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Modeling the Functional Network for Spatial Navigation in the Human Brain

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Reaction-diffusion models in weighted and directed connectomes.

Oliver Schmitt¹, Christian Nitzsche¹, Peter Eipert¹

¹Medical School Hamburg, University of Applied Sciences, Hamburg; University of Rostock, Department of Anatomy, Rostock, Germany.

Plos Computational Biology

|October 28, 2022

Summary

This study introduces reaction-diffusion models to analyze brain connectomes, revealing how demyelination impacts neural pathway oscillations and functions.

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Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

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Published on: November 8, 2012

Area of Science:

Computational Neuroscience
Systems Neuroscience
Network Science

Background:

Connectomes map neural connections, essential for understanding brain function and body regulation.
Dynamic neural signaling patterns underpin cognitive functions and behaviors.
Detailed connectomes include connection weights, orientation, and reciprocal connections.

Purpose of the Study:

To investigate diffusion-reaction models for dynamic patterns in weighted and directed connectomes.
To analyze the impact of demyelination on neural pathways using these models.
To implement and apply reaction-diffusion systems within the neuroVIISAS framework.

Main Methods:

Developed differential equations combining diffusion and reaction terms (Gray-Scott, Gierer-Meinhardt, Mimura-Murray).
Implemented implicit solvers for numerically stable reaction-diffusion systems in neuroVIISAS.
Applied models to a subconnectome of the mechanosensitive pathway affected by multiple sclerosis.

Main Results:

Successfully applied reaction-diffusion systems to weighted and directed connectomes.
Demyelination modeling via connectivity weight modulation altered oscillations in the primary somatosensory cortex.
Demonstrated the utility of the neuroVIISAS framework for studying dynamic processes in empirical and modeled connectomes.

Conclusions:

Established a novel application of reaction-diffusion systems for analyzing complex connectomes.
The findings highlight how demyelination can disrupt neural pathway dynamics.
The neuroVIISAS framework offers extensive capabilities for future research on dynamic network processes.