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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

Graph theoretical analysis of human brain structural networks.

Chun-Yi Zac Lo¹, Yong He, Ching-Po Lin

¹Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, Taipei, Taiwan.

Reviews in the Neurosciences

|August 25, 2011

Summary

Graph theory analysis of human brain networks reveals nonrandom structural patterns. These brain network properties change with age, development, and disease, offering insights into brain function and disorders.

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

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

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

Published on: November 8, 2012

Area of Science:

Neuroscience
Network Science
Medical Imaging

Background:

Human brain connectivity is increasingly studied using noninvasive neuroimaging.
Graph theory analysis provides insights into the topological organization of brain networks.

Purpose of the Study:

To review recent studies on brain structural networks using graph theory and MRI.
To highlight methodological advancements and applications in analyzing brain connectivity.

Main Methods:

Utilizing structural magnetic resonance imaging (MRI) and diffusion MRI.
Applying graph theoretical approaches to analyze brain structural networks.
Examining network properties like small-worldness, modularity, and hubs.

Main Results:

Structural brain networks exhibit nonrandom properties (small-worldness, modularity, hubs).
Network topology changes across development, aging, and in neuropsychiatric diseases.
Network structure correlates with cognitive functions, suggesting links to functional dynamics.

Conclusions:

Graph theory analysis of structural MRI reveals key organizational principles of the human brain.
Network alterations are associated with aging, development, and brain disorders.
Future research combining structural and functional MRI may yield biomarkers for disease diagnosis and treatment.