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Scaling up cell-counting efforts in neuroscience through semi-automated methods

Quantifying how the cellular composition of brain regions vary across development, aging, sex, and disease, is crucial in experimental neuroscience, and the accuracy of different counting methods is continuously debated. Due to the tedious nature of most counting procedures, studies are often restri...

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Detalles Bibliográficos
Autores principales: Bjerke, Ingvild Elise, Yates, Sharon Christine, Carey, Harry, Bjaalie, Jan Gunnar, Leergaard, Trygve Brauns
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10457595/
https://www.ncbi.nlm.nih.gov/pubmed/37636060
http://dx.doi.org/10.1016/j.isci.2023.107562
Descripción
Sumario:Quantifying how the cellular composition of brain regions vary across development, aging, sex, and disease, is crucial in experimental neuroscience, and the accuracy of different counting methods is continuously debated. Due to the tedious nature of most counting procedures, studies are often restricted to one or a few brain regions. Recently, there have been considerable methodological advances in combining semi-automated feature extraction with brain atlases for cell quantification. Such methods hold great promise for scaling up cell-counting efforts. However, little focus has been paid to how these methods should be implemented and reported to support reproducibility. Here, we provide an overview of practices for conducting and reporting cell counting in mouse and rat brains, showing that critical details for interpretation are typically lacking. We go on to discuss how novel methods may increase efficiency and reproducibility of cell counting studies. Lastly, we provide practical recommendations for researchers planning cell counting.