Eivind; Kleven, Heidi & Najafi, Peyman [Show all 16 contributors for this article] (2024). Towards FAIR neuroscience: an efficient workflow for sharing and integrating data. Full text in Research Archive
• Pieschnik, Sophia; Najafi, Peyman; Bjaalie, Jan G.; Leergaard, Trygve Brauns; Davison, Andrew P. & Zehl, Lyuba (2024). Automated conversion of BIDS datasets to Linked Data using openMINDS. Full text in Research Archive
• Zehl, Lyuba; Pieschnik, Sophia; Najafi, Peyman; Bjaalie, Jan G.; Leergaard, Trygve Brauns & Davison, Andrew P. (2024). bids2openminds: extracting linked data from brain imaging data structures. Full text in Research Archive
• Kleven, Heidi; Øvsthus, Martin; Carey, Harry Alexander Chandler; Puchades, Maja; Bjaalie, Jan G. & Leergaard, Trygve B. [Show all 7 contributors for this article] (2024). Three-dimensional reference atlases for integration and analysis of data from the postnatal mouse brain. Full text in Research Archive
• Reiten, Ingrid; Olsen, Grete; Bjaalie, Jan G.; Witter, Menno Peter & Leergaard, Trygve B. (2023). The efferent connections of the orbitofrontal, posterior parietal and insular cortices in the rat: FAIR tract tracing data enabled by EBRAINS. Full text in Research Archive Show summary

  Poster presenterer et datasett som er delt via EBRAINS (ebrains.eu). Datasettet inneholder bildemateriale av koronale rottehjernesnitt som er merket for anterograd tracer, samt en registerering av disse bildene til Waxholm Space Rat Brain v4 atlas. Dataene er delt i følge FAIR-prinsippene og er open access.

• Blixhavn, Camilla Hagen; Bjerke, Ingvild Elise; Reiten, Ingrid; Kleven, Heidi; Schlegel, Ulrike & Puchades, Maja [Show all 8 contributors for this article] (2023). A conceptual framework for positioning and integrating brain data in murine 3D brain atlases. Full text in Research Archive
• Pieschnik, Sophia; Golla, Archana; Reiten, Ingrid; Schlegel, Ulrike; Hennestad, Eivind & Hübenette, Saira Jameela [Show all 20 contributors for this article] (2023). Pioneering open neuroscience - the role of the curation services. Full text in Research Archive
• Bjerke, Ingvild Elise; Imad, Jala; Clascá, Francisco; Groenewegen, Henk J.; Bjaalie, Jan G. & Leergaard, Trygve Brauns (2022). Waxholm Space atlas of the Sprague Dawley rat brain version 4: A volumetric atlas enabling data integration and analysis. Full text in Research Archive
• Reiten, Ingrid; Schlegel, Ulrike; Aasebø, Ida; Davison, Andrew P.; Zehl, Lyuba & Schmid, Oliver [Show all 10 contributors for this article] (2022). Share FAIR neuroscience data using the EBRAINS curation services. Full text in Research Archive
• Reiten, Ingrid; Schlegel, Ulrike; Aasebø, Ida; Swieten, Maaike M. H. van; Davison, Andrew P. & Zehl, Lyuba [Show all 11 contributors for this article] (2022). Share FAIR neuroscience data using the EBRAINS curation services. Full text in Research Archive
• Puchades, Maja; Reiten, Ingrid; Destexhe, Alain; Palomero-Gallagher, Nicola; Ruikes, Thijs & Leergaard, Trygve B. [Show all 7 contributors for this article] (2022). Workshop: Towards exploration of disease mechanisms in animal models: atlases, analysis, modelling and simulation. Full text in Research Archive Show summary

  Researchers Maja A. Puchades and Prof Jan G. Bjaalie have organised a paralell session titled: "Towards exploration of disease mechanisms in animal models". Agenda: For the 90 min meeting: · Presentation of speakers · New directions in disease models research · EBRAINS atlases enabling animal model research · Tools and analytical workflows for data integration in atlases · Use of animal brain atlases for modelling of brain function · Connectivity rat data: tract-tracing use case · Connectivity rat data: electrophysiological tetrodes use case · Panel discussion

• Øyen, Ole Morten; Spurkland, Anne & Leergaard, Trygve B. (2022). Bedre etterutdanning i anatomi for norske klinikere. Tidsskrift for Den norske legeforening (Tidsskriftet). ISSN 0029-2001. 142(11). doi: 10.4045/tidsskr.22.0350. Full text in Research Archive
• Puchades, Maja; Yates, Sharon Christine; Groeneboom, Nicolaas; Csucs, Gergely; Darine, Dmitri Aleksandrovitsj & Carey, Harry [Show all 8 contributors for this article] (2022). EBRAINS tools for rodent brain atlasing. Full text in Research Archive Show summary

