The brain’s structure, despite its complexity, adheres to intricate principles of connectivity and morphology that can be explored through advanced neuroimaging, computational methods, and graph-theoretical approaches.

In our recent work, we utilized the Morphometric INverse Divergence (MIND) network to analyze subtle cortical structural changes in brain networks, while also unraveling the molecular mechanisms underlying cortical morphology and associated topological abnormalities.