Maja Amedjkouh Puchades

• 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 Show summary

  a shift toward technology-enhanced learning environments, has created significant learning opportunities while simultaneously expanding the landscape of advanced training resources, ranging from biophysical simulations to high-dimensional neuroimaging and electrophysiological datasets. However, a critical “educator readiness gap” exists because the successful implementation of these tools often depends on the instructors’ technical expertise and on their capacity to seamlessly integrate them into pedagogical practice. This paper introduces the Neuroscience Education Readiness Checklist (NERC), a 25-item self-assessment framework designed for creators and developers of neuroscience tools and training resources. NERC provides a structured approach that covers the major areas of concern in a comprehensive manner with actionable items. It organizes criteria into three overarching domains: general items and accessibility, instructor usability and workflow, and technical readiness. By addressing specific needs such as domain-specificity, pedagogical utility, and infrastructure requirements, NERC aims to reduce the burden on faculty members who evaluate training resource quality while providing important feedback for creators and developers. Developed through co-design workshops and refined with developer feedback, NERC provides a standardized approach to ensure neuroscience tools are not only technologically sound but also readily education-adoptable and scalable. While initial content has been curated through co-design, future validation will assess inter-rater reliability and predictive validity against adoption outcomes. Ultimately, NERC aims to foster a reproducible educational ecosystem, bridging the gap between innovative neuroscience and effective classroom implementation to ensure equitable access to high-quality neuroscience training.

• 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
• 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; 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.

• Hawrylycz, Michael; Martone, Maryann E.; Ascoli, Giorgio A.; Bjaalie, Jan G.; Dong, Hong-Wei & Ghosh, Satrajit S. [Show all 103 contributors for this article] (2023). A guide to the BRAIN Initiative Cell Census Network data ecosystem. PLoS Biology. ISSN 1544-9173. 21(6). doi: 10.1371/journal.pbio.3002133. Full text in Research Archive Show summary

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

• Carey, Harry; Pegios, Michael; Lewis, Martin; Saleeba, Christine; Turner, A. & Everett, Nicholas [Show all 10 contributors for this article] (2023). DeepSlice: rapid fully automatic registration of mouse brain imaging to a volumetric atlas. Nature Communications. 14(1). doi: 10.1038/s41467-023-41645-4. Full text in Research Archive Show summary

  Registration of data to a common frame of reference is an essential step in the analysis and integration of diverse neuroscientific data. To this end, volumetric brain atlases enable histological datasets to be spatially registered and ana- lyzed, yet accurate registration remains expertise-dependent and slow. In order to address this limitation, we have trained a neural network, DeepSlice, to register mouse brain histological images to the Allen Brain Common Coordinate Framework, retaining registration accuracy while improving speed by >1000 fold.

• 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.

• Carey, Harry; Pegios, Michael; Martin, Lewis; Saleeba, Christine; Turner, Anita & Everett, Nicholas [Show all 9 contributors for this article] (2022). DeepSlice: rapid fully automatic registration of mouse brain imaging to a volumetric atlas. bioRxiv. ISSN 2692-8205. doi: 10.1101/2022.04.28.489953. Full text in Research Archive Show summary

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

• Hawrylycz, Michael J; Martone, Maryann E.; Hof, Patrick R.; Lein, Ed S.; Regev, Aviv & Ascoli, Giorgio A. A. [Show all 99 contributors for this article] (2022). The BRAIN Initiative Cell Census Network Data Ecosystem: A User’s Guide. bioRxiv. ISSN 2692-8205. doi: 10.1101/2022.10.26.513573. Full text in Research Archive Show summary

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

• Royan, Muhammad Rahmad; Siddique, Khadeeja; Csucs, Gergely; Puchades, Maja; Nourizadeh-Lillabadi, Rasoul & Bjaalie, Jan G. [Show all 9 contributors for this article] (2021). 3D Atlas of the Pituitary Gland of the Model Fish Medaka (Oryzias latipes). Frontiers in Endocrinology. 12. doi: 10.3389/fendo.2021.719843. Full text in Research Archive Show summary

  In vertebrates, the anterior pituitary plays a crucial role in regulating several essential physiological processes via the secretion of at least seven peptide hormones by different endocrine cell types. Comparative and comprehensive knowledge of the spatial distribution of those endocrine cell types is required to better understand their physiological functions. Using medaka as a model and several combinations of multicolor fluorescence in situ hybridization, we present the first 3D atlas revealing the glandwide distribution of seven endocrine cell populations: lactotropes, thyrotropes, Lh and Fsh gonadotropes, somatotropes, and pomca-expressing cells (corticotropes and melanotropes) in the anterior pituitary of a teleost fish. By combining in situ hybridization and immunofluorescence techniques, we deciphered the location of corticotropes and melanotropes within the pomca-expressing cell population. The 3D localization approach reveals sexual dimorphism of tshba-, pomca-, and lhb-expressing cells in the adult medaka pituitary. Finally, we show the existence of bi-hormonal cells coexpressing lhb-fshb, fshb-tshba and lhb-sl using single-cell transcriptomics analysis and in situ hybridization. This study offers a solid basis for future comparative studies of the teleost pituitary and its functional plasticity.