  Research in small animals depends on comparisons of cellular and molecular measures in large groups, requiring efficient and reproducible methods for registration of data to brain atlases followed by quantitative analysis. While numerous methodologies and increasing amounts of data are available, they are difficult to combine into coherent and reproducible workflows suitable for large-scale analyses. The EBRAINS research infrastructure enables neuroscientists to conduct their mouse and rat brain data analyses in an open, robust and user-friendly environment. It provides tools and workflows for viewing images; automatic and user guided registration of brain section image data to an atlas; feature extraction with machine learning, whole brain distribution analysis, and metadata management according to the FAIR principles. We present examples of typical use cases, illustrating how the available suite of tools can be used and the results obtained, with an emphasis on the reproducibility of the methods applied and the sharing of the data and metadata. The tools are part of the EBRAINS Atlases services (https://ebrains.eu/services/atlases) and offer one comprehensive solutions for organizing, analyzing and sharing brain research data. These and other EBRAINS research infrastructure tools and workflows are developed in close interaction with users in the neuroscience community. Funded from EU Horizon 2020, Specific Grant Agreement No. 945539 (Human Brain Project SGA3).

• Schlegel, Ulrike; Köhnen, Stefan; Davison, Andrew; Najafi, Peyman; Weyers, Benjamin & Gründling, Jan [Show all 16 contributors for this article] (2022). openMINDS - flexible metadata models for neuroscience. Full text in Research Archive Show summary

  Enhancing transparency and findability of research data is an emerging theme across scientific disciplines. More and more journals and funders, such as the Research Council of Norway, require the sharing of data in accordance with the FAIR guiding principles (Wilkinson et al., Scientific Data 3:160018, 2016), but few publicly accessible databases achieve this requirement. Their suitability is determined by attributes and constraints of the underlying metadata model. In neuroscience, the heterogeneity of data is particularly challenging. The multimodal nature of the research data as well as the wide range in spatial and temporal scales need to be adequately captured. Therefore, a suitable metadata model for neuroscience data has to balance flexibility and restrictiveness to accommodate the individuality of research products, without diminishing comparability across them. Powered by the Human Brain Project (HBP) and EBRAINS, we present the open Metadata Initiative for Neuroscience Data Structures (openMINDS). This novel initiative develops and maintains interlinked metadata models tailored to describe neuroscience research products in graph databases, such as the EBRAINS Knowledge Graph. The openMINDS research products cover data originating from human, animal or simulation studies (datasets), computational models (models), software tools (software), formal specifications for structuring metadata and/or data (metaDataModels), and reference brain atlases (brainAtlas). To illustrate the power of openMINDS, we present selected features describing these research products. We highlight how respective data and their provenance as well as studied specimens can be captured with user-defined granularity, and how the various integration of data via openMINDS can enhance its comparability and findability within and beyond the EBRAINS Knowledge Graph.

• Bjerke, Ingvild Elise; Cullity, Ellen Rose; Kjelsberg, Kasper; Charan, Kristel; Leergaard, Trygve B. & Kim, Jee Hyun (2022). Map of dopamine 1- and 2-receptor positive cells in the developing mouse forebrain. Full text in Research Archive
• Blixhavn, Camilla Hagen; S., Haug Finn-Mogens; Kleven, Heidi; Puchades, Maja; Bjaalie, Jan G. & Leergaard, Trygve B. (2022). Multiplane microscopic atlas of rat brain zincergic terminal fields and metal-containing glia stained with Timm's sulphide silver method. Full text in Research Archive
• Schlegel, Ulrike; Hjallar, Viktor A.; Lensjø, Kristian; Uggerud, Ida Margrethe; Bjaalie, Jan G. & Hvoslef-Eide, Martha [Show all 8 contributors for this article] (2022). Mapping of parahippocampal and visual neural networks in mice: Preliminary evidence for feedback projections from perirhinal cortex to visual areas. Full text in Research Archive Show summary

