Developing a multiscale neural connectivity knowledgebase of the autonomic nervous system.

Area of Science:

• Neuroscience
• Bioengineering
• Computational Biology

Background:

• Understanding the autonomic nervous system (ANS) is crucial for visceral control.
• Existing knowledge of ANS connectivity is fragmented, hindering therapeutic development.
• The Stimulating Peripheral Activity to Relieve Conditions (SPARC) program aims to consolidate this knowledge.

Purpose of the Study:

• To present the design and functionality of the SPARC Connectivity Knowledge Base of the Autonomic Nervous System (SCKAN).
• To detail the knowledge engineering process for populating SCKAN with accurate ANS connectivity data.
• To demonstrate SCKAN's application in developing neuromodulation devices and bioelectronic medicine.

Main Methods:

• Developed SCKAN, a dynamic resource for ANS projection origins, terminations, and routing.
• Implemented a rigorous curation process involving experts, literature, textbooks, and SPARC data.
• Utilized ontological representation and knowledge engineering for data integration and quality assurance.

Main Results:

• Successfully created SCKAN, a comprehensive knowledge base of autonomic nervous system connectivity.
• SCKAN enables automatic generation of anatomical and functional connectivity maps on the SPARC portal.
• The knowledge base supports the development of advanced information systems for neuroscience research.

Conclusions:

• SCKAN provides a robust, curated resource for understanding ANS connectivity.
• The knowledge engineering approach ensures high-quality data for research and development.
• SCKAN facilitates the advancement of bioelectronic medicine and neuromodulation therapies.