• 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
• Groeneboom, Nicolaas Ervik; Yates, Sharon Christine; Puchades, Maja & Bjaalie, Jan G. (2020). Nutil: A Pre- and Post-processing Toolbox for Histological Rodent Brain Section Images. Frontiers in Neuroinformatics. doi: 10.3389/fninf.2020.00037. Full text in Research Archive
• 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.

• 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
• 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.

• Heiland, Tina; Zeitschel, Ulrike; Puchades, Maja; Kuhn, Peer-Hendrik; Lichtenthaler, Stefan F. & Bjaalie, Jan G. [Show all 9 contributors for this article] (2018). Defined astrocytic expression of human amyloid precursor protein in Tg2576 mouse brain. Glia. ISSN 0894-1491. 67(2), p. 393–403. doi: 10.1002/glia.23550. Full text in Research Archive Show summary

  Transgenic Tg2576 mice expressing human amyloid precursor protein (hAPP) with the Swedish mutation are among the most frequently used animal models to study the amyloid pathology related to Alzheimer's disease (AD). The transgene expression in this model is considered to be neuron‐specific. Using a novel hAPP‐specific antibody in combination with cell type‐specific markers for double immunofluorescent labelings and laser scanning microscopy, we here report that—in addition to neurons throughout the brain—astrocytes in the corpus callosum and to a lesser extent in neocortex express hAPP. This astrocytic hAPP expression is already detectable in young Tg2576 mice before the onset of amyloid pathology and still present in aged Tg2576 mice with robust amyloid pathology in neocortex, hippocampus, and corpus callosum. Surprisingly, hAPP immunoreactivity in cortex is restricted to resting astrocytes distant from amyloid plaques but absent from reactive astrocytes in close proximity to amyloid plaques. In contrast, neither microglial cells nor oligodendrocytes of young or aged Tg2576 mice display hAPP labeling. The astrocytic expression of hAPP is substantiated by the analyses of hAPP mRNA and protein expression in primary cultures derived from Tg2576 offspring. We conclude that astrocytes, in particular in corpus callosum, may contribute to amyloid pathology in Tg2576 mice and thus mimic this aspect of AD pathology.

• 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.

• Plank, Anne-Christine; Canneva, Fabio; Raber, Kerstin; Urbach, Yvonne K; Dobner, Julia & Puchades, Maja [Show all 12 contributors for this article] (2018). Early Alterations in Operant Performance and Prominent Huntingtin Aggregation in a Congenic F344 Rat Line of the Classical CAGn51trunc Model of Huntington Disease. Frontiers in Neuroscience. ISSN 1662-4548. 12. doi: 10.3389/fnins.2018.00011. Full text in Research Archive Show summary

  The transgenic rat model of Huntington disease expressing a fragment of mutant HTT (tgHD rat) has been thoroughly characterized and reproduces hallmark symptoms of human adult-onset HD. Pursuing the optimization of this model for evaluation of translational therapeutic approaches, the F344 inbred rat strain was considered as advantageous genetic background for the expression of the HD transgenic construct. In the present study, a novel congenic line of the SPRDtgHD transgenic model of HD, carrying 51 CAG repeats, was generated on the F344 rat genetic background. To assess the behavioral phenotype, classical assays investigating motor function, emotion, and sensorimotor gating were applied, along with automated screening of metabolic and activity parameters as well as operant conditioning tasks. The neuropathological phenotype was analyzed by immunohistochemistry and ex vivo magnetic resonance imaging. F344tgHD rats displayed markedly reduced anxiety-like behavior in the social interaction test and elevated impulsivity traits already at 3 months of age. Neuropathologically, reduced striatal volume and pronounced aggregation of mutant huntingtin in several brain regions were detected at later disease stage. In conclusion, the congenic F344tgHD model reproduces key aspects of the human HD phenotype, substantiating its value for translational therapeutic approaches.