  Feedback projections from higher-order processing areas to lower-order areas within the visual system havebeen observed in several species. While much is known about the function of feedforward connections in thevisual processing pathway, feedback connections are not as well studied. They are thought to cause behaviorssuch as (selective) attention or expectations, but the exact mechanism and underlying neural connectivity isstill unknown. The perirhinal cortex (PRH) forms the intersection between perceptual and mnemonic areas ofthe visual processing pathway. Evidence from rats, monkeys and humans suggests that it is involved in bothobject memory and perceptual tasks, which is reflected in its connectivity. PRH forms numerous feedforwardand feedback projections with other areas of the visual processing pathway. However, little is known about thefunction and organization of feedback projections from PRH, and other parahippocampal regions, to visualareas in mice. Given the widespread availability of genetic and molecular tools, novel opportunities toinvestigate the function of these feedback projections would be enabled by mapping them in mice. Here wepresent preliminary data from anterograde and retrograde tract tracing experiments showing feedbackprojections from PRH, and other parahippocampal regions, to visual areas. We have found first evidence forfeedback projections from PRH to lower-order visual areas that were assumed to be exclusive to higher-developed animals such as monkeys or humans. Further, we have identified feedback projections from otherparahippocampal regions with specific subregional distribution.

• Leergaard, Trygve B.; Puchades, Maja; Kleven, Heidi & Bjerke, Ingvild Elise (2022). HBP Brain Matters webinar #12 "Rodent Brain Atlasing". Full text in Research Archive Show summary

  This episode featured the following HBP researchers: Heidi Kleven who is a PhD student at the University of Oslo with a research focus on developing and expanding rat and mouse brain atlases. She presented her ongoing work on brain atlases, focusing on the Waxholm Space atlas of the Sprague Dawley rat brain. Maja Puchades from the University of Oslo presented an overview of EBRAINS tools for analyses of Rodent brain images. A pipeline consisting of several tools allows users to register their images to a reference atlas and perform quantitative analysis in an atlas context. Both standalone and online versions of the tools are now available through the EBRAINS infrastructure. Ingvild Bjerke from the University of Oslo is a postdoctoral researcher. Her research focuses on mapping cellular parameters in the rodent brain, using EBRAINS atlases and tools to perform brain-wide analyses. She presented her published research mapping calbindin- and parvalbumin-positive cells in the rat and mouse brain. The session was moderated by Trygve Leergaard who is a professor of Anatomy at the Institute of Basic Medical Sciences, University of Oslo. His research has been focused on resolving fundamental architectonical principles underlying brain map transformations in major sensorimotor projection systems connecting the cerebral cortex with several brain stem nuclei.

• Bjerke, Ingvild Elise; Leergaard, Trygve B.; Bjaalie, Jan G. & Kim, Jee Hyun (2022). Quantitative map of dopamine 1- and 2-receptor positive cells in the developing mouse forebrain. Full text in Research Archive
• Reiten, Ingrid & Leergaard, Trygve Brauns (2022). Digitisation, sharing and atlas registration of tract tracing histological sections. Full text in Research Archive
• Leergaard, Trygve B.; Bjerke, Ingvild Elise; Bjaalie, Jan G.; Palomero-Gallagher, Nicola; Puchades, Maja & Carey, Harry [Show all 7 contributors for this article] (2022). Neuroscience data integration through use of digital brain atlases. Full text in Research Archive Show summary

  This two-day course will provide a hands-on introduction to three-dimensional reference atlases for the rat and mouse brain, and demonstrate how such atlases can be utilized to integrate and analyze heterogeneous neuroscience data. Students will gain updated knowledge about current approaches to assigning anatomical location to experimental data from the brain, and acquire basic skills in associated analytic tools. Invited speaker Nicola Palomero-Gallagher will give a lecture on neuroanatomy. Jan Bjaalie, Trygve Leergaard and co-workers Camilla Blixhavn, Ingvild Bjerke, Maja Puchades, Sharon Yates and Harry Carey from the Neural Systems Laboratory (University of Oslo) will introduce new concepts for data integration and development of murine brain atlas resources established in context of the European Human Brain Project.

• Schlegel, Ulrike; Köhnen, Stefan; Davison, Andrew P.; Najafi, Peyman; Weyers, Benjamin & Gründling, Jan [Show all 17 contributors for this article] (2021). openMINDS - flexible metadata models for neuroscience. Full text in Research Archive Show summary

  Enhancing transparency and findability of research data is an emerging theme across scientific disciplines. While publicly accessible databases aid in achieving this goal, their suitability is determined by attributes and constraints of the underlying metadata model. In neuroscience, the heterogeneity of data is particularly challenging. The multimodal nature of the research data as well as the wide range in spatial and temporal scales need to be adequately captured . Therefore, a suitable metadata model for neuroscience data has to balance flexibility and restrictiveness to accommodate the individuality of research products, without diminishing comparability across them. Powered by the Human Brain Project (HBP) and EBRAINS, we present the open Metadata Initiative for Neuroscience Data Structures (openMINDS). This novel initiative develops and maintains interlinked metadata models tailored to describe neuroscience research products in graph databases, such as the EBRAINS Knowledge Graph. The openMINDS research products cover data originating from human, animal or simulation studies (datasets), computational models (models), software tools (software), formal specifications for structuring metadata and/or data (metaDataModels), and reference brain atlases (brainAtlas). To illustrate the power of openMINDS, we present selected features describing these research products. We highlight how respective data and their provenance as well as studied specimens can be captured with user-defined granularity, and how the various integration of data via openMINDS can enhance its comparability and findability within and beyond the EBRAINS Knowledge Graph.

