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

Area of Science:

• Neuroscience
• Bioinformatics
• Data Science

Background:

• Brain atlases are essential tools in neuroscience for experimental design, data integration, analysis, and reporting in animal models.
• The proliferation of diverse brain atlases presents challenges in selecting the optimal resource and conducting efficient, reproducible atlas-based analyses.
• Comparing findings across studies utilizing different atlases hinders scientific reproducibility.

Purpose of the Study:

• To provide a comprehensive guide on utilizing mouse and rat brain atlases for data analysis and reporting.
• To promote adherence to FAIR (Findable, Accessible, Interoperable, Re-usable) data principles in neuroscience research.
• To address challenges in atlas selection, data comparison, and transparent reporting to enhance scientific reproducibility.

Main Methods:

• Introduction to the interpretation and navigation of brain atlases for identifying specific brain regions.
• Discussion of atlas application in various analytical tasks, including spatial registration and data visualization.
• Guidance on comparing data mapped to different atlases and ensuring transparent reporting practices.

Main Results:

• Neuroscientists can effectively use brain atlases to navigate, analyze, and visualize neuroscientific data.
• Methods are presented for comparing data across different atlases, facilitating cross-study comparisons.
• Guidance is provided for transparent reporting of findings, enhancing the re-usability of data.

Conclusions:

• Strategic selection and application of brain atlases are crucial for robust neuroscientific data analysis.
• Implementing atlas-based workflows supports FAIR data principles, improving data accessibility and interoperability.
• Increased adoption of atlas-based tools is vital for advancing reproducible science and collaborative research in neuroscience.