Eigenmode-based approach reveals a decline in brain structure-function liberality across the human lifespan.

Area of Science:

• Neuroscience
• Network Science
• Computational Biology

Background:

• Understanding the relationship between brain structure and function is crucial but challenging due to moderate correlations and high model complexity in current methods.
• The fundamental principles governing structure-function coupling remain largely unknown.

Purpose of the Study:

• To develop a novel mapping method for a concise and strong correspondence between brain structure and function.
• To investigate how this structure-function coupling changes across the human lifespan.
• To explore individual differences in brain organization related to cognition and neurological disorders.

Main Methods:

• Proposed a network mapping method based on network eigendecomposition.
• Incorporated interactions between different structural eigenmodes to explain functional connectivity.
• Applied the methodology to data across the human lifespan.

Main Results:

• A concise and strong correspondence between brain structure and function was established.
• Functional connectivity explanation significantly improved by incorporating structural eigenmode interactions.
• Functional diversity decreases with age, with functional interactions increasingly dominated by the leading functional mode.
• Structure-function coupling weakens with age, driven by decreased functional components less constrained by anatomy.

Conclusions:

• The proposed method enhances understanding of structure-function coupling from a collective, connectome-oriented perspective.
• The findings provide a refined identification of functional aspects relevant to human aging.
• The approach holds potential for mechanistic insights into individual differences in cognition, development, and neurological disorders.