Towards a sharable numeric and symbolic knowledge base on cerebral cortex anatomy: lessons learned from a prototype

Area of Science:

• Neuroscience
• Computer Science
• Medical Informatics

Background:

• The sulco-gyral pattern of the human brain cortex is complex.
• Integrating diverse knowledge types (numeric and symbolic) is challenging for brain research and applications.

Purpose of the Study:

• To propose a novel knowledge base for representing sulco-gyral brain cortex information.
• To enable reusability across diverse applications like education, surgical decision support, and data sharing.

Main Methods:

• Implementation of a knowledge base using web technologies.
• Formal representation of taxonomy and mereotopology for brain structures.
• Utilization of identity criteria for symbolic concept representation.

Main Results:

• A functional knowledge base integrating numeric and symbolic data was developed.
• The proposed formalisms enable robust representation of brain cortex features.
• The system is designed for flexible integration into various neuro-related applications.

Conclusions:

• A formal representation of taxonomy, mereotopology, and identity criteria is essential for a versatile brain cortex knowledge base.
• The developed web-based knowledge base facilitates diverse applications in neuroscience and neurosurgery.
• This approach enhances the sharing and utilization of neuroimaging data.