• Prydz, Agnete; Stahl, Katja; Puchades, Maja Amedjkouh; Davarpaneh, Nina; Nadeem, Maria & Ottersen, Ole Petter [Show all 8 contributors for this article] (2017). Subcellular expression of aquaporin-4 in substantia nigra of normal and MPTP-treated mice. Neuroscience. ISSN 0306-4522. 359, p. 258–266. doi: 10.1016/j.neuroscience.2017.07.029. Full text in Research Archive Show summary

  Aquaporin-4 (AQP4) is the predominant water channel in mammalian CNS where it is localized at the perivascular astrocytic foot processes abutting brain microvessels. Several lines of evidence suggest that AQP4 is involved in important homeostatic functions and that mislocalization of the perivascular pool of AQP4 is implicated in several different brain disorders. A recent study suggests that the differential susceptibility of midbrain dopaminergic neurons to the parkinsonogenic toxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) depends on the expression of AQP4. Further, MRI studies of patients with Parkinson’s disease (PD) point to an excessive water accumulation in the substantia nigra (SN). This prompted us to investigate the cellular and subcellular distribution of AQP4 in mouse SN using immunofluorescence and quantitative immunogold cytochemistry. Compared with neocortex, SN exhibits a higher concentration of AQP4. Specifically, judged by electron microscopic immunogold analysis, the perivascular density of AQP4 in SN exceeds by 70% the perivascular density of AQP4 in the neocortex. An even larger difference in AQP4 labeling was found for astrocytic processes in the neuropil. Treatment with MPTP further increased (by >30%) the perivascular AQP4 density in SN, but also increased AQP4 labeling in the neocortex. Our data indicate that the perivascular AQP4 pool in SN is high in normal animals and even higher after treatment with MPTP. This would leave the SN more prone to water accumulation and supports the idea that AQP4 could be involved in the pathogenesis of PD.

• Morland, Cecilie; Andersson, Krister; Haugen, Øyvind Pernell; Hadzic, Alena; Kleppa, Liv & Gille, Andreas [Show all 21 contributors for this article] (2017). Exercise induces cerebral VEGF and angiogenesis via the lactate receptor HCAR1. Nature Communications. 8. doi: 10.1038/ncomms15557. Full text in Research Archive Show summary

  Physical exercise can improve brain function and delay neurodegeneration; however, the initial signal from muscle to brain is unknown. Here we show that the lactate receptor (HCAR1) is highly enriched in pial fibroblast-like cells that line the vessels supplying blood to the brain, and in pericyte-like cells along intracerebral microvessels. Activation of HCAR1 enhances cerebral vascular endothelial growth factor A (VEGFA) and cerebral angiogenesis. High-intensity interval exercise (5 days weekly for 7 weeks), as well as L-lactate subcutaneous injection that leads to an increase in blood lactate levels similar to exercise, increases brain VEGFA protein and capillary density in wild-type mice, but not in knockout mice lacking HCAR1. In contrast, skeletal muscle shows no vascular HCAR1 expression and no HCAR1-dependent change in vascularization induced by exercise or lactate. Thus, we demonstrate that a substance released by exercising skeletal muscle induces supportive effects in brain through an identified receptor. Editorial summary: Physical exercise promotes brain angiogenesis through an unknown signalling cascade. Morland et al. identify the elusive muscle-brain communication and show that lactate produced by muscle activity binds to its receptor HCAR1 in brain vessel-surrounding cells, stimulating VEGF production and brain angiogenesis.

• Wood, Thomas Ragnar; Osredkar, Damjan; Puchades, Maja Amedjkouh; Maes, Elke; Falck, Mari & Flatebø, Torun [Show all 9 contributors for this article] (2016). Treatment temperature and insult severity influence the neuroprotective effects of therapeutic hypothermia. Scientific Reports. 6. doi: 10.1038/srep23430. Full text in Research Archive Show summary

  Therapeutic hypothermia (HT) is standard care for moderate and severe neonatal hypoxic-ischaemic encephalopathy (HIE), the leading cause of permanent brain injury in term newborns. However, the optimal temperature for HT is still unknown, and few preclinical studies have compared multiple HT treatment temperatures. Additionally, HT may not benefit infants with severe encephalopathy. In a neonatal rat model of unilateral hypoxia-ischaemia (HI), the effect of five different HT temperatures was investigated after either moderate or severe injury. At postnatal-day seven, rat pups underwent moderate or severe HI followed by 5 h at normothermia (37 °C), or one of five HT temperatures: 33.5 °C, 32 °C, 30 °C, 26 °C, and 18 °C. One week after treatment, neuropathological analysis of hemispheric and hippocampal area loss, and CA1 hippocampal pyramidal neuron count, was performed. After moderate injury, a significant reduction in hemispheric and hippocampal loss on the injured side, and preservation of CA1 pyramidal neurons, was seen in the 33.5 °C, 32 °C, and 30 °C groups. Cooling below 33.5 °C did not provide additional neuroprotection. Regardless of treatment temperature, HT was not neuroprotective in the severe HI model. Based on these findings, and previous experience translating preclinical studies into clinical application, we propose that milder cooling should be considered for future clinical trials.

