4.5 Article

A neuroscientist's guide to using murine brain atlases for efficient analysis and transparent reporting

Journal

FRONTIERS IN NEUROINFORMATICS
Volume 17, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fninf.2023.1154080

Keywords

brain atlases; FAIR data; reporting practices; spatial registration; rat brain; mouse brain; brain-wide analysis; neuroinformatics

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Brain atlases are essential resources for neuroscience research. This perspective article provides a guide on how to use mouse and rat brain atlases for data analysis and reporting in accordance with the FAIR principles. It discusses the interpretation and navigation of atlases, their applications in spatial registration and data visualization, as well as the importance of transparent reporting and comparing data mapped to different atlases. The article emphasizes the relevance of atlas-based tools and workflows for FAIR data sharing.
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.

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