About this Research Topic
Brain atlases are ubiquitous in fundamental neuroscience research and serve as basic tools for translational research. Atlases are central in order to integrate diverse information collected at multiple spatial and temporal scales. The complexity of the workflows used to produce atlases is highly diverse: while adapting some parcellation scheme from a template to a new dataset is often an easy procedure, other data require highly complex processing workflows and access to large-scale storage and computing systems. In the light of the current reproducibility questions, we propose to explore how brain atlases with large collections of integrated data are built, used, maintained, related to each other, and how these aspects impact the results of neuroscientific analyses.
In this Research Topic, we aim to bring together different aspects of the research on atlases and approaches for data integration in atlases, covering, e.g.:
- Challenges and solutions regarding reproducibility of atlas construction workflows
- Correspondences of labels and region definitions, and related aspects of metadata and ontology engineering; within and cross-species mappings
- Standards for atlas-related data formats
- Visualization and navigation issues
- Best practices and guidelines for annotation of data and atlases
- Standards and best practices for atlas sharing
- Reproducibility challenges resulting from Big Data in atlas construction and sharing
Keywords: Brain atlases, atlases construction, computing systems, data integration, region definition
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