• Abrams, Mathew Birdsall; Bjaalie, Jan G.; Das, Samir; Egan, Gary F.; Ghosh, Satrajit S. & Goscinski, Wojtek J. [Show all 23 contributors for this article] (2021). Correction to: A Standards Organization for Open and FAIR Neuroscience: the International Neuroinformatics Coordinating Facility (Neuroinformatics, (2021), 10.1007/s12021-020-09509-0). Neuroinformatics. ISSN 1539-2791. doi: 10.1007/s12021-021-09522-x. Full text in Research Archive
• Puchades, Maja; Yates, Sharon Christine; Bjerke, Ingvild Elise; Groeneboom, Nicolaas; Csucs, Gergely & Leergaard, Trygve B. [Show all 7 contributors for this article] (2021). Implementing the QUINT workflow for spatial quantitative analysis of labelling in mice and rats. Full text in Research Archive Show summary

  Research in small animal disease models and simulation depend on quantitative comparisons of cellular and molecular measures in large groups of specimens, requiring efficient and reproducible methods. The EBRAINS QUINT workflow combines 3D atlas registration tools (QuickNII and VisuAlign) with machine learning based image segmentation (ilastik), and a tool for quantitative analysis on whole brain and regional level (Nutil Quantifier). Workflow descriptions, video tutorials, courses and email sup

• Puchades, Maja; Dickscheid, Timo & Leergaard, Trygve B. (2021). Hands-on Session V: Brain Atlases. Full text in Research Archive Show summary

  The Virtual Master Class Series is a collaborative effort – between IBRO, IBI, INCF & HBP – to train Senior PIs on various EBRAINS Tools and Services throughout all regions of the world. This first edition focuses on the vast Brain Atlasing and Simulation Services available in EBRAINS. Expert speakers will present several tools and delve into practical usage in 6 hands-on sessions. The event is designed as a train-the-teacher” workshop. The target group of the event are mid-career researchers in the Asia-Pacific region, affiliated with and invited by IBRO.

• Reiten, Ingrid; Schlegel, Ulrike; Aasebø, Ida; Zehl, Lyuba; Blixhavn, Camilla Hagen & Davison, Andrew [Show all 17 contributors for this article] (2021). Data sharing via EBRAINS: why and how. Full text in Research Archive
• Leergaard, Trygve B.; Bjerke, Ingvild Elise; Palomero-Gallagher, Nicola; Witter, Menno; Dickscheid, Timo & Puchades, Maja [Show all 7 contributors for this article] (2021). Neuroscience data integration through use of digital brain atlases. Full text in Research Archive Show summary

  Kurs om data integrasjon og digitale hjerne atlas. September 1: INTRODUCTION (Trygve Leergaard & Ingvild Bjerke) SESSION 1: Concepts for sharing and integration of neuroscience data (Jan Bjaalie) SHORT BREAK SESSION 2: Navigating the brain (Nicola Palomero-Gallagher, Menno P. Witter, Timo Dickscheid) LUNCH BREAK SESSION 2: continued SHORT BREAK SESSION 3: Introduction to EBRAINS digital brain atlas resources (Timo Dickscheid & Maja Puchades) CLOSURE DAY 1 September 2: SESSION 4: Sharing and assigning location parameters to murine data (Ingvild Bjerke & Maja Puchades) SHORT BREAK SESSION 4, continued SHORT BREAK SESSION 5: Automated quantification of experimental murine image data (Sharon Yates & Maja Puchades) LUNCH BREAK SESSION 5, continued (Sharon Yates) BREAK SESSION 6: Visions of data integration in the future (Jan Bjaalie) CLOSURE DAY 2: Evaluation and preparation for exam task (Trygve Leergaard)

• Reiten, Ingrid; Schlegel, Ulrike; Aasebø, Ida Elisabeth Jørgensen; Blixhavn, Camilla Hagen; Zehl, Lyuba & Kjelsberg, Kasper [Show all 13 contributors for this article] (2020). Neuroscience community-gains from data sharing through the EBRAINS infrastructure. Full text in Research Archive Show summary

