Trygve Brauns Leergaard

• Syverstad, Gry-Helen Enger; Melbye, Christopher; 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.
• Abrams, Mathew Birdsall; Bjaalie, Jan G.; Das, Samir; Egan, Gary F.; Ghosh, Satrajit S. & Goscinski, Wojtek J. [Show all 23 contributors for this article] (2021). A Standards Organization for Open and FAIR Neuroscience: the International Neuroinformatics Coordinating Facility. Neuroinformatics. ISSN 1539-2791. doi: 10.1007/s12021-020-09509-0. Full text in Research Archive
• Allegra Mascaro, A. L.; Falotico, E.; Petkosi, S.; Pasquini, M.; Vannucci, L. & Tort-Colet, N. [Show all 23 contributors for this article] (2020). Experimental and Computational Study on Motor Control and Recovery After Stroke: Toward a Constructive Loop Between Experimental and Virtual Embodied Neuroscience . Frontiers in Systems Neuroscience. ISSN 1662-5137. 14. doi: 10.3389/fnsys.2020.00031. Full text in Research Archive
• 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. ISSN 2589-0042. 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. ISSN 2052-4463. 7. doi: 10.6084/m9.figshare.12199088.
• 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. ISSN 1662-5196. 13. doi: 10.3389/fninf.2019.00075. Full text in Research Archive
• Post, Joakim Iver; Leergaard, Trygve B.; Ratz, Veronika; Walaas, S. Ivar; von Hörsten, Stephan & Nissen-Meyer, Lise Sofie Haug (2019). Differential Levels and Phosphorylation of Type 1 Inositol 1,4,5-Trisphosphate Receptor in Four Different Murine Models of Huntington Disease . Journal of Huntington's Disease. ISSN 1879-6397. 8(3), p. 271–289. doi: 10.3233/JHD-180301.
• Osen, Kirsten Kjelsberg; Imad, Jala; Wennberg, Arvind Eirik; Papp, Eszter Agnes & Leergaard, Trygve Brauns (2019). Waxholm Space atlas of the rat brain auditory system: Three-dimensional delineations based on structural and diffusion magnetic resonance imaging. NeuroImage. ISSN 1053-8119. 199, p. 38–56. doi: 10.1016/j.neuroimage.2019.05.016. Full text in Research Archive Show summary

