使用鼠脑图谱进行有效分析和透明报告的神经科学家指南。

IF 2.5 4区 医学 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY Frontiers in Neuroinformatics Pub Date : 2023-03-09 eCollection Date: 2023-01-01 DOI:10.3389/fninf.2023.1154080
Heidi Kleven, Ingrid Reiten, Camilla H Blixhavn, Ulrike Schlegel, Martin Øvsthus, Eszter A Papp, Maja A Puchades, Jan G Bjaalie, Trygve B Leergaard, Ingvild E Bjerke
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引用次数: 0

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。有多种图谱可用,为特定目的找到最佳图谱并进行有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发现也不是微不足道的,它代表了可再生科学的障碍。通过这篇前瞻性的文章,我们提供了一个指南,说明如何根据FAIR原则使用小鼠和大鼠大脑图谱来分析和报告数据,FAIR原则主张数据是可查找、可访问、可互操作和可重复使用的。我们首先介绍了如何解释和使用地图册导航到大脑位置,然后讨论了如何将地图册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提供指导,并确保研究结果的透明报告。最后,我们总结了选择图谱时的主要考虑因素,并展望了增加使用基于图谱的工具和工作流程对FAIR数据共享的相关性。
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A neuroscientist's guide to using murine brain atlases for efficient analysis and transparent reporting.

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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来源期刊
Frontiers in Neuroinformatics
Frontiers in Neuroinformatics MATHEMATICAL & COMPUTATIONAL BIOLOGY-NEUROSCIENCES
CiteScore
4.80
自引率
5.70%
发文量
132
审稿时长
14 weeks
期刊介绍: Frontiers in Neuroinformatics publishes rigorously peer-reviewed research on the development and implementation of numerical/computational models and analytical tools used to share, integrate and analyze experimental data and advance theories of the nervous system functions. Specialty Chief Editors Jan G. Bjaalie at the University of Oslo and Sean L. Hill at the École Polytechnique Fédérale de Lausanne are supported by an outstanding Editorial Board of international experts. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics and the public worldwide. Neuroscience is being propelled into the information age as the volume of information explodes, demanding organization and synthesis. Novel synthesis approaches are opening up a new dimension for the exploration of the components of brain elements and systems and the vast number of variables that underlie their functions. Neural data is highly heterogeneous with complex inter-relations across multiple levels, driving the need for innovative organizing and synthesizing approaches from genes to cognition, and covering a range of species and disease states. Frontiers in Neuroinformatics therefore welcomes submissions on existing neuroscience databases, development of data and knowledge bases for all levels of neuroscience, applications and technologies that can facilitate data sharing (interoperability, formats, terminologies, and ontologies), and novel tools for data acquisition, analyses, visualization, and dissemination of nervous system data. Our journal welcomes submissions on new tools (software and hardware) that support brain modeling, and the merging of neuroscience databases with brain models used for simulation and visualization.
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