  EBRAINS provides tools and services which can be used to address challenges in brain research and brain-inspired technology development. EBRAINS assists scientists to collect, analyse, share and integrate brain data, and to perform modeling and simulation of brain function. EBRAINS is delivered by the EU Flagship Human Brain Project. All tools and services in EBRAINS are available for researchers in Europe and globally through https://ebrains.eu. Here we exemplify the use of the platform in different neuroscientific projects. In particular, the ‘Data & Knowledge’ services in EBRAINS offer one of the most comprehensive services for sharing brain research data ranging in type as well as spatial and temporal scale. An extensive metadata curation process ensures a robust presentation of datasets, models and software via the EBRAINS Knowledge Graph (https://kg.ebrains.eu/search/), making the data Findable, Accessible, Interoperable and Reusable (FAIR). By describing data across modalities in a standardised way and integrating it into the same reference space, data can be compared, combined and analysed with tools and analytical workflows embedded in the platform. New data, and data derived from the analytical workflows, can be submitted to curation and added to the existing EBRAINS datasets. The interplay between datasets, models and software makes EBRAINS attractive as a platform for discovery based and hypothesis driven research.

• Schlegel, Ulrike; Reiten, Ingrid; Aasebø, Ida Elisabeth Jørgensen; Blixhavn, Camilla Hagen; Zehl, Lyuba & Kjelsberg, Kasper [Show all 13 contributors for this article] (2020). EBRAINS data sharing: benefits and workflow. Full text in Research Archive
• Reiten, Ingrid; Schlegel, Ulrike; Blixhavn, Camilla Hagen; Andersson, Krister Andreas; Aasebø, Ida Elisabeth Jørgensen & Yates, Sharon Christine [Show all 12 contributors for this article] (2020). Data sharing through the online EBRAINS platform: a new service for brain research. Full text in Research Archive Show summary

  Enhancing the reproducibility and transparency of research is an emerging theme across scientific disciplines, driven by new technological advances, and captured by the Open Science concept. The heterogeneity of research data, which often hinders direct comparisons of findings, adds a layer of complexity to this effort. To address these challenges in neuroscience, the Human Brain Project has developed a new research infrastructure, EBRAINS, providing tools and services to the neuroscientific community. The EBRAINS data curation service offers comprehensive stewardship for sharing experimental and computational data. New workflows and standards for neuroscience data and metadata management have been developed to make the research results discoverable, comparable across modalities, and possible to reanalyse and reuse in new combinations. Here we present our workflows and curation services tailored for sharing heterogeneous neuroscience data. We demonstrate the integration of such data in the infrastructure, and highlight some practicalities for researchers who want to share their neuroscience data through EBRAINS.

• Yates, Sharon Christine; Groeneboom, Nicolaas; Csucs, Gergely; Leergaard, Trygve B.; Kreshuk, Anna & Kutra, Dominik [Show all 8 contributors for this article] (2020). New functionalities i the QUINT workflow for brain atlas based image analysis. Full text in Research Archive Show summary

  The novel QUINT workflow enables quantification and spatial analysis of labeling in series of histological section images from mouse or rat brains, that have been registered to 3D reference brain atlases (Allen Mouse Brain Atlas, CCFv3 and Waxholm Space atlas of the rat brain v2 and v3). The workflow utilizes several open source software developed with support from the Human Brain Project: QuickNII, ilastik, VisuAlign and Nutil. Here we present new software functionalities: a tool for non-linear registration of 2D images to a reference atlas (VisuAlign) performed after the linear registration with QuickNII; an improved Nutil graphical user interface based on feedback from the community; and improved ilastik functionality allowing usage of masks, generated by tools like QuickNII or other software. The workflow is exemplified by quantification of parvalbumin positive cells from an Allen mouse brain in situ hybridisation experiment, which is available in the EBRAINS data portal.

• Yates, Sharon Christine; Groeneboom, Nicolaas; Csúcs, Gergely; Leergaard, Trygve B.; Puchades, Maja & Bjaalie, Jan G. (2019). Batch quantification and spatial analysis of labelling in microscopic rodent brain sections. Full text in Research Archive
• Andersson, Krister Andreas; Blixhavn, Camilla Hagen; Kleven, Heidi; Zehl, Lyuba; Bjerke, Ingvild Elise & Schmid, Oliver [Show all 17 contributors for this article] (2019). Neuroinformatics platform for making neuroscience data Findable, Accessible, Interoperable, and Reuseable. Full text in Research Archive
• Andersson, Krister Andreas; Blixhavn, Camilla Hagen; Zehl, Lyuba; Zarfarnia, Sara; Köhnen, Stefan & Hilverling, Anna [Show all 19 contributors for this article] (2019). Resources for making neuroscience data FAIR. The Human Brain Project invites researchers to share, find, and use data via the new EBRAINS infrastructure. Full text in Research Archive
• Andersson, Krister Andreas; Blixhavn, Camilla Hagen; Kleven, Heidi; Schlegel, Ulrike; Oliver, Schmid & Puchades, Maja [Show all 10 contributors for this article] (2019). EBRAINS fair data service: A novel infrastructure for making neuroscience data findable, accessible, interoperable, and reuseable. Full text in Research Archive
• Schlegel, Ulrike; Blixhavn, Camilla Hagen; Andersson, Krister Andreas; Yates, Sharon Christine; Øvsthus, Martin & Bjerke, Ingvild Elise [Show all 11 contributors for this article] (2019). Integrating and analysing heterogeneous rodent neuroscience data using three-dimensional brain reference atlases. Full text in Research Archive Show summary

