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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

Individual-level brain morphological similarity networks: Current methodologies and applications.

Mengjing Cai¹, Juanwei Ma¹, Zirui Wang¹

¹Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China.

CNS Neuroscience & Therapeutics

|July 31, 2023

Summary

This review summarizes individual-level brain morphological networks, a powerful tool for understanding brain structure. These networks reveal individual brain organization and changes in health and disease.

Keywords:

brain network individual level morphological similarity network structural magnetic resonance imaging

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Modeling the Functional Network for Spatial Navigation in the Human Brain

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Three-Dimensional Shape Modeling and Analysis of Brain Structures

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Published on: November 14, 2019

Area of Science:

Neuroscience
Neuroimaging
Brain Network Analysis

Background:

The human brain's complexity necessitates advanced imaging techniques like magnetic resonance imaging (MRI).
Structural MRI-based brain morphological networks offer advantages in data acquisition and image quality.
These networks reveal intrinsic structural organizing principles of the brain.

Purpose of the Study:

To review the methodology and applications of individual-level brain morphological networks.
To highlight the significance of individual-level networks in understanding brain structure.
To provide insights into brain development and neuropsychiatric disorders.

Main Methods:

Focuses on individual-level brain morphological network studies.
Introduces various network construction methods.
Reviews representative research in the field.

Main Results:

Individual-level morphological networks measure regional similarity within single brains.
These networks reflect individual brain's morphological information.
They have shown significant value in exploring topological brain changes in normal and disease states.

Conclusions:

Individual-level morphological networks offer novel perspectives on brain development and disease mechanisms.
The review identifies current challenges and future research directions in this field.