• Osredkar, Damjan; Sabir, Hemmen; Falck, Mari; Wood, Thomas Ragnar; Maes, Elke & Flatebø, Torun [Show all 8 contributors for this article] (2015). Hypothermia Does Not Reverse Cellular Responses Caused by Lipopolysaccharide in Neonatal Hypoxic-Ischaemic Brain Injury. Developmental Neuroscience. ISSN 0378-5866. 37(4-5), p. 390–397. doi: 10.1159/000430860. Full text in Research Archive
• Morland, Cecilie; Lauritzen, Knut Husø; Puchades, Maja Amedjkouh; Holm-Hansen, Signe; Andersson, Krister & Gjedde, Albert [Show all 9 contributors for this article] (2015). The lactate receptor, G-protein-coupled receptor 81/hydroxycarboxylic acid receptor 1: Expression and action in brain. Journal of Neuroscience Research. ISSN 0360-4012. 93(7), p. 1045–1055. doi: 10.1002/jnr.23593. Full text in Research Archive
• Lauritzen, Knut Husø; Morland, Cecilie; Puchades, Maja Amedjkouh; Holm-Hansen, Signe; Hagelin, Else Marie Valbjørn & Lauritzen, Fredrik [Show all 10 contributors for this article] (2014). Lactate receptor sites link neurotransmission, neurovascular coupling, and brain energy metabolism. Cereb Cortex. Cerebral Cortex. ISSN 1047-3211. p. 2784–2795. doi: 10.1093/cercor/bht136. Full text in Research Archive
• Lauritzen, Knut Husø; Morland, Cecilie; Puchades, Maja Amedjkouh; Holm-Hansen, Signe; Hagelin, Else Marie Valbjørn & Lauritzen, Fredrik [Show all 10 contributors for this article] (2013). Lactate Receptor Sites Link Neurotransmission, Neurovascular Coupling, and Brain Energy Metabolism. Cerebral Cortex. ISSN 1047-3211. doi: 10.1093/cercor/bht136. Full text in Research Archive Show summary

  The G-protein-coupled lactate receptor, GPR81 (HCA1), is known to promote lipid storage in adipocytes by downregulating cAMP levels. Here, we show that GPR81 is also present in the mammalian brain, including regions of the cerebral neocortex and hippocampus, where it can be activated by physiological concentrations of lactate and by the specific GPR81 agonist 3,5-dihydroxybenzoate to reduce cAMP. Cerebral GPR81 is concentrated on the synaptic membranes of excitatory synapses, with a postsynaptic predominance. GPR81 is also enriched at the blood-brain-barrier: the GPR81 densities at endothelial cell membranes are about twice the GPR81 density at membranes of perivascular astrocytic processes, but about one-seventh of that on synaptic membranes. There is only a slight signal in perisynaptic processes of astrocytes. In synaptic spines, as well as in adipocytes, GPR81 immunoreactivity is located on subplasmalemmal vesicular organelles, suggesting trafficking of the protein to and from the plasma membrane. The results indicate roles of lactate in brain signaling, including a neuronal glucose and glycogen saving response to the supply of lactate. We propose that lactate, through activation of GPR81 receptors, can act as a volume transmitter that links neuronal activity, cerebral energy metabolism and energy substrate availability.

• Stensrud, Mats Julius; Puchades, Maja Amedjkouh & Gundersen, Vidar (2013). GABA is localized in dopaminergic synaptic vesicles in the rodent striatum. Brain Structure and Function. ISSN 1863-2653. doi: 10.1007/s00429-013-0609-4. Full text in Research Archive
• Sogn, Carl Johan; Puchades, Maja Amedjkouh & Gundersen, Vidar (2013). Rare contacts between synapses and microglial processes containing high levels of Iba1 and actin - a postembedding immunogold study in the healthy rat brain. European Journal of Neuroscience. ISSN 0953-816X. 38(1), p. 2030–2040. doi: 10.1111/ejn.12213. Full text in Research Archive
• Puchades, Maja Amedjkouh; Sogn, Carl Johan; Mæhlen, Jan; Bergersen, Linda Hildegard & Gundersen, Vidar (2013). Unaltered lactate and glucose transporter levels in the MPTP mouse model of Parkinson's disease. Parkinson's Disease. ISSN 2090-8083. 3(3), p. 371–385. doi: 10.3233/JPD-130190. Full text in Research Archive

View all works in NVA

• 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/.

• Gonzales, Christina Martinez; Yates, Sharon Christine; Kleven, Heidi & Puchades, Maja (2026). From slices to 3D: QUINT workflow for brain atlas registration and image quantification. doi: https:/ebrains.eu/news-and-events/events/2026/from-slices-to-3d-quint-workflow-for-brain-atlas-registration-and-image. Full text in Research Archive Show summary

  This 1-hour online + Q&A roundtable brings together QUINT developers, experts in digital brain atlases and neuroinformatics, to discuss the QUINT Workflow. This event is designed for students and researchers working with histological images, offering a unique opportunity to ask questions and get feedback from leading experts in the field.

