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神经科学家使用小鼠脑图谱进行高效分析和透明报告指南。

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

作者信息

Kleven Heidi, Reiten Ingrid, Blixhavn Camilla H, Schlegel Ulrike, Øvsthus Martin, Papp Eszter A, Puchades Maja A, Bjaalie Jan G, Leergaard Trygve B, Bjerke Ingvild E

机构信息

Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway.

出版信息

Front Neuroinform. 2023 Mar 9;17:1154080. doi: 10.3389/fninf.2023.1154080. eCollection 2023.

Abstract

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.

摘要

脑图谱在神经科学中被广泛用作进行实验研究以及整合、分析和报告动物模型数据的资源。有各种各样的图谱可供使用,为特定目的找到最佳图谱并进行高效的基于图谱的数据分析可能具有挑战性。比较使用不同图谱报告的结果也并非易事,这是可重复科学的一个障碍。在这篇观点文章中,我们提供了一份指南,说明如何根据倡导数据应可查找、可访问、可互操作和可重复使用的FAIR原则,将小鼠和大鼠脑图谱用于分析和报告数据。我们首先介绍如何解读图谱并将其用于导航到脑区位置,然后讨论如何将其用于不同的分析目的,包括空间配准和数据可视化。我们为神经科学家如何比较映射到不同图谱的数据并确保结果的透明报告提供指导。最后,我们总结了选择图谱时的关键考虑因素,并展望了增加基于图谱的工具和工作流程的采用对FAIR数据共享的相关性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/364f/10033636/10c4ac0ccacb/fninf-17-1154080-g001.jpg

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