Blar i Kavliinstitutt for nevrovitenskap på tidsskrift "iScience"

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    • Densities and numbers of calbindin andparvalbumin positive neurons across the rat and mouse brain 

      Bjerke, Ingvild Elise; Yates, Sharon Christine; Laja, Arthur; Witter, Menno; Puchades, Maja; Bjaalie, Jan G.; Leergaard, Trygve B. (Peer reviewed; Journal article, 2020)
      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 ...

    • Enhancer-Driven Gene Expression (EDGE) Enables the Generation of Viral Vectors Specific to Neuronal Subtypes 

      Nair Raveendran, Rajeevkumar; Blankvoort, Stefan; Lagartos, Maria Jose; Kentros, Clifford (Journal article; Peer reviewed, 2020)
      Although a variety of remarkable molecular tools for studying neural circuits have recently beendeveloped, the ability to deploy them in particular neuronal subtypes is limited by the fact that nativepromoters are almost ...

    • Insights into the quantification and reporting of model-related uncertainty across different disciplines 

      Simmonds, Emily Grace; Dunn-Sigouin, Etienne; Adjei, Kwaku Peprah; Andersen, Christoffer Wold; Aspheim, Janne Cathrin Hetle; Battistin, Claudia; Bulso, Nicola; Christensen, Hannah M.; Cretois, Benjamin; Cubero, Ryan John Abat; Davidovich, Ivan Andres; Dickel, Lisa; Dunn, Benjamin Adric; Dyrstad, Karin; Einum, Sigurd; Giglio, Donata; Gjerløw, Haakon; Godefroidt, Amélie; González-Gil, Ricardo; Gonzalo Cogno, Soledad; Große, Fabian; Halloran, Paul; Jensen, Mari Fjalstad; Kennedy, John James; Langsæther, Peter Egge; Laverick, Jack H; Lederberger, Debora; Li, Camille; Mandeville, Elizabeth G; Mandeville, Caitlin; Moe, Espen; Schröder, Tobias Navarro; Nunan, David; Sicacha-Parada, Jorge; Simpson, Melanie Rae; Skarstein, Emma Sofie; Spensberger, Clemens; Stevens, Richard; Subramanian, Aneesh C.; Svendsen, Lea; Theisen, Ole Magnus; Watret, Connor; O'Hara, Robert B. (Peer reviewed; Journal article, 2022)
      Quantifying uncertainty associated with our models is the only way we can express how much we know about any phenomenon. Incomplete consideration of model-based uncertainties can lead to overstated conclusions with real-world ...