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

• 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. ISSN 2052-4463. 6, p. 1–15. doi: 10.1038/sdata.2019.28.
• 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. ISSN 1932-6203. 14(5). doi: 10.1371/journal.pone.0216796. 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. ISSN 1662-5129. 12. doi: 10.3389/fnana.2018.00082. Full text in Research Archive
• 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.2018.02.0. Full text in Research Archive
• Mughal, Awais; Zhang, Lili; Fayzullin, Artem; Server, Andrés; Li, Yuping & Wu, Yingxi [Show all 11 contributors for this article] (2018). Patterns of Invasive Growth in Malignant Gliomas - The Hippocampus Emerges as an Invasion-Spared Brain Region. Neoplasia. ISSN 1522-8002. 20(7), p. 643–656. doi: 10.1016/j.neo.2018.04.001. Full text in Research Archive
• Stahl, Katja; Rahmani, Soulmaz; Prydz, Agnete; Skauli, Nadia; MacAulay, Nanna & Mylonakou, Maria-Niki [Show all 13 contributors for this article] (2018). Targeted deletion of the aquaglyceroporin AQP9 is protective in a mouse model of Parkinson's disease. PLOS ONE. ISSN 1932-6203. 13(3). doi: 10.1371/journal.pone.0194896. Full text in Research Archive
• Schubert, N; Axer, M; Schober, M; Huynh, A; Huysegoms, M & Palomero-Gallagher, N [Show all 11 contributors for this article] (2016). 3D reconstructed cyto-, muscarinic M<sub>2</sub> receptor, and fiber architecture of the rat brain registered to the waxholm space atlas. Frontiers in Neuroanatomy. ISSN 1662-5129. 10(MAY). doi: 10.3389/fnana.2016.00051.
• Papp, Eszter Agnes; Leergaard, Trygve Brauns; Csúcs, Gergely & Bjaalie, Jan G. (2016). Brain-wide mapping of axonal connections: Workflow for automated detection and spatial analysis of labeling in microscopic sections. Frontiers in Neuroinformatics. ISSN 1662-5196. 10(11). doi: 10.3389/fninf.2016.00011. Full text in Research Archive
• Yetman, Michael J.; Lillehaug, Sveinung; Bjaalie, Jan G.; Leergaard, Trygve Brauns & Jankowsky, Joanna L. (2016). Transgene expression in the Nop-tTA driver line is not inherently restricted to the entorhinal cortex. Brain Structure and Function. ISSN 1863-2653. 221(4), p. 2231–2249. doi: 10.1007/s00429-015-1040-9.
• Blackstad, Jan Sigurd Beddari; Osen, Kirsten Kjelsberg; Scharfman, Helen E.; Storm-Mathisen, Jon; Blackstad, Theodor & Leergaard, Trygve Brauns (2016). Observations on hippocampal mossy cells in mink (Neovison vison) with special reference to dendrites ascending to the granular and molecular layers. Hippocampus. ISSN 1050-9631. 26(2), p. 229–245. doi: 10.1002/hipo.22518.
• Zakiewicz, Izabela Maria; Majka, Piotr; Wòjcik, Daniel K.; Bjaalie, Jan G. & Leergaard, Trygve Brauns (2015). Three-Dimensional Histology Volume Reconstruction of Axonal Tract Tracing Data: Exploring Topographical Organization in Subcortical Projections from Rat Barrel Cortex. PLOS ONE. ISSN 1932-6203. 10(9). doi: 10.1371/journal.pone.0137571.
• Boccara, Charlotte Nina; Kjønigsen, Lisa Jannicke; Hammer, Ingvild Marie F.; Bjaalie, Jan G.; Leergaard, Trygve Brauns & Witter, Menno (2015). A three-plane architectonic atlas of the rat hippocampal region. Hippocampus. ISSN 1050-9631. 25(7), p. 838–857. doi: 10.1002/hipo.22407.
• Vårbakken, Kjartan; Steen, Harald; Samuelsen, Gunnar; Dahl, Hans A; Leergaard, Trygve Brauns & Stuge, Britt (2015). Primary functions of the quadratus femoris and obturator externus muscles indicated from lengths and moment arms measured in mobilized cadavers. Clinical Biomechanics. ISSN 0268-0033. 30(3), p. 231–237. doi: 10.1016/j.clinbiomech.2015.02.004.
• Kjønigsen, Lisa Jannicke; Lillehaug, Sveinung; Bjaalie, Jan G.; Witter, Menno & Leergaard, Trygve Brauns (2015). Waxholm Space atlas of the rat brain hippocampal region: Three-dimensional delineations based on magnetic resonance and diffusion tensor imaging. NeuroImage. ISSN 1053-8119. 108, p. 441–449. doi: 10.1016/j.neuroimage.2014.12.080. Full text in Research Archive
• Papp, Eszter Agnes; Leergaard, Trygve Brauns; Calabrese, Evan; Johnson, G. Allan & Bjaalie, Jan G. (2015). Addendum to “Waxholm Space atlas of the Sprague Dawley rat brain” [NeuroImage 97 (2014) 374-386]. NeuroImage. ISSN 1053-8119. 105, p. 561–562. doi: 10.1016/j.neuroimage.2014.10.017.
