Structural MRI of brain similarity networks

Area of Science:

• Neuroimaging
• Network Neuroscience
• Computational Neuroscience

Background:

• Structural MRI analytics enable mapping of individual brain network organization.
• Anatomical similarity is a key metric for understanding brain structure.
• Interpretation of MRI similarity relies on assumptions about cortical architectonics and connectivity.

Purpose of the Study:

• To review the measurement and meaning of structural MRI similarity.
• To examine assumptions linking MRI similarity to architectonic and connectional similarity.
• To contextualize MRI similarity with generative models and empirical findings.

Main Methods:

• Overview of historical and technical foundations of MRI similarity analysis.
• Comparison with structural covariance and tractography analysis.
• Integration of economic and heterochronic models of homophilic networks.

Main Results:

• Review of genetic and transcriptional architecture of MRI similarity.
• Examination of developmental and clinical studies in neurodevelopmental and neurodegenerative disorders.
• Identification of knowledge gaps for validating MRI similarity as a marker.

Conclusions:

• Structural MRI similarity offers a promising approach to mapping individual brain networks.
• Further research is needed to consolidate its validity as a marker of brain architecture and connectivity.
• Understanding the assumptions and limitations is crucial for accurate interpretation.