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Updated: May 27, 2026

Modeling the Functional Network for Spatial Navigation in the Human Brain

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

Knowledge synthesis with maps of neural connectivity.

Marcelo Tallis¹, Richard Thompson, Thomas A Russ

¹Information Sciences Institute, University of Southern California Marina del Rey, CA, USA.

Frontiers in Neuroinformatics

|November 5, 2011

Summary

This study introduces improved software for synthesizing neuroanatomical knowledge from neural connectivity data. The NeuARt web-application enhances data mapping and navigation for sub-regional brain connectivity research.

Keywords:

knowledge engineering neural connectivity neuroanatomical mapping tract-tracing

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Area of Science:

Neuroscience
Computational Neuroscience
Bioinformatics

Background:

The Swanson laboratory has developed a methodology for mapping neural connectivity in brain regions like the hypothalamus and amygdala since the 1990s.
Previous work involved a visualization application for macro connections using the Swanson atlas.
Accurate registration of neuroanatomical data maps is crucial for knowledge synthesis.

Purpose of the Study:

To describe major improvements to the NeuARt application for neuroanatomical knowledge synthesis.
To incorporate a knowledge representation of experimental design into the software.
To enhance data mapping and navigational features within a unified web-application.

Main Methods:

Developed a unified web-application integrating visualization and data mapping components.
Incorporated a Knowledge Engineering from Experimental Design (KEfED) model based on experimental variables.
Extended KEfED to define neuroanatomical data maps as measurement variables within study designs.

Main Results:

NeuARt now features an improved interface and enhanced data mapping capabilities.
Navigational access is provided between data maps and semantic representations of area-to-area connections.
The software allows anatomical datasets to be described within a standard experimental context.

Conclusions:

The enhanced NeuARt application facilitates neuroanatomical knowledge synthesis by integrating experimental design.
The software enables indexing of anatomical datasets by non-spatial experimental features.
This represents a step towards an accurate sub-regional account of neural connectivity.