• Vårbakken, Kjartan; Steen, Harald; Samuelsen, Gunnar; Dahl, Hans A; Leergaard, Trygve Brauns & Nordsletten, Lars [Show all 7 contributors for this article] (2014). Lengths of the external hip rotators in mobilized cadavers indicate the quadriceps coxa as a primary abductor and extensor of the flexed hip. Clinical Biomechanics. ISSN 0268-0033. 29(7), p. 794–802. doi: 10.1016/j.clinbiomech.2014.05.011.
• Zakiewicz, Izabela Maria; Bjaalie, Jan G. & Leergaard, Trygve Brauns (2014). Brain-wide map of efferent projections from rat barrel cortex. Frontiers in Neuroinformatics. ISSN 1662-5196. 8. doi: 10.3389/fninf.2014.00005.
• Papp, Eszter Agnes; Leergaard, Trygve Brauns; Calabrese, Evan; Johnson, G. Allan & Bjaalie, Jan G. (2014). Waxholm Space atlas of the Sprague Dawley rat brain. NeuroImage. ISSN 1053-8119. 97, p. 374–386. doi: 10.1016/j.neuroimage.2014.04.001.
• Nuruddin, Syed; Syverstad, Gry-Helen Enger; Lillehaug, Sveinung; Leergaard, Trygve Brauns; Nilsson, Lars & Ropstad, Erik [Show all 9 contributors for this article] (2014). Elevated mRNA-Levels of Gonadotropin-Releasing Hormone and Its Receptor in Plaque-Bearing Alzheimer's Disease Transgenic Mice. PLOS ONE. ISSN 1932-6203. 9(8). doi: 10.1371/journal.pone.0103607.
• Pandya, Abhilash D.; Leergaard, Trygve Brauns; Dissen, Erik; Haraldsen, Guttorm & Spurkland, Anne (2014). Expression of the T cell-specific adapter protein in human tissues. Scandinavian Journal of Immunology. ISSN 0300-9475. 80(3), p. 169–179. doi: 10.1111/sji.12199.
• Lillehaug, Sveinung; Syverstad, Gry-Helen Enger; Nilsson, Lars; Bjaalie, Jan G.; Leergaard, Trygve Brauns & Torp, Reidun (2014). Brainwide distribution and variance of amyloid-beta deposits in tg-ArcSwe mice. Neurobiology of Aging. ISSN 0197-4580. 35(3), p. 556–564. doi: 10.1016/j.neurobiolaging.2013.09.013.
• White, NS; Leergaard, Trygve Brauns; D'Arceuil, Helen; Bjaalie, Jan G. & Dale, AM (2013). Probing tissue microstructure with Restriction Spectrum Imaging: Histological and theoretical validation. Human Brain Mapping. ISSN 1065-9471. 34(2), p. 327–346. doi: 10.1002/hbm.21454.
• Nagelhus, Erlend Arnulf; Amiry-Moghaddam, Mahmood ; Bergersen, Linda Hildegard; Bjaalie, Jan G.; Eriksson, Jens & Gundersen, Vidar [Show all 12 contributors for this article] (2013). The glia doctrine: Addressing the role of glial cells in healthy brain ageing. Mechanisms of Ageing and Development. ISSN 0047-6374. 134(10), p. 449–459. doi: 10.1016/j.mad.2013.10.001.
• Stensrud, Mats Julius; Chaudhry, Farrukh Abbas; Leergaard, Trygve Brauns; Bjaalie, Jan G. & Gundersen, Vidar (2013). Vesicular glutamate transporter-3 in the rodent brain: Vesicular colocalization with vesicular -aminobutyric acid transporter. Journal of Comparative Neurology. ISSN 0021-9967. 521(13), p. 3042–3056. doi: 10.1002/cne.23331.
• Leergaard, Trygve Brauns; Hilgetag, Claus C & Sporns, Olaf (2012). Mapping the connectome: multi-level analysis of brain connectivity. Frontiers in Neuroinformatics. ISSN 1662-5196. doi: 10.3389/fninf.2012.00014.
• Antonsen, Bjørnar Torske; Jiang, Yi; Veraart, Jelle; Qu, Hong; Nguyen, Huu Phuc & Sijbers, Jan [Show all 9 contributors for this article] (2012). Altered diffusion tensor imaging measurements in aged transgenic Huntington disease rats. Brain Structure and Function. ISSN 1863-2653. doi: 10.1007/s00429-012-0427-0.
• Blockx, I; Verhoye, M; Van Audekerke, J; Bergwerf, I; Kane, John & Palacios, RDY [Show all 14 contributors for this article] (2012). Identification and characterization of Huntington related pathology: An in vivo DKI imaging study. NeuroImage. ISSN 1053-8119. 63(2), p. 653–662. doi: 10.1016/j.neuroimage.2012.06.032.
• Veraart, Jelle; Leergaard, Trygve Brauns; Antonsen, Bjørnar; Van Hecke, Wim; Blockx, Ines & Jeurissen, Ben [Show all 11 contributors for this article] (2011). Population-averaged diffusion tensor imaging atlas of the Sprague Dawley rat brain. NeuroImage. ISSN 1053-8119. 58(4), p. 975–983. doi: 10.1016/j.neuroimage.2011.06.063.

