Assessment of system dysfunction in the brain through MRI-based connectomics

Area of Science:

• Neuroscience
• Network Science
• Computational Biology

Background:

• Brain function relies on complex structural and functional connections.
• Network-based analysis offers a quantitative framework to study brain topology.
• Altered connectivity is linked to neurological and psychiatric conditions.

Purpose of the Study:

• To explore the application of network-based analysis in understanding brain connectivity.
• To investigate how graph theory can model brain organization.
• To associate network alterations with developmental, aging, and disease states.

Main Methods:

• Utilizing graph theory to represent the brain as a network of nodes and edges.
• Analyzing topological organization of structural and functional brain connectivity.
• Comparing network properties across different life stages and patient populations.

Main Results:

• Identified distinct modifications in brain network topology during development and aging.
• Associated disrupted functional and structural connectivity with disorders like dementia, ALS, MS, and schizophrenia.
• Demonstrated improved understanding of clinical manifestations, including disability and cognitive impairment.

Conclusions:

• Network-based analysis provides valuable insights into brain organization and its alterations.
• This methodology enhances comprehension of neurological and psychiatric disorders.
• Future research may leverage network analysis for disorder staging, subtype identification, and outcome prediction.