  Achieving advances in the field of neuroscience with its rapidly growing number of published data requires integration across many scales and levels of investigation. Such integration is challenging due to the heterogeneous nature of the data, and the difficulty of comparing data from different studies. Key aspects include lack of standards for presentation of data and experimental parameters (metadata), and variable practices for assigning and reporting anatomical location in the brain. The EU Human Brain Project (HBP) is addressing these challenges by establishing an infrastructure of neuroinformatic tools and data curation services through which disparate neuroscience data can be shared, used and analysed. Three-dimensional (3D) open access brain reference atlases provide anatomical context for all the shared data, easing comparison and interpretation of findings. We here present HBP workflows for assigning metadata describing anatomical locations to different types of neuroscience data, and workflows for extracting, quantifying and co-visualizing morphological features from multiple datasets in 3D anatomical brain atlas viewers. We highlight the added value of mapping data to a common atlas framework in example studies, and demonstrate new analytic opportunities enabled by combining image analysis tools with information from a 3D brain reference atlas. The HBP now invites the community to use the new research infrastructure established.

• Blixhavn, Camilla Hagen; Andersson, Krister Andreas; Kleven, Heidi; Schlegel, Ulrike; Puchades, Maja & Bjaalie, Jan G. [Show all 7 contributors for this article] (2019). Infrastructure and workflow for integrating and navigating multi-scale and multi-modal murine neuroscience data using 3D digital brain reference atlases. Full text in Research Archive
• Blixhavn, Camilla Hagen; Andersson, Krister Andreas; Kleven, Heidi; Schlegel, Ulrike; Puchades, Maja & Bjaalie, Jan G. [Show all 7 contributors for this article] (2019). Find and explore rodent brain data using 3D atlases in the new EBRAINS infrastructure. Full text in Research Archive
• Puchades, Maja; Yates, Sharon Christine; Groeneboom, Nicolaas; Csúcs, Gergely; Leergaard, Trygve B. & Bjaalie, Jan G. (2019). Workflow for quantification and spatial analysis of labeling in large series of histological images from murine brains. Full text in Research Archive Show summary

  We present a novel workflow - QUINT- for quantification and spatial analysis of labeling in series of histological section images from mouse or rat brains, using Human Brain Project (HBP) tools and procedures. The workflow can be used to detect and localise any distinct feature in the brain sections. The workflow is therefore transferable to different transgenic disease models and other types of mouse or rat studies.