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• Reiten, Ingrid; Schlegel, Ulrike; Aasebø, Ida; Zehl, Lyuba; Blixhavn, Camilla Hagen & Davison, Andrew [Show all 17 contributors for this article] (2021). Data sharing via EBRAINS: why and how .
• Schlegel, Ulrike; Köhnen, Stefan; Davison, Andrew P.; Najafi, Peyman; Weyers, Benjamin & Gründling, Jan [Show all 17 contributors for this article] (2021). openMINDS - flexible metadata models for neuroscience. Show summary

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

• Puchades, Maja ; Dickscheid, Timo & Leergaard, Trygve B. (2021). Hands-on Session V: Brain Atlases. 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 ; 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. 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

• 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.
• 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.
• 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.
• 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. 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.

• 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.
• 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.
• 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.
• 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. 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.

• 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.
• 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 .
• 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.
• 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. 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.

• 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.
• Zehl, Lyuba; Zafarnia, Sara; Köhnen, Stefan; Andersson, Krister Andreas; Markovic, Milica & Legouée, Elodie [Show all 20 contributors for this article] (2018). Integrating neuroscientific data into a unified database: from individual experiments to a standardized metadata collection using the Human Brain Project Neuroinformatics Platform.
• Zehl, Lyuba; Zafarnia, Sara; Köhnen, Stefan; Andersson, Krister Andreas; Markovic, Milica & Legouée, Elodie [Show all 20 contributors for this article] (2018). Integrating neuroscientific data into a unified database: from individual experiments to a standardized metadata collection using the Human Brain Project Neuroinformatics Platform.
• 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.
• von Linstow, Christian Ulrich; Yates, Sharon Christine; Leergaard, Trygve B.; Plank, A-C; von Hörsten, S. & 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.
• Bjerke, Ingvild Elise; Øvsthus, Martin; Andersson, Krister Andreas; Bjaalie, Jan G. & Leergaard, Trygve B. (2018). Best practices for determining and documenting neuroanatomical locations in the rodent brain.
• Øvsthus, Martin; Bjerke, Ingvild Elise; Yates, Sharon Christine; Bjaalie, Jan G. & Leergaard, Trygve Brauns (2018). Mapping topographical organization in mouse brain subcortical axonal projections using Human Brain Project infrastructure.
• 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.
• Leergaard, Trygve B. (2017). Building and using rodent brain reference atlases for integration of experimental data.
• Timonidis, Nestor; Bakker, Rembrandt; Øvsthus, Martin; Garcia-Amado, M; Porrero, C & Leergaard, Trygve B. [Show all 8 contributors for this article] (2017). Towards predicting the full mesoconnectome based on data fusion.
• 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.
• Imad, Jala; Kleven, Heidi; Clascá, Francisco; Wennberg, Arvind Eirik; Osen, Kirsten Kjelsberg & Coello, Sebastian Christopher [Show all 11 contributors for this article] (2017). Enriching and adding detail to the Waxholm Space rat brain reference atlas.
• 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.
• Coello, Sebastian Christopher; Leergaard, Trygve B. & Bjaalie, Jan G. (2017). Tackling the normalization of 2-D rodent histology sections in a 3-D coordinate space.
• Coello, Sebastian Christopher; Leergaard, Trygve B. & Bjaalie, Jan G. (2017). Tackling the normalization of 2-D rodent histology sections in a 3-D coordinate space.
• 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 .
• Imad, Jala; Osen, Kirsten Kjelsberg; Clascá, Francisco; Wennberg, Arvind E.; Coello, Sebastian Christopher & Csúcs, Gergely [Show all 9 contributors for this article] (2017). Enriching and Adding Detail to the Waxholm Space Rat Brain Reference Atlas. Show summary

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

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

• 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. 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. 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.

