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A three-dimensional, population-based average of the C57BL/6 mouse brain from DAPI-stained coronal slices

Fluorescence imaging of immunolabeled brain slices is a key tool in neuroscience that enable mapping of proteins or DNA/RNA at resolutions not possible with non-invasive techniques, including magnetic resonance or nuclear imaging. The signal in specific regions is usually quantified after manually d...

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Detalles Bibliográficos
Autores principales: Stæger, Frederik Filip, Mortensen, Kristian Nygaard, Nielsen, Malthe Skytte Nordentoft, Sigurdsson, Björn, Kaufmann, Louis Krog, Hirase, Hajime, Nedergaard, Maiken
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7359299/
https://www.ncbi.nlm.nih.gov/pubmed/32661243
http://dx.doi.org/10.1038/s41597-020-0570-z
Descripción
Sumario:Fluorescence imaging of immunolabeled brain slices is a key tool in neuroscience that enable mapping of proteins or DNA/RNA at resolutions not possible with non-invasive techniques, including magnetic resonance or nuclear imaging. The signal in specific regions is usually quantified after manually drawing regions of interest, risking operator-bias. Automated segmentation methods avoid this risk but require multi-sample average atlases with similar image contrast as the images to be analyzed. We here present the first population-based average atlas of the C57BL/6 mouse brain constructed from brain sections labeled with the fluorescence nuclear stain DAPI. The data set constitutes a rich three-dimensional representation of the average mouse brain in the DAPI staining modality reconstructed from coronal slices and includes an automatic segmentation/spatial normalization pipeline for novel coronal slices. It constitutes the final population-based average template, individual reconstructed brain volumes, and native coronal slices. The comprehensive data set and accompanying spatial normalization/segmentation software are provided. We encourage the community to utilize it to improve and validate methods for automated brain slice analysis.