• Bjerke, Ingvild Elise; Øvsthus, Martin; Andersson, Krister Andreas; Bjaalie, Jan G. & Leergaard, Trygve B. (2018). Best practices for determining and documenting neuroanatomical locations in the rodent brain. Full text in Research Archive
• Linstow, Christian Ulrich von; Yates, Sharon Christine; Leergaard, Trygve B.; Plank, A-C; Hörsten, S. von & Puchades, Maja [Show all 7 contributors for this article] (2018). Whole brain analysis of Huntingtin aggregates in the F344 transgenic rat model of Huntington’s disease. Full text in Research Archive
• Zehl, Lyuba; Zafarnia, Sara; Köhnen, Stefan; Andersson, Krister Andreas; Markovic, Milica & Legouée, Elodie [Show all 20 contributors for this article] (2018). Integrating neuroscientific data into a unified database: from individual experiments to a standardized metadata collection using the Human Brain Project Neuroinformatics Platform. Full text in Research Archive
• Zehl, Lyuba; Zafarnia, Sara; Köhnen, Stefan; Andersson, Krister Andreas; Markovic, Milica & Legouée, Elodie [Show all 20 contributors for this article] (2018). Integrating neuroscientific data into a unified database: from individual experiments to a standardized metadata collection using the Human Brain Project Neuroinformatics Platform. Full text in Research Archive
• Andersson, Krister Andreas; Blixhavn, Camilla Hagen; Zehl, Lyuba; Markovic, Milica; Kleven, Heidi & Zafarnia, Sara [Show all 15 contributors for this article] (2018). HBP Curation service: Share your data via the Neuroinformatics platform. Full text in Research Archive
• Yates, Sharon Christine; Puchades, Maja; kreshuk, anna; Kutra, Dominik; Leergaard, Trygve B. & Bjaalie, Jan G. [Show all 7 contributors for this article] (2018). HBP Analytic Workflow: from Microscopic Image Data to Extracted Features in Atlas Space. Full text in Research Archive
• Blixhavn, Camilla Hagen; Andersson, Krister; Øvsthus, Martin; Bjerke, Ingvild Elise; Kleven, Heidi & Puchades, Maja [Show all 8 contributors for this article] (2018). Data integration through digital brain atlasing: Making diverse neuroscience data discoverable using Human Brain Project infrastructure. Full text in Research Archive
• Øvsthus, Martin; Bjerke, Ingvild Elise; Yates, Sharon Christine; Bjaalie, Jan G. & Leergaard, Trygve Brauns (2018). Mapping topographical organization in mouse brain subcortical axonal projections using Human Brain Project infrastructure. Full text in Research Archive
• Imad, Jala; Osen, Kirsten Kjelsberg; Clascá, Francisco; Wennberg, Arvind E.; Coello, Sebastian Christopher & Csúcs, Gergely [Show all 9 contributors for this article] (2017). Enriching and Adding Detail to the Waxholm Space Rat Brain Reference Atlas. Full text in Research Archive Show summary

  Brain reference atlases are important resources for assigning anatomical location to experimental data, and for planning and interpreting experimental results. Three-dimensional atlases can also serve as templates for spatial co-registration (integration) and comparison of different types of brain images. The Waxholm Space atlas of the rat brain is a public resource based on high resolution magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) data. It features a coordinate system based on internal landmarks (Waxholm Space) and delineations of so far 79 brain structures (Papp et al., Neuroimage 97:374-386, 2015; Kjonigsen et al., Neuroimage 108:441-449, 2015). The atlas is shared via the Neuroimaging Informatics Tools and Resources Clearinghouse (www.nitrc.org), and has since its release been widely adopted by the community. A limitation is, however, that detailed anatomical delineations of several major brain regions are missing. In some instances, delineations are not easily introduced due to low contrast in the underlying MRI / DTI templates, or complex features that are challenging to interpret in MRI / DTI data. To amend this, we have spatially registered images of serial histological sections stained for cyto-, chemo- and myeloarchitecture to the Waxholm Space rat brain template, and used these to aid the interpretation of boundaries of structures. We here outline our approach to defining brain structures in the Waxholm Space rat brain template, and present new delineations of the ascending auditory system, the thalamus, as well as several regions in the cerebral cortex and basal forebrain. The anatomical criteria underlying the delineations will be published, and the next version of the atlas delineations will be shared from www.nitrc.org.

• Yates, Sharon Christine; Puchades, Maja; Coello, Sebastian Christopher; Kreshuk, Anna; Hartlage-Rübsamen, Maike & Rossner, Steffen [Show all 8 contributors for this article] (2017). Workflow for automated quantification and spatial analysis of labeling in microscoping rodent brain sections. Full text in Research Archive Show summary

  Introduction: Automated analysis of series of microscopic images from rodent brains can to advantage be used in many neuroscience research projects. To this end, we present a workflow for the automated quantification and spatial analysis of labeling in large series of section images from rodent brain. As an example, we present the quantification of Alzheimer’s disease plaques across a whole mouse brain series immunohistochemically stained for the APP N-terminus (1D1). Method: As a first step, the whole brain image series was anchored to the Allen mouse brain atlas, using an in-house software tool (QuickNII), to produce accurate anatomical maps adapted to the orientation of the images. Subsequently, the section images were classified by use of the ilastik software tool, based on supervised random forest learning algorithms. The classifier relies on input from manual user annotations of selected training images and the image features intensity, edge and texture. In a separate process, the class corresponding to plaque staining was cleaned, to remove edge artifact and background noise. The classified images were subsequently analyzed on a whole brain and regional level with input from the atlas maps. Thereby, a list of individual plaque features (area, location, etc.), region level features (number of plaques, area of plaques, etc.) and whole brain features were derived, enabling quantitative regional analysis as a semi-automatic pipeline. Results: With limited user interaction, we identified and localized according to brain region, individual amyloid plaques across a whole brain image series (Figure 1). Further validation of the workflow is on-going.