• Leergaard, Trygve B. (2016). Navigating the rodent brain: An anatomist’s guide to assigning location to brain image data.
• 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.
• Leergaard, Trygve Brauns (2015). Hjerneforskning i den digitale tidsalder: Fremtidens hjerneatlas.
• Blackstad, Jan Sigurd Beddari; Osen, Kirsten Kjelsberg; Scharfman, HE; Storm-Mathisen, Jon; Blackstad, Theodor W. & Leergaard, Trygve Brauns (2015). Hippocampal mossy cells in mink (Neovison vison).
• 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.
• Schubert, N; Axer, M; Graessel, D; Schober, M; Huynh, A & Huysegoms, M [Show all 11 contributors for this article] (2015). 3D reconstructed fiber-, cyto- and receptorarchitecture of the rat brain transferred into the Waxholm Space atlas.
• Leergaard, Trygve Brauns & Bjaalie, Jan G. (2014). Infrastructure for digital atlasing of mouse and rat brain: Rodent Brain WorkBench.
• Leergaard, Trygve Brauns (2014). Navigating the rodent brain by digital atlasing.
• Papp, Eszter Agnes; Leergaard, Trygve Brauns; Csucs, Gergely; Darine, Dmitri Aleksandrovitsj & Bjaalie, Jan G. (2014). Workflow for integration and analysis of histological data in rodent brain Waxholm Space. Frontiers in Neuroinformatics. ISSN 1662-5196. doi: 10.3389/conf.fninf.2014.18.00060.
• Papp, Eszter Agnes; Leergaard, Trygve Brauns; Csucs, Gergely; Darine, Dmitri Aleksandrovitsj & Bjaalie, Jan G. (2014). Workflow for integration and analysis of histological data in rodent brain Waxholm Space.
• Leergaard, Trygve Brauns; Coello, Christopher; Papp, Eszter Agnes; Ragan, Tim & Bjaalie, Jan G. (2014). Registration of serial two-photon data to rodent brain Waxholm Space. Frontiers in Neuroinformatics. ISSN 1662-5196. doi: 10.3389/conf.fninf.2014.18.00059.
• Leergaard, Trygve Brauns; Coello, Christopher; Papp, Eszter Agnes; Ragan, Tim & Bjaalie, Jan G. (2014). Registration of serial two-photon data to rodent brain Waxholm Space.
• Leergaard, Trygve Brauns; Lillehaug, Sveinung; Papp, Eszter Agnes; Coello, Christopher; Ragan, Tim & Bjaalie, Jan G. (2014). Waxholm Space atlas template enriched with serial two-photon and histological data.
• Leergaard, Trygve Brauns; Yetman, Michael J.; Lillehaug, Sveinung; Bjaalie, Jan G. & Jankowsky, Joanna L. (2014). Transgene expression in the neuropsin tTA driver line is not restricted to the entorhinal cortex.
• Leergaard, Trygve Brauns; Lillehaug, Sveinung; Yetman, Michael J.; Jankowsky, Joanna L. & Bjaalie, Jan G. (2014). Interactive brainwide atlas of tetracycline responsive trans-activator promoter mouse lines.
• Bjaalie, Jan G. & Leergaard, Trygve Brauns (2014). Neuroscience in the information ages: Brain atlasing goes digital. META. ISSN 1890-1956. p. 14–17.
• Syverstad, Gry-Helen Enger; Nuruddin, Syed; Lillehaug, Sveinung; Leergaard, Trygve B.; Haraldsen, Ira Hebold & Torp, Reidun (2013). Targeting gonadotroping-releasing hormone in Alzheimer’s disease.
• Syverstad, Gry-Helen Enger; Lillehaug, Sveinung; Nilsson, Lars N. G.; Bjaalie, Jan G.; Leergaard, Trygve B. & Torp, Reidun (2013). Spatial distribution and variance of amyloid-beta load in middle-aged transgenic Alzheimer’s disease mice with both the Artic and Swedish AβPP mutations.
• Bjaalie, Jan G.; Papp, Eszter Agnes; Kjonigsen, LJ; Johnson, GA; Witter, Menno & Leergaard, Trygve Brauns (2013). Waxholm Space Atlas of the rat brain with detailed hippocampal subdivisions. Show summary