• Puchades, Maja (2025). Use of integrated EBRAINS tools in Education: the QUINT online workflow. Full text in Research Archive Show summary

  Neuroscience Education Plenary by INCF and EBRAINS Education Task Force. This session will introduce EBRAINS and INCF’s efforts to democratise neuroinformatics and make tools and resources developed by the large-scale brain initiatives more classroom ready. In addition, an example of an EBRAINS resource used in education will be presented; and participants will be introduced to the NeurotechEU, the European University Alliance of Brain and Technology.

• 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

• Puchades, Maja & Bjerke, Ingvild Elise (2024). StratNeuro PhD Retreat 2024 in collaboration with INCF. Full text in Research Archive Show summary

  Full day course on EBRAINS atlases and atlas related tools including the QUINT workflow. Presentations and hands-on sessions with exercises the students performed on their own computers.

• Puchades, Maja (2024). “Meet EBRAINS: Europe's digital infrastructure for brain research". 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
• 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
• Puchades, Maja Amedjkouh; Yates, Sharon Christine; Bjerke, Ingvild Elise & Carey, Harry (2023). Rodent atlasing tools and the QUINT workflow. Full text in Research Archive
• Yates, Sharon Christine; Gurdon, Brianna; Csucs, Gergely; Groeneboom, Nicolaas Ervik; Puchades, Maja Amedjkouh & Kaczorowski, Catherine [Show all 7 contributors for this article] (2023). High-throughput method for brain-wide characterisation of genetically diverse AD mice. Full text in Research Archive
• 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
• Puchades, Maja; Carey, Harry & Bjaalie, Jan G. (2022). Neuroinformatics tools for performing feature extraction and advanced brain-wide distribution analysis in an atlas context. Full text in Research Archive Show summary

  Workshop organised by University of Oslo during INCF assembly 2022. This workshop will present and compare a series of neuroinformatics tools for performing feature extraction and advanced brain-wide distribution analysis in an atlas context. The speakers will be recruited from different projects and institutions developing complementary tools and services for brain-wide analysis of data originating from small animal experimental Workshop neuroscience. They will discuss alternative approaches for registration of images, segmentation, analyses, reuse of data, and smart combinations of new neuroinformatics tools originating from different laboratories and projects. Attendees will be guided through use cases demonstrating how the tools can be used in different contexts and for different purposes. Topic: Neuroinformatics tools for performing feature extraction and advanced brain-wide distribution analysis in an atlas context. International invited speakers: Lydia Ng (Allen Brain Institute); Daniel Furth (Uppsala University); Nicolas Chiaruttini (EPFL); Adam Tyson (UCL).

• Carey, Harry; Csucs, Gergely; McMullan, Simon; Puchades, Maja & Bjaalie, Jan G. (2022). DeepSlice Rat: A Deep Neural Network for automatic registration of rat brain images to the Waxholm Space atlas of the rat brain. Full text in Research Archive Show summary

  The rat is widely used in experimental neuroscience and with the increasing availability of many genetic tools in rat, its popularity in neuroscientific research is likely to increase. In order to properly leverage the magnitude of rat data that the neuroscientific community generates, brain derived data must be mapped to a common spatial reference space. To this end, the Waxholm Space atlas of the rat brain (RRID:SCR_017124) has been created. While there exist tools to register rat brain data to the Waxholm Space, including the QuickNII (RRID:SCR_016854) and VisuAlign (RRID:SCR_017978) tools provided by the EBRAINS research infrastructure (https://ebrains.eu/services/atlases), these tools are relatively demanding of time and expertise, often requiring hours per whole brain. If we are to comprehensively map the massive amount of brain data currently being generated, we will require automated methods capable of registering data to a common reference space. Here we present DeepSlice Rat, a deep neural network for the automated registration of rat brain images to the Waxholm Space atlas of the rat brain. We show that DeepSlice Rat is equal in performance to an expert neuroanatomist whilst being thousands of times faster. DeepSlice Rat can be used in combination with QuickNII for verification of the registration, and VisuAlign for non-linear adjustments, creating an AI assisted workflow that will greatly enhance productivity. DeepSlice Rat will be freely available on EBRAINS (alongside a mouse implementation) as both a Python package and web-application.