• Andersson, Krister; Øvsthus, Martin; Bjerke, Ingvild Elise; Puchades, Maja; Telefont, Martin & Jeff, Muller [Show all 9 contributors for this article] (2017). Data integration through digital brain atlasing: Human Brain Project infrastructure. Full text in Research Archive Show summary

  The Human Brain Project is building an ICT-based scientific research infrastructure that will permit researchers to advance our knowledge in the fields of neuroscience through data exploration, analytics and simulation at multiple levels of brain organization. Experimental neuroscience is connected to the infrastructure through systems for organizing and managing heterogeneous research data. These data systems are initially tested by data producing laboratories in the HBP, and will ultimately be opened for the community. HBP data curation services support users in elevating the level of data consistency and in the migration of data to the open domain. The starting point for research projects that will use HBP resources is the HBP Collaboratory, a rich collaborative workspace which is open to the community. The Collaboratory provides guidance and access to resources, including storage for data and a workbench for entering and organizing metadata. As a central element, the Collaboratory provides high-quality reference atlases of the rodent and human brain, together with appropriate tools and workflows that allow users to register data to the atlases for their study, and to perform initial analysis of data. It also links to important external data repositories and services. Here we present an overview of currently available reference atlases, tools and workflows. We exemplify the use of these resources in a range of neuroscience projects, ranging from brain-wide mapping of molecular level information to identification of precise location of electrophysiology recording sites. With coordinates corresponding to reference atlas space, harvested through the workflow, valuable metadata for future search and analysis of data are captured. Furthermore, with data aligned to reference atlases, analysis of the spatial distribution of events, labeled elements, and regions of interest in image material is strongly supported. Following registration to reference atlas, subsequent image processing and analysis steps delivers lists of extracted features corresponding to atlas structures, enabling quantitative regional analysis. We exemplify analytical workflows producing automated quantification and spatial analysis of labeling in series of histological section images from whole rodent brain. These and other atlas related workflows will be made available as HBP software services.

• Bjerke, Ingvild Elise; Andersson, Krister; Øvsthus, Martin; Puchades, Maja; Bjaalie, Jan G. & Leergaard, Trygve Brauns (2017). Determining and documenting the anatomical location of experimental neuroscience data: Best practice recommendations. Full text in Research Archive Show summary

  Anatomical location is a key parameter for interpretation and comparison of neuroscientific data. Location is typically determined by looking up diagrams in anatomical reference atlases, communicated using anatomical terms, and shown in representative images. But the documentation provided varies considerably among scientific publications. Essential information about nomenclature and reference atlases, or criteria used to define boundaries of structures is often missing. This lack of accuracy limits the opportunities for comparing and integrating data from different publications, and could lead to failure in replicating scientific experiments. To clarify and address this challenge, we have investigated current practice for assigning and documenting anatomical location for different categories of experimental neuroscience data reported in > 120 articles investigating the rodent brain. Our findings show that the specificity and accuracy of anatomical documentation in most cases can be considerably improved with relatively simple procedures. We here suggest some general and method-specific recommendations for such improvements, and discuss how these steps may contribute to increase the accuracy of anatomical descriptions and data interpretation. We demonstrate how new three-dimensional rodent brain reference atlases, and associated software tools for spatial registration of brain image data to a common anatomical space, offer new opportunities for efficient integration and comparison of neuroscience data.

• Papp, Eszter Agnes; Bjaalie, Jan G. & Leergaard, Trygve Brauns (2018). Volumetric atlasing in the rodent brain: connecting experimental image data to standard anatomical space. Universitetet i Oslo. Full text in Research Archive Show summary

  A major challenge for understanding the brain in health and disease is related to combining information about the brain from many different sources. Spatial analysis and comparison of 2D and 3D brain images with the aim to discover new structural and functional features in the data requires mapping the images to a common anatomical space. For rodent models, widely used anatomical reference atlases have until recently been published in a book format that hinders effective comparison across images acquired at different angles and dimensions. The ambition of this study is to advance digital atlasing of the rodent brain towards a new generation of volumetric atlases that facilitate integration of whole-brain image data from multiple modalities. We present the first comprehensive anatomical reference atlas of the Sprague Dawley rat brain based on magnetic resonance imaging. To ensure interoperability with other atlases, we applied the Waxholm Space standard in the rat brain for the first time, and created a mapping against the widely used stereotaxic space. For connecting experimental data to the new reference atlas, we established standard anatomical landmarks for image registration across different levels of structural detail, and created a workflow for section to volume alignment and spatial analysis of brain-wide microscopic image series. Open access to the results of this work has enabled localization of signal in functional and structural image volumes, integration of 2D image series, and development of new atlases of various features of the brain.

View all works in NVA