The Locare workflow: representing neuroscience data locations as geometric objects in 3D brain atlases

Area of Science:

• Neuroscience
• Bioinformatics
• Computational Biology

Background:

• Neuroscience research generates vast, multimodal data on brain structure and function.
• Organizing and integrating this data based on anatomical location is challenging.
• Current metadata standards struggle to represent diverse data types for anatomical relevance.

Purpose of the Study:

• To develop a standardized method for representing neuroscience data locations within 3D brain atlases.
• To enable spatial querying and co-visualization of multimodal neuroscience data.
• To facilitate the integration and analysis of brain data based on anatomical context.

Main Methods:

• Developed the Locare workflow to define data locations as geometric objects in 3D brain atlases.
• Utilized standardized file formats for specifying geometric objects.
• Proposed JSON schemas (LocareJSON) for atlas coordinate-based object specification.

Main Results:

• Successfully defined geometric objects for multimodal and multilevel neuroscience data in rodent brain atlases (rat/mouse).
• Demonstrated the workflow's applicability for diverse experimental neuroscience data.
• Created LocareJSON schemas for standardized spatial metadata.

Conclusions:

• The Locare workflow and LocareJSON schemas provide a standardized framework for spatially organizing neuroscience data.
• This approach enhances data discoverability, integration, and analysis within anatomical contexts.
• Facilitates co-visualization and spatial querying, advancing comparative neuroscience research.