• Puchades, Maja & Bjaalie, Jan G. (2022). Introduction to the EBRAINS Research Infrastructure: Data Knowledge services and Data analysis. Full text in Research Archive
• Carey, Harry; Csucs, Gergely; Puchades, Maja & Bjaalie, Jan G. (2022). AutoAlign Rat: Spatially anchoring rat brain histology to the Waxholm rat brain atlas using deep neural networks. Full text in Research Archive Show summary

  The rat offers many benefits over the mouse for experimental neuroscience, though the popularity of the mouse has surged in recent years due to an ever-growing genetic toolbox. This toolbox is now being expanded to rats and will surely lead to an explosion in rat brain data. To prepare for this we must build tools to spatially anchor rat brain data into a common reference space, enabling comparison and meta-analysis of anchored data. To this end we have created AutoAlign, a deep learning toolbox which spatially anchors rat brain histology to the Waxholm Space atlas of the rat brain (RRID: SCR_017124). AutoAlign can anchor rat brain histology cut coronally, sagitally, and horizontally, here we compare the accuracy of the algorithm to humans across each of these planes. While anchoring a whole-brain dataset would take an anatomist many hours, AutoAlign achieves this in seconds. AutoAlign is compatible with the QUINT workflow, including QuickNII (RRID: SCR_016854), allowing predictions to be modified by users, and VisuAlign (RRID: SCR_017978) enabling the atlas to be warped and deformed to anchored sections. AutoAlign Rat is freely available as both a Python package and web application.

• 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

• 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).

• Puchades, Maja (2022). EBRAINS atlases, tools & workflows. Full text in Research Archive Show summary

  Presentation of the EBRAINS atlas service resources during the EBRAINS FENS satellite event, ‘EBRAINS Research Infrastructure Symposium: addressing grand challenges in brain research’, aims to bring together experimental, clinical and computational neuroscientists. We will highlight the connections between basic and clinical neuroscience and computational neuroscience. The program will be structured around four sessions on why, what, how and where to integrate multi-resolution and multi-scale data for neuroscience research.

• Yates, Sharon Christine; Gurdon, Brianna; Csucs, Gergely; Groeneboom, Nicolaas Ervik; Puchades, Maja Amedjkouh & Kaczorowski, Catherine [Show all 7 contributors for this article] (2022). Quint workflow for brain-wide quantification of rodent models: new functionality for high-throughput studies. Full text in Research Archive Show summary

  Sectioned brain tissue of rodent models is used to explore the cellular and molecular composition of the brain in health and disease. The QUINT workflow was developed to support standardized atlas-based analysis of sectioned tissue without the need for coding ability. It is shared on the EBRAINS Atlas Services as a suite of open-source tools that can be flexibly combined to meet the needs of diverse projects (ebrains.eu). This includes tools for atlas-registration, feature extraction and quantification in regions defined by a reference atlas of the brain. New functionality has been added to the QUINT workflow to meet the needs of a novel Alzheimer’s disease project involving a large population of genetically diverse mice, the AD-BDX panel (Neuner et al, Neuron 2019, PMID: 30595332). This includes QCAlign: a tool for assessing the quality of the section images, as well as the quality of the atlas-registration to the sections as performed with the registration tools. By supporting systematic assessment of the material, QCAlign allows the removal of damaged sections, and the post-processing of results according to strict criteria that are transparent and reproducible. As a proof-of-concept, the QCAlign tool was applied to data from the Alzheimer’s project to detect and remove sections with more than 30% damage. It was also used to assess the quality of the atlas-registration before and after application of nonlinear refinements to the registration. To summarize, QCAlign tackles challenges posed by high-throughput studies and expands the scope of the QUINT workflow for comprehensive analysis.

• 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
• 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.

• 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.

• 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.

• Puchades, Maja & Dickscheid, Timo (2021). Workshop IV: EBRAINS data sharing and use of multilevel human brain atlases. Full text in Research Archive Show summary

  The EBRAINS Research Infrastructure provides services for finding and sharing neuroscience research data as well as comprehensive atlases of the human, rodent and mouse brain. In this hands-on session, we will introduce tools and workflows for finding datasets and interacting with the human brain atlas. There is a broad consensus among researchers, publishers and funding bodies that open sharing of data is needed to address major reproducibility and transparency challenges that currently exist in all scientific disciplines. EBRAINS offers access to curated data and models discoverable and comparable across modalities according to the FAIR guiding principles. The EBRAINS multilevel human brain atlas integrates maps that capture different facets of human brain organisation, in a common framework. It is defined across multiple reference spaces, zooming in from the millimeter scale in the MNI space to the micrometer level of the BigBrain. The atlas currently links cytoarchitectonic areas with ultra-high resolution BigBrain data, fiber bundles from MRI tractography, maps of functional modules, and a whole range of multimodal data features associated to various brain regions. The range and scope of available maps and features is constantly increasing. As the amount of data constituting the human atlas exceeds the disk capacity of most computers, it is designed as an online framework that you can access in a number of ways through the siibra toolsuite. The main entry point is our interactive 3D viewer (siibra explorer), which allows to explore the different facets of the atlas in 3D and to select specific data features for download. Programmatic interfaces, including a Python library (siibra-python) and HTTP API (siibra-API) are currently in development, with pre-releases available for interested users. We will talk about the development of key parts of this atlas: Maps and 3D models of the human brain, derived from microscopic resolution of histology using state of the art machine learning and “big data” technologies. We will then walk you through the main features of the different interfaces of the EBRAINS atlas, introducing you to typical scientific use cases. Workshop Chairs & Tutors: Maja A. Puchades | University of Oslo Timo Dickscheid | Forschungszentrum Jülich

• Puchades, Maja & Dickscheid, Timo (2021). Hands-on Session I: 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 3 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 African region, affiliated with and invited by IBRO as well as attendees of the INCF Training Week.