  Volumetric brain atlases are typically built on top of template data sets acquired with Magnetic Resonance Imaging. A relatively high level of structural details is provided combined with the advantage of allowing the entire brain to be viewed interactively in any plane. With appropriate tools for interactive viewing, volumetric atlases are useful for planning of experiments and data analysis by registration of other data sets to the atlas. We provide a volumetric atlas of the rat brain based on ex vivo MRI anatomical (T2*) images with 39 μm isotropic voxels and diffusion tensor imaging (DTI) volumes with 78 μm isotropic voxels acquired from an 80 day old male Sprague-Dawley rat. The atlas covers 83 anatomical structures (areas, nuclei, regions, and fiber tracts) across the brain. The structures were delineated using ITK-SNAP software based on multiple types of image contrasts and anatomical reference information. White matter structures were readily distinguished from grey matter, and some structural differences could also be observed within gray matter. Delineations were aided by information from classical 2D atlases and collections of histological images from brains of comparable animals, and delineation criteria were defined for all structures. Cyto- and chemoarchitectonic features from an online 2D histological atlas (Kjonigsen et al., Front Neuroinform. 2011) were used for delineation of 16 structures in the hippocampal region. The atlas and the underlying MRI and DTI image volumes are to be made open access through the INCF Software Center. Spatial reference is provided by Waxholm Space, a standard atlas space recently defined by the International Neuroinformatics Coordinating Facility (INCF). Waxholm Space connects the atlas to a growing infrastructure of interoperable resources and services for multi-level data integration and analysis across reference spaces.

• Papp, Eszter Agnes; Leergaard, Trygve Brauns; Johnson, G. Allan & Bjaalie, Jan G. (2012). First generation Waxholm atlas of the Sprague-Dawley rat brain.
• Leergaard, Trygve Brauns (2011). Interpreting morphological substrates of diffusion MRI: Histological validation approaches and 3D rat brain atlasing.
• Zakiewicz, Izabela Maria; Bjaalie, Jan G. & Leergaard, Trygve Brauns (2011). Neuroinformatics web applications for 3-D analysis of brain connectivity: anatomical organization of subcortical projections from whisker and forelimb regions of the rat somatosensory cortex. Frontiers in Neuroinformatics. ISSN 1662-5196. doi: 10.3389/conf.fninf.2011.08.00060.
• Moene, Ivar Andre; Darine, Dmitri Aleksandrovitsj; Ramachandran, Muthuraja; Leergaard, Trygve Brauns & Bjaalie, Jan G. (2011). Rodent Brain Navigator: database and atlas system for microscopy and imaging data. Frontiers in Neuroinformatics. ISSN 1662-5196. doi: 10.3389/conf.fninf.2011.08.00159.
• Kjønigsen, Lisa Jannicke; Leergaard, Trygve Brauns; Witter, Menno & Bjaalie, Jan G. (2011). Three-dimensional atlas framework for mapping of projections from the entorhinal cortex to the hippocampal formation in rat. Frontiers in Neuroinformatics. ISSN 1662-5196. doi: 10.3389/conf.fninf.2011.08.00129.
• Papp, Eszter Agnes; Bjaalie, Jan G. & Leergaard, Trygve Brauns (2018). Volumetric atlasing in the rodent brain: connecting experimental image data to standard anatomical space. Faculty of Medicine, University of Oslo. ISSN 978-82-8377-194-7. Full text in Research Archive Show summary

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

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