• Puchades, Maja (2021). Brain atlas based analysis tools:Q and A. Full text in Research Archive Show summary

  Overview of EBRAINS atlas service and related tools

• 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.

• Gurdon, Brianna; Hadad, Niran; Telpoukhovskaia, Maria; Yates, Sharon Christine; Puchades, Maja & Bjaalie, Jan G. [Show all 7 contributors for this article] (2020). Brain-wide spatial analysis to identify region-specific changes in cell composition associated with resilience to Alzheimer’s disease in the AD-BXD mouse population. Full text in Research Archive
• 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.

• 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
• 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
• 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.

• 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 labelling in microscoping rodent brain sections. Full text in Research Archive
• Puchades, Maja; Csúcs, Gergely; Checinska, Martyna; Øvsthus, Martin; Bjerke, Ingvild Elise & Andersson, Krister [Show all 8 contributors for this article] (2017). Neuroinformatics tool and workflow for anchoring of serial histological images in rodent brain 3D space. Full text in Research Archive Show summary

  Reference atlases of the brain are important tools for assigning location to data captured in neuroscience experiments. Spatial alignment of sectional images to reference atlases is, however, challenging to perform for several reasons. Manual approaches applied to large series of sectional images are time consuming and, moreover, histological sections are often cut at angles deviating from the principal anatomical planes presented in conventional reference atlases. Novel 3D reference atlases and accompanying tools provide new opportunities for rapid and accurate spatial registration and integration of data in common atlas space. We here present QuickNII which is new tools for use with the Waxholm Space atlas for the rat brain and the Allen Mouse brain atlas for the mouse brain, and a workflow that allows users to 1) interactively generate customized atlas images (slices of the 3D reference atlas) corresponding to the plane of sectioning of any experimental image series, 2) superimpose atlas images onto experimental images using affine transformations to match key anatomical landmarks, 3) propagate the transformations across a series of images, 4) assign spatial reference atlas coordinates to the experimental images, and 5) allow viewing and analysis of the experimental data integrated in the reference atlas. We exemplify the workflow and use of our methods with a range of experimental data from neuroanatomical and neurophysiological investigations.

• Puchades, Maja; Øvsthus, Martin; Bjerke, Ingvild Elise; Andersson, Krister; Csúcs, Gergely & Leergaard, Trygve Brauns [Show all 7 contributors for this article] (2017). Data integration through digital brain atlasing: semiautomatic spatial registration of serial histological images to rodent brain 3D reference atlases. Full text in Research Archive Show summary

  Reference atlases of the brain are important tools for assigning location to data captured in neuroscience experiments. Spatial alignment of sectional images to reference atlases is, however, challenging to perform for several reasons. Manual approaches applied to large series of sectional images are time consuming and, moreover, histological sections are often cut at angles deviating from the principal anatomical planes presented in conventional reference atlases. Novel 3D reference atlases and accompanying tools provide new opportunities for rapid and accurate spatial registration and integration of data in common atlas space. We here present new tools for use with the Waxholm Space atlas for the rat brain and the Allen Mouse brain atlas, and workflow that allows users to 1) interactively generate customized atlas images (slices of the 3D reference atlas) corresponding to the plane of sectioning of any experimental image series, 2) superimpose atlas images onto experimental images using affine transformations to match key anatomical landmarks, 3) propagate the transformations across a series of images, 4) assign spatial reference atlas coordinates to the experimental images, and 5) allow viewing and analysis of the experimental data integrated in the reference atlas. We exemplify the work flow and use of our methods with a range of experimental data from neuroanatomical and neurophysiological investigations.

• Bjerke, Ingvild Elise; Andersson, Krister Andreas; Øvsthus, Martin; Puchades, Maja; Bjaalie, Jan G. & Leergaard, Trygve B. (2017). Navigating the rodent brain: Best practice recommendations for determining and documenting spatial location for neuroscience data. Full text in Research Archive
• Leprince, Y; Coello, Sebastian Christopher; Csúcs, Gergely; Chervakov, P; Darine, Dmitri Aleksandrovitsj & Øvsthus, Martin [Show all 12 contributors for this article] (2017). Interactive tools for registering of 2D and 3D images to reference atlases. Full text in Research Archive
• Andersson, Krister Andreas; Bell, Simon; Bjerke, Ingvild Elise; Øvsthus, Martin; Blixhavn, Camilla Hagen & Kleven, Heidi [Show all 18 contributors for this article] (2017). Submitting data and metadata through the HBP Data Workbench: Concepts, data flows, policies, and best practices. Full text in Research Archive
• Andersson, Krister; Morland, Cecilie; Haugen, Øyvind Pernell; Hadzic, Alena; Kleppa, Liv & Gille, Andreas [Show all 21 contributors for this article] (2017). Exercise benefits brain through the lactate receptor HCAR1, increasing VEGF and capillary density in hippocampus and cortex. Full text in Research Archive Show summary

  While physical exercise is known to improve brain function and delay neurodegeneration, the signal from muscle to brain has not been identified. We show here that the lactate receptor, hydroxycarboxylic acid receptor 1 (HCAR1 also known as GPR81), mediates exercise induced increase in the content of vascular endothelial growth factor A (VEGFA) and in capillary density in the hippocampus and cerebral cortex. Mice were subjected to high intensity interval exercise 5 days per week for 7 weeks. Increases in VEGFA and capillary density were observed in wild-type (wt) mice, but not in knockout (ko) mice lacking HCAR1. Subcutaneous injections of L-lactate 5 days per week for 7 weeks, to achieve intermittently high blood lactate levels comparable to those after exercise, reproduced the findings in wt mice. No changes were observed in ko mice. The intermittent nature of the stimulation may be important since continuously high extracellular lactate has previously been observed to down-regulate HCAR1. To our knowledge, the present finding is the first demonstration that a substance released by exercising skeletal muscle induces supportive effects in brain through an identified receptor. No changes in VEGFA or capillary density were observed in the cerebellar cortex. HCAR1 was highly expressed in pial fibroblast-like cells that line the vessels supplying blood to the brain, and in fibroblast-/pericyte-like cells along intracerebral microvessels. These cells are strategically placed to monitor changes in blood-born lactate as well as in brain extracellular lactate (which equilibrate across the vascular endothelium via monocarboxylate transporter 1). Skeletal muscle showed no vascular HCAR1 expression and no HCAR1-dependent change in vascularization induced by exercise or lactate. As VEGFA governs neuronal functions such as LTP as well as vascular growth, the increases may have direct effects on neurons as well as indirect effects through enhancement of vascularization. Both disturbed vascularization and impaired synaptic function are components of the pathogenesis in neurodegenerative dementias such as Alzheimer’s disease. The lactate receptor HCAR1 may prove a useful nutraceutical target for intervention in persons at risk for dementia who are unable to exercise sufficiently to achieve optimal HCAR1 stimulation through rises in blood lactate.

• Morland, Cecilie; Andersson, Krister; Haugen, Øyvind Pernell; Hadzic, Alena; Kleppa, Liv & Gille, Andreas [Show all 18 contributors for this article] (2016). A novel mechanism for cerebral angiogenesis via lactate receptor HCAR1 at pial vessels. Full text in Research Archive
• Puchades, Maja; Bjerke, Ingvild Elise; Øvsthus, Martin; Andersson, Krister; Csúcs, Gergely & Leergaard, Trygve Brauns [Show all 7 contributors for this article] (2016). Spatial registration of serial histological image data to reference brain atlases. Full text in Research Archive
• Morland, Cecilie; Andersson, Krister; Haugen, Øyvind Pernell; Hadzic, Alena; Kleppa, Liv & Gille, Andreas [Show all 18 contributors for this article] (2016). Exercise induces cerebral angiogenesis via lactate receptor HCAR1 at pial vessels. Full text in Research Archive
• Falck, Mari; Osredkar, Damjan; Maes, Elke; Wood, Thomas Ragnar; Puchades, Maja Amedjkouh & Sabir, Hemmen [Show all 7 contributors for this article] (2015). Systemic Inflammation Negates Hypothermic Neuroprotection in a Neonatal HIE-model. Full text in Research Archive
• Puchades, Maja Amedjkouh; Darine, Dmitri Aleksandrovitsj; Csúcs, Gergely; Lillehaug, Sveinung; Leergaard, Trygve Brauns & Bjaalie, Jan G. (2015). Feeding rodent brain data to computational models through HBP spatial atlas templates and knowledge graph portal. Full text in Research Archive
• Bergersen, Linda Hildegard; Lauritzen, Knut Husø; Lauritzen, Fredrik; Puchades, Maja Amedjkouh & Gjedde, Albert (2012). Lactate receptor locations link neurotransmission, neurovascular coupling, and brain energy metabolism. Journal of Cerebral Blood Flow and Metabolism. ISSN 0271-678X. 32, p. S183–S183. Full text in Research Archive

View all works in NVA